From 4520e699f7d2510e43182a3f0fbe9cbe017190dd Mon Sep 17 00:00:00 2001 From: awstools Date: Thu, 14 Sep 2023 18:23:47 +0000 Subject: [PATCH] Updates SDK to v2.1458.0 --- .changes/2.1458.0.json | 17 + CHANGELOG.md | 7 +- README.md | 2 +- apis/appstream-2016-12-01.min.json | 33 +- apis/appstream-2016-12-01.normal.json | 54 +- apis/appstream-2016-12-01.waiters2.json | 12 +- apis/cloudformation-2010-05-15.normal.json | 24 +- apis/entityresolution-2018-05-10.min.json | 4 + apis/entityresolution-2018-05-10.normal.json | 68 +- .../lookoutequipment-2020-12-15.examples.json | 214 +++++ apis/lookoutequipment-2020-12-15.min.json | 272 +++++- apis/lookoutequipment-2020-12-15.normal.json | 795 ++++++++++++++++-- ...ookoutequipment-2020-12-15.paginators.json | 5 + clients/appstream.d.ts | 52 +- clients/cloudformation.d.ts | 12 +- clients/entityresolution.d.ts | 58 +- clients/lookoutequipment.d.ts | 493 +++++++++-- dist/aws-sdk-core-react-native.js | 2 +- dist/aws-sdk-react-native.js | 12 +- dist/aws-sdk.js | 6 +- dist/aws-sdk.min.js | 4 +- lib/core.js | 2 +- package.json | 2 +- 23 files changed, 1893 insertions(+), 257 deletions(-) create mode 100644 .changes/2.1458.0.json diff --git a/.changes/2.1458.0.json b/.changes/2.1458.0.json new file mode 100644 index 0000000000..41374d39ae --- /dev/null +++ b/.changes/2.1458.0.json @@ -0,0 +1,17 @@ +[ + { + "type": "feature", + "category": "AppStream", + "description": "This release introduces multi-session fleets, allowing customers to provision more than one user session on a single fleet instance." + }, + { + "type": "feature", + "category": "EntityResolution", + "description": "Changed \"ResolutionTechniques\" and \"MappedInputFields\" in workflow and schema mapping operations to be required fields." + }, + { + "type": "feature", + "category": "LookoutEquipment", + "description": "This release adds APIs for the new scheduled retraining feature." + } +] \ No newline at end of file diff --git a/CHANGELOG.md b/CHANGELOG.md index f11c2f04d2..2ce17a1aa6 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,7 +1,12 @@ # Changelog for AWS SDK for JavaScript - + +## 2.1458.0 +* feature: AppStream: This release introduces multi-session fleets, allowing customers to provision more than one user session on a single fleet instance. +* feature: EntityResolution: Changed "ResolutionTechniques" and "MappedInputFields" in workflow and schema mapping operations to be required fields. +* feature: LookoutEquipment: This release adds APIs for the new scheduled retraining feature. + ## 2.1457.0 * feature: Drs: Updated existing APIs and added new ones to support using AWS Elastic Disaster Recovery post-launch actions. Added support for new regions. * feature: Firehose: DocumentIdOptions has been added for the Amazon OpenSearch destination. diff --git a/README.md b/README.md index 1c0817ec74..9da5b56e03 100644 --- a/README.md +++ b/README.md @@ -71,7 +71,7 @@ require('aws-sdk/lib/maintenance_mode_message').suppress = true; To use the SDK in the browser, simply add the following script tag to your HTML pages: - + You can also build a custom browser SDK with your specified set of AWS services. This can allow you to reduce the SDK's size, specify different API versions of diff --git a/apis/appstream-2016-12-01.min.json b/apis/appstream-2016-12-01.min.json index 7740f95c0c..25e0da786d 100644 --- a/apis/appstream-2016-12-01.min.json +++ b/apis/appstream-2016-12-01.min.json @@ -401,6 +401,9 @@ }, "SessionScriptS3Location": { "shape": "Sw" + }, + "MaxSessionsPerInstance": { + "type": "integer" } } }, @@ -1129,7 +1132,8 @@ "Limit": { "type": "integer" }, - "AuthenticationType": {} + "AuthenticationType": {}, + "InstanceId": {} } }, "output": { @@ -1162,7 +1166,8 @@ "AuthenticationType": {}, "NetworkAccessConfiguration": { "shape": "S33" - } + }, + "InstanceId": {} } } }, @@ -1846,6 +1851,9 @@ }, "SessionScriptS3Location": { "shape": "Sw" + }, + "MaxSessionsPerInstance": { + "type": "integer" } } }, @@ -2276,12 +2284,12 @@ }, "S2l": { "type": "structure", - "required": [ - "DesiredInstances" - ], "members": { "DesiredInstances": { "type": "integer" + }, + "DesiredSessions": { + "type": "integer" } } }, @@ -2331,6 +2339,18 @@ }, "Available": { "type": "integer" + }, + "DesiredUserSessions": { + "type": "integer" + }, + "AvailableUserSessions": { + "type": "integer" + }, + "ActiveUserSessions": { + "type": "integer" + }, + "ActualUserSessions": { + "type": "integer" } } }, @@ -2377,6 +2397,9 @@ }, "SessionScriptS3Location": { "shape": "Sw" + }, + "MaxSessionsPerInstance": { + "type": "integer" } } }, diff --git a/apis/appstream-2016-12-01.normal.json b/apis/appstream-2016-12-01.normal.json index 17b99777cb..bd25242a8f 100644 --- a/apis/appstream-2016-12-01.normal.json +++ b/apis/appstream-2016-12-01.normal.json @@ -2670,13 +2670,14 @@ }, "ComputeCapacity": { "type": "structure", - "required": [ - "DesiredInstances" - ], "members": { "DesiredInstances": { "shape": "Integer", "documentation": "

The desired number of streaming instances.

" + }, + "DesiredSessions": { + "shape": "Integer", + "documentation": "

The desired number of user sessions for a multi-session fleet. This is not allowed for single-session fleets.

When you create a fleet, you must set either the DesiredSessions or DesiredInstances attribute, based on the type of fleet you create. You can’t define both attributes or leave both attributes blank.

" } }, "documentation": "

Describes the capacity for a fleet.

" @@ -2702,6 +2703,22 @@ "Available": { "shape": "Integer", "documentation": "

The number of currently available instances that can be used to stream sessions.

" + }, + "DesiredUserSessions": { + "shape": "Integer", + "documentation": "

The total number of sessions slots that are either running or pending. This represents the total number of concurrent streaming sessions your fleet can support in a steady state.

DesiredUserSessionCapacity = ActualUserSessionCapacity + PendingUserSessionCapacity

This only applies to multi-session fleets.

" + }, + "AvailableUserSessions": { + "shape": "Integer", + "documentation": "

The number of idle session slots currently available for user sessions.

AvailableUserSessionCapacity = ActualUserSessionCapacity - ActiveUserSessions

This only applies to multi-session fleets.

" + }, + "ActiveUserSessions": { + "shape": "Integer", + "documentation": "

The number of user sessions currently being used for streaming sessions. This only applies to multi-session fleets.

" + }, + "ActualUserSessions": { + "shape": "Integer", + "documentation": "

The total number of session slots that are available for streaming or are currently streaming.

ActualUserSessionCapacity = AvailableUserSessionCapacity + ActiveUserSessions

This only applies to multi-session fleets.

" } }, "documentation": "

Describes the capacity status for a fleet.

" @@ -3055,7 +3072,7 @@ }, "MaxUserDurationInSeconds": { "shape": "Integer", - "documentation": "

The maximum amount of time that a streaming session can remain active, in seconds. If users are still connected to a streaming instance five minutes before this limit is reached, they are prompted to save any open documents before being disconnected. After this time elapses, the instance is terminated and replaced by a new instance.

Specify a value between 600 and 360000.

" + "documentation": "

The maximum amount of time that a streaming session can remain active, in seconds. If users are still connected to a streaming instance five minutes before this limit is reached, they are prompted to save any open documents before being disconnected. After this time elapses, the instance is terminated and replaced by a new instance.

Specify a value between 600 and 432000.

" }, "DisconnectTimeoutInSeconds": { "shape": "Integer", @@ -3108,6 +3125,10 @@ "SessionScriptS3Location": { "shape": "S3Location", "documentation": "

The S3 location of the session scripts configuration zip file. This only applies to Elastic fleets.

" + }, + "MaxSessionsPerInstance": { + "shape": "Integer", + "documentation": "

The maximum number of user sessions on an instance. This only applies to multi-session fleets.

" } } }, @@ -4009,11 +4030,11 @@ ], "members": { "StackName": { - "shape": "String", + "shape": "Name", "documentation": "

The name of the stack. This value is case-sensitive.

" }, "FleetName": { - "shape": "String", + "shape": "Name", "documentation": "

The name of the fleet. This value is case-sensitive.

" }, "UserId": { @@ -4031,6 +4052,10 @@ "AuthenticationType": { "shape": "AuthenticationType", "documentation": "

The authentication method. Specify API for a user authenticated using a streaming URL or SAML for a SAML federated user. The default is to authenticate users using a streaming URL.

" + }, + "InstanceId": { + "shape": "String", + "documentation": "

The identifier for the instance hosting the session.

" } } }, @@ -4629,6 +4654,10 @@ "SessionScriptS3Location": { "shape": "S3Location", "documentation": "

The S3 location of the session scripts configuration zip file. This only applies to Elastic fleets.

" + }, + "MaxSessionsPerInstance": { + "shape": "Integer", + "documentation": "

The maximum number of user sessions on an instance. This only applies to multi-session fleets.

" } }, "documentation": "

Describes a fleet.

" @@ -4642,7 +4671,8 @@ "DOMAIN_JOIN_INFO", "IAM_ROLE_ARN", "USB_DEVICE_FILTER_STRINGS", - "SESSION_SCRIPT_S3_LOCATION" + "SESSION_SCRIPT_S3_LOCATION", + "MAX_SESSIONS_PER_INSTANCE" ] }, "FleetAttributes": { @@ -5384,6 +5414,10 @@ "NetworkAccessConfiguration": { "shape": "NetworkAccessConfiguration", "documentation": "

The network details for the streaming session.

" + }, + "InstanceId": { + "shape": "String", + "documentation": "

The identifier for the instance hosting the session.

" } }, "documentation": "

Describes a streaming session.

" @@ -6024,7 +6058,7 @@ "documentation": "

The ARN of the public, private, or shared image to use.

" }, "Name": { - "shape": "String", + "shape": "Name", "documentation": "

A unique name for the fleet.

" }, "InstanceType": { @@ -6099,6 +6133,10 @@ "SessionScriptS3Location": { "shape": "S3Location", "documentation": "

The S3 location of the session scripts configuration zip file. This only applies to Elastic fleets.

" + }, + "MaxSessionsPerInstance": { + "shape": "Integer", + "documentation": "

The maximum number of user sessions on an instance. This only applies to multi-session fleets.

" } } }, diff --git a/apis/appstream-2016-12-01.waiters2.json b/apis/appstream-2016-12-01.waiters2.json index 1c8dea0ded..f53f609cb7 100644 --- a/apis/appstream-2016-12-01.waiters2.json +++ b/apis/appstream-2016-12-01.waiters2.json @@ -10,19 +10,19 @@ "state": "success", "matcher": "pathAll", "argument": "Fleets[].State", - "expected": "RUNNING" + "expected": "ACTIVE" }, { "state": "failure", "matcher": "pathAny", "argument": "Fleets[].State", - "expected": "STOPPING" + "expected": "PENDING_DEACTIVATE" }, { "state": "failure", "matcher": "pathAny", "argument": "Fleets[].State", - "expected": "STOPPED" + "expected": "INACTIVE" } ] }, @@ -35,19 +35,19 @@ "state": "success", "matcher": "pathAll", "argument": "Fleets[].State", - "expected": "STOPPED" + "expected": "INACTIVE" }, { "state": "failure", "matcher": "pathAny", "argument": "Fleets[].State", - "expected": "STARTING" + "expected": "PENDING_ACTIVATE" }, { "state": "failure", "matcher": "pathAny", "argument": "Fleets[].State", - "expected": "RUNNING" + "expected": "ACTIVE" } ] } diff --git a/apis/cloudformation-2010-05-15.normal.json b/apis/cloudformation-2010-05-15.normal.json index d26e80de7d..7f42b96b8f 100644 --- a/apis/cloudformation-2010-05-15.normal.json +++ b/apis/cloudformation-2010-05-15.normal.json @@ -2219,7 +2219,7 @@ }, "RetainExceptOnCreate": { "shape": "RetainExceptOnCreate", - "documentation": "

This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute.

" + "documentation": "

When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain.

Default: false

" } }, "documentation": "

The input for CreateStack action.

" @@ -2317,7 +2317,7 @@ }, "Capabilities": { "shape": "Capabilities", - "documentation": "

In some cases, you must explicitly acknowledge that your stack set template contains certain capabilities in order for CloudFormation to create the stack set and related stack instances.

" + "documentation": "

In some cases, you must explicitly acknowledge that your stack set template contains certain capabilities in order for CloudFormation to create the stack set and related stack instances.

" }, "Tags": { "shape": "Tags", @@ -2325,7 +2325,7 @@ }, "AdministrationRoleARN": { "shape": "RoleARN", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role to use to create this stack set.

Specify an IAM role only if you are using customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Prerequisites: Granting Permissions for Stack Set Operations in the CloudFormation User Guide.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role to use to create this stack set.

Specify an IAM role only if you are using customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Prerequisites: Granting Permissions for Stack Set Operations in the CloudFormation User Guide.

" }, "ExecutionRoleName": { "shape": "ExecutionRoleName", @@ -3077,7 +3077,7 @@ "members": { "StackName": { "shape": "StackName", - "documentation": "

If you don't pass a parameter to StackName, the API returns a response that describes all resources in the account. This requires ListStacks and DescribeStacks permissions.

The IAM policy below can be added to IAM policies when you want to limit resource-level permissions and avoid returning a response when no parameter is sent in the request:

{ \"Version\": \"2012-10-17\", \"Statement\": [{ \"Effect\": \"Deny\", \"Action\": \"cloudformation:DescribeStacks\", \"NotResource\": \"arn:aws:cloudformation:*:*:stack/*/*\" }] }

The name or the unique stack ID that's associated with the stack, which aren't always interchangeable:

Default: There is no default value.

" + "documentation": "

If you don't pass a parameter to StackName, the API returns a response that describes all resources in the account, which can impact performance. This requires ListStacks and DescribeStacks permissions.

Consider using the ListStacks API if you're not passing a parameter to StackName.

The IAM policy below can be added to IAM policies when you want to limit resource-level permissions and avoid returning a response when no parameter is sent in the request:

{ \"Version\": \"2012-10-17\", \"Statement\": [{ \"Effect\": \"Deny\", \"Action\": \"cloudformation:DescribeStacks\", \"NotResource\": \"arn:aws:cloudformation:*:*:stack/*/*\" }] }

The name or the unique stack ID that's associated with the stack, which aren't always interchangeable:

Default: There is no default value.

" }, "NextToken": { "shape": "NextToken", @@ -3461,7 +3461,7 @@ }, "RetainExceptOnCreate": { "shape": "RetainExceptOnCreate", - "documentation": "

This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute.

" + "documentation": "

When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain.

Default: false

" } }, "documentation": "

The input for the ExecuteChangeSet action.

" @@ -5318,7 +5318,7 @@ }, "RetainExceptOnCreate": { "shape": "RetainExceptOnCreate", - "documentation": "

This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute.

" + "documentation": "

When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain.

Default: false

" } } }, @@ -5582,7 +5582,7 @@ }, "RetainExceptOnCreate": { "shape": "RetainExceptOnCreate", - "documentation": "

This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute.

" + "documentation": "

When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain.

Default: false

" } }, "documentation": "

The Stack data type.

" @@ -6324,7 +6324,7 @@ }, "AdministrationRoleARN": { "shape": "RoleARN", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role used to create or update the stack set.

Use customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Prerequisites: Granting Permissions for Stack Set Operations in the CloudFormation User Guide.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role used to create or update the stack set.

Use customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Prerequisites: Granting Permissions for Stack Set Operations in the CloudFormation User Guide.

" }, "ExecutionRoleName": { "shape": "ExecutionRoleName", @@ -6455,7 +6455,7 @@ }, "AdministrationRoleARN": { "shape": "RoleARN", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role used to perform this stack set operation.

Use customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Define Permissions for Multiple Administrators in the CloudFormation User Guide.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role used to perform this stack set operation.

Use customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Define Permissions for Multiple Administrators in the CloudFormation User Guide.

" }, "ExecutionRoleName": { "shape": "ExecutionRoleName", @@ -7355,7 +7355,7 @@ }, "RetainExceptOnCreate": { "shape": "RetainExceptOnCreate", - "documentation": "

This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute.

" + "documentation": "

When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain.

Default: false

" } }, "documentation": "

The input for an UpdateStack action.

" @@ -7453,7 +7453,7 @@ }, "Capabilities": { "shape": "Capabilities", - "documentation": "

In some cases, you must explicitly acknowledge that your stack template contains certain capabilities in order for CloudFormation to update the stack set and its associated stack instances.

" + "documentation": "

In some cases, you must explicitly acknowledge that your stack template contains certain capabilities in order for CloudFormation to update the stack set and its associated stack instances.

" }, "Tags": { "shape": "Tags", @@ -7465,7 +7465,7 @@ }, "AdministrationRoleARN": { "shape": "RoleARN", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role to use to update this stack set.

Specify an IAM role only if you are using customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Granting Permissions for Stack Set Operations in the CloudFormation User Guide.

If you specified a customized administrator role when you created the stack set, you must specify a customized administrator role, even if it is the same customized administrator role used with this stack set previously.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role to use to update this stack set.

Specify an IAM role only if you are using customized administrator roles to control which users or groups can manage specific stack sets within the same administrator account. For more information, see Granting Permissions for Stack Set Operations in the CloudFormation User Guide.

If you specified a customized administrator role when you created the stack set, you must specify a customized administrator role, even if it is the same customized administrator role used with this stack set previously.

" }, "ExecutionRoleName": { "shape": "ExecutionRoleName", diff --git a/apis/entityresolution-2018-05-10.min.json b/apis/entityresolution-2018-05-10.min.json index 3c03979104..864d09c68d 100644 --- a/apis/entityresolution-2018-05-10.min.json +++ b/apis/entityresolution-2018-05-10.min.json @@ -86,6 +86,7 @@ "input": { "type": "structure", "required": [ + "mappedInputFields", "schemaName" ], "members": { @@ -767,6 +768,9 @@ }, "Sh": { "type": "structure", + "required": [ + "resolutionType" + ], "members": { "resolutionType": {}, "ruleBasedProperties": { diff --git a/apis/entityresolution-2018-05-10.normal.json b/apis/entityresolution-2018-05-10.normal.json index f33d2cd125..3d74bea806 100644 --- a/apis/entityresolution-2018-05-10.normal.json +++ b/apis/entityresolution-2018-05-10.normal.json @@ -333,7 +333,7 @@ "shape": "ValidationException" } ], - "documentation": "

Returns a list of all the MatchingWorkflows that have been created for an AWS account.

" + "documentation": "

Returns a list of all the MatchingWorkflows that have been created for an Amazon Web Services account.

" }, "ListSchemaMappings": { "name": "ListSchemaMappings", @@ -362,7 +362,7 @@ "shape": "ValidationException" } ], - "documentation": "

Returns a list of all the SchemaMappings that have been created for an AWS account.

" + "documentation": "

Returns a list of all the SchemaMappings that have been created for an Amazon Web Services account.

" }, "ListTagsForResource": { "name": "ListTagsForResource", @@ -388,7 +388,7 @@ "shape": "ValidationException" } ], - "documentation": "

Displays the tags associated with an AWS Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged.

" + "documentation": "

Displays the tags associated with an Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged.

" }, "StartMatchingJob": { "name": "StartMatchingJob", @@ -452,7 +452,7 @@ "shape": "ValidationException" } ], - "documentation": "

Assigns one or more tags (key-value pairs) to the specified AWS Entity Resolution resource. Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. Tags don't have any semantic meaning to AWS and are interpreted strictly as strings of characters. You can use the TagResource action with a resource that already has tags. If you specify a new tag key, this tag is appended to the list of tags associated with the resource. If you specify a tag key that is already associated with the resource, the new tag value that you specify replaces the previous value for that tag.

" + "documentation": "

Assigns one or more tags (key-value pairs) to the specified Entity Resolution resource. Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values. In Entity Resolution, SchemaMapping and MatchingWorkflow can be tagged. Tags don't have any semantic meaning to Amazon Web Services and are interpreted strictly as strings of characters. You can use the TagResource action with a resource that already has tags. If you specify a new tag key, this tag is appended to the list of tags associated with the resource. If you specify a tag key that is already associated with the resource, the new tag value that you specify replaces the previous value for that tag.

" }, "UntagResource": { "name": "UntagResource", @@ -475,7 +475,7 @@ "shape": "ResourceNotFoundException" } ], - "documentation": "

Removes one or more tags from the specified AWS Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged.

", + "documentation": "

Removes one or more tags from the specified Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged.

", "idempotent": true }, "UpdateMatchingWorkflow": { @@ -558,11 +558,11 @@ }, "resolutionTechniques": { "shape": "ResolutionTechniques", - "documentation": "

An object which defines the resolutionType and the ruleBasedProperties

" + "documentation": "

An object which defines the resolutionType and the ruleBasedProperties.

" }, "roleArn": { "shape": "String", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" }, "tags": { "shape": "TagMap", @@ -603,11 +603,11 @@ }, "resolutionTechniques": { "shape": "ResolutionTechniques", - "documentation": "

An object which defines the resolutionType and the ruleBasedProperties

" + "documentation": "

An object which defines the resolutionType and the ruleBasedProperties.

" }, "roleArn": { "shape": "String", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" }, "workflowArn": { "shape": "MatchingWorkflowArn", @@ -622,6 +622,7 @@ "CreateSchemaMappingInput": { "type": "structure", "required": [ + "mappedInputFields", "schemaName" ], "members": { @@ -827,7 +828,7 @@ }, "status": { "shape": "JobStatus", - "documentation": "

The current status of the job. Either running, succeeded, queued, or failed.

" + "documentation": "

The current status of the job.

" } } }, @@ -880,11 +881,11 @@ }, "resolutionTechniques": { "shape": "ResolutionTechniques", - "documentation": "

An object which defines the resolutionType and the ruleBasedProperties

" + "documentation": "

An object which defines the resolutionType and the ruleBasedProperties.

" }, "roleArn": { "shape": "String", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to access resources on your behalf.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to access resources on your behalf.

" }, "tags": { "shape": "TagMap", @@ -1035,7 +1036,7 @@ }, "recordsNotProcessed": { "shape": "Integer", - "documentation": "

The total number of records that did not get processed,

" + "documentation": "

The total number of records that did not get processed.

" }, "totalRecordsProcessed": { "shape": "Integer", @@ -1075,7 +1076,7 @@ }, "status": { "shape": "JobStatus", - "documentation": "

The current status of the job. Either running, succeeded, queued, or failed.

" + "documentation": "

The current status of the job.

" } }, "documentation": "

An object containing the JobId, Status, StartTime, and EndTime of a job.

" @@ -1121,7 +1122,7 @@ "members": { "jobs": { "shape": "JobList", - "documentation": "

A list of JobSummary objects, each of which contain the ID, status, start time, and end time of a job.

" + "documentation": "

A list of JobSummary objects, each of which contain the ID, status, start time, and end time of a job.

" }, "nextToken": { "shape": "NextToken", @@ -1284,7 +1285,7 @@ "documentation": "

A name of a column to be written to the output. This must be an InputField name in the schema mapping.

" } }, - "documentation": "

A list of OutputAttribute objects, each of which have the fields Name and Hashed. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.

" + "documentation": "

A list of OutputAttribute objects, each of which have the fields Name and Hashed. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.

" }, "OutputSource": { "type": "structure", @@ -1303,14 +1304,14 @@ }, "output": { "shape": "OutputSourceOutputList", - "documentation": "

A list of OutputAttribute objects, each of which have the fields Name and Hashed. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.

" + "documentation": "

A list of OutputAttribute objects, each of which have the fields Name and Hashed. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.

" }, "outputS3Path": { - "shape": "OutputSourceOutputS3PathString", + "shape": "S3Path", "documentation": "

The S3 path to which Entity Resolution will write the output table.

" } }, - "documentation": "

A list of OutputAttribute objects, each of which have the fields Name and Hashed. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.

" + "documentation": "

A list of OutputAttribute objects, each of which have the fields Name and Hashed. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.

" }, "OutputSourceConfig": { "type": "list", @@ -1328,10 +1329,6 @@ "max": 750, "min": 0 }, - "OutputSourceOutputS3PathString": { - "type": "string", - "pattern": "^s3://([^/]+)/?(.*?([^/]+)/?)$" - }, "RecordAttributeMap": { "type": "map", "key": { @@ -1356,17 +1353,20 @@ }, "ResolutionTechniques": { "type": "structure", + "required": [ + "resolutionType" + ], "members": { "resolutionType": { "shape": "ResolutionType", - "documentation": "

There are two types of matching, RULE_MATCHING and ML_MATCHING

" + "documentation": "

The type of matching. There are two types of matching: RULE_MATCHING and ML_MATCHING.

" }, "ruleBasedProperties": { "shape": "RuleBasedProperties", "documentation": "

An object which defines the list of matching rules to run and has a field Rules, which is a list of rule objects.

" } }, - "documentation": "

An object which defines the resolutionType and the ruleBasedProperties

" + "documentation": "

An object which defines the resolutionType and the ruleBasedProperties.

" }, "ResolutionType": { "type": "string", @@ -1402,11 +1402,11 @@ "members": { "attributeMatchingModel": { "shape": "AttributeMatchingModel", - "documentation": "

You can either choose ONE_TO_ONE or MANY_TO_MANY as the AttributeMatchingModel. When choosing MANY_TO_MANY, the system can match attribute across the sub-types of an attribute type. For example, if the value of the Email field of Profile A and the value of BusinessEmail field of Profile B matches, the two profiles are matched on the Email type. When choosing ONE_TO_ONE the system can only match if the sub-types are exact matches. For example, only when the value of the Email field of Profile A and the value of the Email field of Profile B matches, the two profiles are matched on the Email type.

" + "documentation": "

The comparison type. You can either choose ONE_TO_ONE or MANY_TO_MANY as the AttributeMatchingModel. When choosing MANY_TO_MANY, the system can match attributes across the sub-types of an attribute type. For example, if the value of the Email field of Profile A and the value of BusinessEmail field of Profile B matches, the two profiles are matched on the Email type. When choosing ONE_TO_ONE ,the system can only match if the sub-types are exact matches. For example, only when the value of the Email field of Profile A and the value of the Email field of Profile B matches, the two profiles are matched on the Email type.

" }, "rules": { "shape": "RuleBasedPropertiesRulesList", - "documentation": "

A list of Rule objects, each of which have fields RuleName and MatchingKeys.

" + "documentation": "

A list of Rule objects, each of which have fields RuleName and MatchingKeys.

" } }, "documentation": "

An object which defines the list of matching rules to run and has a field Rules, which is a list of rule objects.

" @@ -1433,6 +1433,10 @@ "min": 0, "pattern": "^[a-zA-Z_0-9- \\t]*$" }, + "S3Path": { + "type": "string", + "pattern": "^s3://([^/]+)/?(.*?([^/]+)/?)$" + }, "SchemaAttributeType": { "type": "string", "enum": [ @@ -1474,7 +1478,7 @@ }, "matchKey": { "shape": "AttributeName", - "documentation": "

A key that allows grouping of multiple input attributes into a unified matching group. For example, let's consider a scenario where the source table contains various addresses, such as business_address and shipping_address. By assigning the MatchKey Address' to both attributes, Entity Resolution will match records across these fields to create a consolidated matching group. If no MatchKey is specified for a column, it won't be utilized for matching purposes but will still be included in the output table.

" + "documentation": "

A key that allows grouping of multiple input attributes into a unified matching group. For example, let's consider a scenario where the source table contains various addresses, such as business_address and shipping_address. By assigning the MatchKey Address to both attributes, Entity Resolution will match records across these fields to create a consolidated matching group. If no MatchKey is specified for a column, it won't be utilized for matching purposes but will still be included in the output table.

" }, "type": { "shape": "SchemaAttributeType", @@ -1666,11 +1670,11 @@ }, "resolutionTechniques": { "shape": "ResolutionTechniques", - "documentation": "

An object which defines the resolutionType and the ruleBasedProperties

" + "documentation": "

An object which defines the resolutionType and the ruleBasedProperties.

" }, "roleArn": { "shape": "String", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" }, "workflowName": { "shape": "EntityName", @@ -1712,7 +1716,7 @@ }, "roleArn": { "shape": "String", - "documentation": "

The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" + "documentation": "

The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.

" }, "workflowName": { "shape": "EntityName", @@ -1725,5 +1729,5 @@ "pattern": "^arn:(aws|aws-us-gov|aws-cn):(entityresolution):.*:[0-9]+:((schemamapping|matchingworkflow)/[a-zA-Z0-9_-]+)$" } }, - "documentation": "

Welcome to the AWS Entity Resolution API Reference.

AWS Entity Resolution is an AWS service that provides pre-configured entity resolution capabilities that enable developers and analysts at advertising and marketing companies to build an accurate and complete view of their consumers.

With AWS Entity Resolution, you have the ability to match source records containing consumer identifiers, such as name, email address, and phone number. This holds true even when these records have incomplete or conflicting identifiers. For example, AWS Entity Resolution can effectively match a source record from a customer relationship management (CRM) system, which includes account information like first name, last name, postal address, phone number, and email address, with a source record from a marketing system containing campaign information, such as username and email address.

To learn more about AWS Entity Resolution concepts, procedures, and best practices, see the AWS Entity Resolution User Guide.

" + "documentation": "

Welcome to the Entity Resolution API Reference.

Entity Resolution is an Amazon Web Services service that provides pre-configured entity resolution capabilities that enable developers and analysts at advertising and marketing companies to build an accurate and complete view of their consumers.

With Entity Resolution, you can match source records containing consumer identifiers, such as name, email address, and phone number. This is true even when these records have incomplete or conflicting identifiers. For example, Entity Resolution can effectively match a source record from a customer relationship management (CRM) system with a source record from a marketing system containing campaign information.

To learn more about Entity Resolution concepts, procedures, and best practices, see the Entity Resolution User Guide.

" } \ No newline at end of file diff --git a/apis/lookoutequipment-2020-12-15.examples.json b/apis/lookoutequipment-2020-12-15.examples.json index 0ea7e3b0bb..1eb4987edc 100644 --- a/apis/lookoutequipment-2020-12-15.examples.json +++ b/apis/lookoutequipment-2020-12-15.examples.json @@ -1,5 +1,219 @@ { "version": "1.0", "examples": { + "CreateRetrainingScheduler": [ + { + "input": { + "ClientToken": "sample-client-token", + "LookbackWindow": "P360D", + "ModelName": "sample-model", + "PromoteMode": "MANUAL", + "RetrainingFrequency": "P1M" + }, + "output": { + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", + "ModelName": "sample-model", + "Status": "PENDING" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "creates-a-retraining-scheduler-with-manual-promote-mode-1694018486212", + "title": "Creates a retraining scheduler with manual promote mode" + }, + { + "input": { + "ClientToken": "sample-client-token", + "LookbackWindow": "P360D", + "ModelName": "sample-model", + "RetrainingFrequency": "P1M", + "RetrainingStartDate": "2024-01-01T00:00:00Z" + }, + "output": { + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", + "ModelName": "sample-model", + "Status": "PENDING" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "creates-a-retraining-scheduler-with-a-specific-start-date-1694018790519", + "title": "Creates a retraining scheduler with a specific start date" + } + ], + "DeleteRetrainingScheduler": [ + { + "input": { + "ModelName": "sample-model" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "deletes-a-retraining-scheduler-1694019240097", + "title": "Deletes a retraining scheduler" + } + ], + "DescribeRetrainingScheduler": [ + { + "input": { + "ModelName": "sample-model" + }, + "output": { + "CreatedAt": "2023-10-01T15:00:00Z", + "LookbackWindow": "P360D", + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", + "ModelName": "sample-model", + "PromoteMode": "MANAGED", + "RetrainingFrequency": "P1M", + "RetrainingStartDate": "2023-11-01T00:00:00Z", + "Status": "RUNNING", + "UpdatedAt": "2023-10-01T15:00:00Z" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "describes-a-retraining-scheduler-1694019344252", + "title": "Describes a retraining scheduler" + } + ], + "ListRetrainingSchedulers": [ + { + "input": { + "MaxResults": 50 + }, + "output": { + "RetrainingSchedulerSummaries": [ + { + "LookbackWindow": "P180D", + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-1/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", + "ModelName": "sample-model-1", + "RetrainingFrequency": "P1M", + "RetrainingStartDate": "2023-06-01T00:00:00Z", + "Status": "RUNNING" + }, + { + "LookbackWindow": "P180D", + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-2/a1b2c3d4-5678-90ab-cdef-EXAMPLE22222", + "ModelName": "sample-model-2", + "RetrainingFrequency": "P30D", + "RetrainingStartDate": "2023-08-15T00:00:00Z", + "Status": "RUNNING" + }, + { + "LookbackWindow": "P360D", + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-3/a1b2c3d4-5678-90ab-cdef-EXAMPLE33333", + "ModelName": "sample-model-3", + "RetrainingFrequency": "P1M", + "RetrainingStartDate": "2023-09-01T00:00:00Z", + "Status": "STOPPED" + } + ] + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "listing-retraining-schedulers-1694016740503", + "title": "Listing retraining schedulers" + } + ], + "StartRetrainingScheduler": [ + { + "input": { + "ModelName": "sample-model" + }, + "output": { + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", + "ModelName": "sample-model", + "Status": "PENDING" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "starts-a-retraining-scheduler-1694019629413", + "title": "Starts a retraining scheduler" + } + ], + "StopRetrainingScheduler": [ + { + "input": { + "ModelName": "sample-model" + }, + "output": { + "ModelArn": "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", + "ModelName": "sample-model", + "Status": "STOPPING" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "stops-a-retraining-scheduler-1694019734149", + "title": "Stops a retraining scheduler" + } + ], + "UpdateModel": [ + { + "input": { + "LabelsInputConfiguration": { + "LabelGroupName": "sample-label-group" + }, + "ModelName": "sample-model" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "updates-a-model-1694020683458", + "title": "Updates a model" + } + ], + "UpdateRetrainingScheduler": [ + { + "input": { + "ModelName": "sample-model", + "RetrainingFrequency": "P1Y", + "RetrainingStartDate": "2024-01-01T00:00:00Z" + }, + "comments": { + "input": { + }, + "output": { + } + }, + "description": "", + "id": "updates-a-retraining-scheduler-1694019840918", + "title": "Updates a retraining scheduler" + } + ] } } diff --git a/apis/lookoutequipment-2020-12-15.min.json b/apis/lookoutequipment-2020-12-15.min.json index 8540967efa..c04910d703 100644 --- a/apis/lookoutequipment-2020-12-15.min.json +++ b/apis/lookoutequipment-2020-12-15.min.json @@ -200,6 +200,37 @@ } } }, + "CreateRetrainingScheduler": { + "input": { + "type": "structure", + "required": [ + "ModelName", + "RetrainingFrequency", + "LookbackWindow", + "ClientToken" + ], + "members": { + "ModelName": {}, + "RetrainingStartDate": { + "type": "timestamp" + }, + "RetrainingFrequency": {}, + "LookbackWindow": {}, + "PromoteMode": {}, + "ClientToken": { + "idempotencyToken": true + } + } + }, + "output": { + "type": "structure", + "members": { + "ModelName": {}, + "ModelArn": {}, + "Status": {} + } + } + }, "DeleteDataset": { "input": { "type": "structure", @@ -268,6 +299,17 @@ } } }, + "DeleteRetrainingScheduler": { + "input": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": {} + } + } + }, "DescribeDataIngestionJob": { "input": { "type": "structure", @@ -284,7 +326,7 @@ "JobId": {}, "DatasetArn": {}, "IngestionInputConfiguration": { - "shape": "S1v" + "shape": "S22" }, "RoleArn": {}, "CreatedAt": { @@ -293,10 +335,10 @@ "Status": {}, "FailedReason": {}, "DataQualitySummary": { - "shape": "S20" + "shape": "S27" }, "IngestedFilesSummary": { - "shape": "S29" + "shape": "S2g" }, "StatusDetail": {}, "IngestedDataSize": { @@ -339,13 +381,13 @@ }, "ServerSideKmsKeyId": {}, "IngestionInputConfiguration": { - "shape": "S1v" + "shape": "S22" }, "DataQualitySummary": { - "shape": "S20" + "shape": "S27" }, "IngestedFilesSummary": { - "shape": "S29" + "shape": "S2g" }, "RoleArn": {}, "DataStartTime": { @@ -537,7 +579,31 @@ "PreviousActiveModelVersionArn": {}, "PreviousModelVersionActivatedAt": { "type": "timestamp" - } + }, + "PriorModelMetrics": { + "jsonvalue": true + }, + "LatestScheduledRetrainingFailedReason": {}, + "LatestScheduledRetrainingStatus": {}, + "LatestScheduledRetrainingModelVersion": { + "type": "long" + }, + "LatestScheduledRetrainingStartTime": { + "type": "timestamp" + }, + "LatestScheduledRetrainingAvailableDataInDays": { + "type": "integer" + }, + "NextScheduledRetrainingStartDate": { + "type": "timestamp" + }, + "AccumulatedInferenceDataStartTime": { + "type": "timestamp" + }, + "AccumulatedInferenceDataEndTime": { + "type": "timestamp" + }, + "RetrainingSchedulerStatus": {} } } }, @@ -613,7 +679,13 @@ }, "ImportedDataSizeInBytes": { "type": "long" - } + }, + "PriorModelMetrics": {}, + "RetrainingAvailableDataInDays": { + "type": "integer" + }, + "AutoPromotionResult": {}, + "AutoPromotionResultReason": {} } } }, @@ -641,6 +713,37 @@ } } }, + "DescribeRetrainingScheduler": { + "input": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": {} + } + }, + "output": { + "type": "structure", + "members": { + "ModelName": {}, + "ModelArn": {}, + "RetrainingStartDate": { + "type": "timestamp" + }, + "RetrainingFrequency": {}, + "LookbackWindow": {}, + "Status": {}, + "PromoteMode": {}, + "CreatedAt": { + "type": "timestamp" + }, + "UpdatedAt": { + "type": "timestamp" + } + } + } + }, "ImportDataset": { "input": { "type": "structure", @@ -692,7 +795,8 @@ "ServerSideKmsKeyId": {}, "Tags": { "shape": "S7" - } + }, + "InferenceDataImportStrategy": {} } }, "output": { @@ -733,7 +837,7 @@ "DatasetName": {}, "DatasetArn": {}, "IngestionInputConfiguration": { - "shape": "S1v" + "shape": "S22" }, "Status": {} } @@ -873,10 +977,14 @@ "shape": "Sr" }, "CustomerResultObject": { - "shape": "S2b" + "shape": "S2i" }, "Status": {}, - "FailedReason": {} + "FailedReason": {}, + "ModelVersion": { + "type": "long" + }, + "ModelVersionArn": {} } } } @@ -1094,13 +1202,59 @@ "ActiveModelVersion": { "type": "long" }, - "ActiveModelVersionArn": {} + "ActiveModelVersionArn": {}, + "LatestScheduledRetrainingStatus": {}, + "LatestScheduledRetrainingModelVersion": { + "type": "long" + }, + "LatestScheduledRetrainingStartTime": { + "type": "timestamp" + }, + "NextScheduledRetrainingStartDate": { + "type": "timestamp" + }, + "RetrainingSchedulerStatus": {} } } } } } }, + "ListRetrainingSchedulers": { + "input": { + "type": "structure", + "members": { + "ModelNameBeginsWith": {}, + "Status": {}, + "NextToken": {}, + "MaxResults": { + "type": "integer" + } + } + }, + "output": { + "type": "structure", + "members": { + "RetrainingSchedulerSummaries": { + "type": "list", + "member": { + "type": "structure", + "members": { + "ModelName": {}, + "ModelArn": {}, + "Status": {}, + "RetrainingStartDate": { + "type": "timestamp" + }, + "RetrainingFrequency": {}, + "LookbackWindow": {} + } + } + }, + "NextToken": {} + } + } + }, "ListSensorStatistics": { "input": { "type": "structure", @@ -1130,16 +1284,16 @@ "type": "boolean" }, "MissingValues": { - "shape": "S4g" + "shape": "S4w" }, "InvalidValues": { - "shape": "S4g" + "shape": "S4w" }, "InvalidDateEntries": { - "shape": "S4g" + "shape": "S4w" }, "DuplicateTimestamps": { - "shape": "S4g" + "shape": "S4w" }, "CategoricalValues": { "type": "structure", @@ -1256,7 +1410,7 @@ "members": { "DatasetName": {}, "IngestionInputConfiguration": { - "shape": "S1v" + "shape": "S22" }, "RoleArn": {}, "ClientToken": { @@ -1293,6 +1447,25 @@ } } }, + "StartRetrainingScheduler": { + "input": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": {} + } + }, + "output": { + "type": "structure", + "members": { + "ModelName": {}, + "ModelArn": {}, + "Status": {} + } + } + }, "StopInferenceScheduler": { "input": { "type": "structure", @@ -1314,6 +1487,25 @@ } } }, + "StopRetrainingScheduler": { + "input": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": {} + } + }, + "output": { + "type": "structure", + "members": { + "ModelName": {}, + "ModelArn": {}, + "Status": {} + } + } + }, "TagResource": { "input": { "type": "structure", @@ -1418,6 +1610,38 @@ } } } + }, + "UpdateModel": { + "input": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": {}, + "LabelsInputConfiguration": { + "shape": "S1c" + }, + "RoleArn": {} + } + } + }, + "UpdateRetrainingScheduler": { + "input": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": {}, + "RetrainingStartDate": { + "type": "timestamp" + }, + "RetrainingFrequency": {}, + "LookbackWindow": {}, + "PromoteMode": {} + } + } } }, "shapes": { @@ -1511,7 +1735,7 @@ "TargetSamplingRate": {} } }, - "S1v": { + "S22": { "type": "structure", "required": [ "S3InputConfiguration" @@ -1530,7 +1754,7 @@ } } }, - "S20": { + "S27": { "type": "structure", "required": [ "InsufficientSensorData", @@ -1625,7 +1849,7 @@ } } }, - "S29": { + "S2g": { "type": "structure", "required": [ "TotalNumberOfFiles", @@ -1641,12 +1865,12 @@ "DiscardedFiles": { "type": "list", "member": { - "shape": "S2b" + "shape": "S2i" } } } }, - "S2b": { + "S2i": { "type": "structure", "required": [ "Bucket", @@ -1657,7 +1881,7 @@ "Key": {} } }, - "S4g": { + "S4w": { "type": "structure", "required": [ "Count", diff --git a/apis/lookoutequipment-2020-12-15.normal.json b/apis/lookoutequipment-2020-12-15.normal.json index 4cedaf3a97..358f503f98 100644 --- a/apis/lookoutequipment-2020-12-15.normal.json +++ b/apis/lookoutequipment-2020-12-15.normal.json @@ -190,7 +190,41 @@ "shape": "AccessDeniedException" } ], - "documentation": "

Creates an ML model for data inference.

A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred.

Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.

" + "documentation": "

Creates a machine learning model for data inference.

A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred.

Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.

" + }, + "CreateRetrainingScheduler": { + "name": "CreateRetrainingScheduler", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "CreateRetrainingSchedulerRequest" + }, + "output": { + "shape": "CreateRetrainingSchedulerResponse" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ConflictException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Creates a retraining scheduler on the specified model.

" }, "DeleteDataset": { "name": "DeleteDataset", @@ -252,7 +286,7 @@ "shape": "InternalServerException" } ], - "documentation": "

Deletes an inference scheduler that has been set up. Already processed output results are not affected.

" + "documentation": "

Deletes an inference scheduler that has been set up. Prior inference results will not be deleted.

" }, "DeleteLabel": { "name": "DeleteLabel", @@ -345,7 +379,7 @@ "shape": "ValidationException" } ], - "documentation": "

Deletes an ML model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up.

" + "documentation": "

Deletes a machine learning model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up.

" }, "DeleteResourcePolicy": { "name": "DeleteResourcePolicy", @@ -378,6 +412,37 @@ ], "documentation": "

Deletes the resource policy attached to the resource.

" }, + "DeleteRetrainingScheduler": { + "name": "DeleteRetrainingScheduler", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "DeleteRetrainingSchedulerRequest" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ConflictException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Deletes a retraining scheduler from a model. The retraining scheduler must be in the STOPPED status.

" + }, "DescribeDataIngestionJob": { "name": "DescribeDataIngestionJob", "http": { @@ -562,7 +627,7 @@ "shape": "InternalServerException" } ], - "documentation": "

Provides a JSON containing the overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on.

" + "documentation": "

Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on.

" }, "DescribeModelVersion": { "name": "DescribeModelVersion", @@ -626,6 +691,37 @@ ], "documentation": "

Provides the details of a resource policy attached to a resource.

" }, + "DescribeRetrainingScheduler": { + "name": "DescribeRetrainingScheduler", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "DescribeRetrainingSchedulerRequest" + }, + "output": { + "shape": "DescribeRetrainingSchedulerResponse" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.

" + }, "ImportDataset": { "name": "ImportDataset", "http": { @@ -961,6 +1057,34 @@ ], "documentation": "

Generates a list of all models in the account, including model name and ARN, dataset, and status.

" }, + "ListRetrainingSchedulers": { + "name": "ListRetrainingSchedulers", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "ListRetrainingSchedulersRequest" + }, + "output": { + "shape": "ListRetrainingSchedulersResponse" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Lists all retraining schedulers in your account, filtering by model name prefix and status.

" + }, "ListSensorStatistics": { "name": "ListSensorStatistics", "http": { @@ -1131,6 +1255,40 @@ ], "documentation": "

Starts an inference scheduler.

" }, + "StartRetrainingScheduler": { + "name": "StartRetrainingScheduler", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "StartRetrainingSchedulerRequest" + }, + "output": { + "shape": "StartRetrainingSchedulerResponse" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ConflictException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Starts a retraining scheduler.

" + }, "StopInferenceScheduler": { "name": "StopInferenceScheduler", "http": { @@ -1165,6 +1323,40 @@ ], "documentation": "

Stops an inference scheduler.

" }, + "StopRetrainingScheduler": { + "name": "StopRetrainingScheduler", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "StopRetrainingSchedulerRequest" + }, + "output": { + "shape": "StopRetrainingSchedulerResponse" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ConflictException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Stops a retraining scheduler.

" + }, "TagResource": { "name": "TagResource", "http": { @@ -1325,6 +1517,68 @@ } ], "documentation": "

Updates the label group.

" + }, + "UpdateModel": { + "name": "UpdateModel", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "UpdateModelRequest" + }, + "errors": [ + { + "shape": "ConflictException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ValidationException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Updates a model in the account.

" + }, + "UpdateRetrainingScheduler": { + "name": "UpdateRetrainingScheduler", + "http": { + "method": "POST", + "requestUri": "/" + }, + "input": { + "shape": "UpdateRetrainingSchedulerRequest" + }, + "errors": [ + { + "shape": "ValidationException" + }, + { + "shape": "ResourceNotFoundException" + }, + { + "shape": "ConflictException" + }, + { + "shape": "ThrottlingException" + }, + { + "shape": "AccessDeniedException" + }, + { + "shape": "InternalServerException" + } + ], + "documentation": "

Updates a retraining scheduler.

" } }, "shapes": { @@ -1333,6 +1587,21 @@ "max": 1011, "min": 1 }, + "AutoPromotionResult": { + "type": "string", + "enum": [ + "MODEL_PROMOTED", + "MODEL_NOT_PROMOTED", + "RETRAINING_INTERNAL_ERROR", + "RETRAINING_CUSTOMER_ERROR", + "RETRAINING_CANCELLED" + ] + }, + "AutoPromotionResultReason": { + "type": "string", + "max": 256, + "min": 1 + }, "Boolean": { "type": "boolean" }, @@ -1456,7 +1725,7 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the previously trained ML model being used to create the inference scheduler.

" + "documentation": "

The name of the previously trained machine learning model being used to create the inference scheduler.

" }, "InferenceSchedulerName": { "shape": "InferenceSchedulerName", @@ -1617,19 +1886,19 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name for the ML model to be created.

" + "documentation": "

The name for the machine learning model to be created.

" }, "DatasetName": { "shape": "DatasetIdentifier", - "documentation": "

The name of the dataset for the ML model being created.

" + "documentation": "

The name of the dataset for the machine learning model being created.

" }, "DatasetSchema": { "shape": "DatasetSchema", - "documentation": "

The data schema for the ML model being created.

" + "documentation": "

The data schema for the machine learning model being created.

" }, "LabelsInputConfiguration": { "shape": "LabelsInputConfiguration", - "documentation": "

The input configuration for the labels being used for the ML model that's being created.

" + "documentation": "

The input configuration for the labels being used for the machine learning model that's being created.

" }, "ClientToken": { "shape": "IdempotenceToken", @@ -1638,23 +1907,23 @@ }, "TrainingDataStartTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that should be used to begin the subset of training data for the machine learning model.

" }, "TrainingDataEndTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that should be used to end the subset of training data for the machine learning model.

" }, "EvaluationDataStartTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the machine learning model.

" }, "EvaluationDataEndTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the machine learning model.

" }, "RoleArn": { "shape": "IamRoleArn", - "documentation": "

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model.

" + "documentation": "

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model.

" }, "DataPreProcessingConfiguration": { "shape": "DataPreProcessingConfiguration", @@ -1666,7 +1935,7 @@ }, "Tags": { "shape": "TagList", - "documentation": "

Any tags associated with the ML model being created.

" + "documentation": "

Any tags associated with the machine learning model being created.

" }, "OffCondition": { "shape": "OffCondition", @@ -1687,6 +1956,59 @@ } } }, + "CreateRetrainingSchedulerRequest": { + "type": "structure", + "required": [ + "ModelName", + "RetrainingFrequency", + "LookbackWindow", + "ClientToken" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model to add the retraining scheduler to.

" + }, + "RetrainingStartDate": { + "shape": "Timestamp", + "documentation": "

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

" + }, + "RetrainingFrequency": { + "shape": "RetrainingFrequency", + "documentation": "

This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

" + }, + "LookbackWindow": { + "shape": "LookbackWindow", + "documentation": "

The number of past days of data that will be used for retraining.

" + }, + "PromoteMode": { + "shape": "ModelPromoteMode", + "documentation": "

Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.

" + }, + "ClientToken": { + "shape": "IdempotenceToken", + "documentation": "

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

", + "idempotencyToken": true + } + } + }, + "CreateRetrainingSchedulerResponse": { + "type": "structure", + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model that you added the retraining scheduler to.

" + }, + "ModelArn": { + "shape": "ModelArn", + "documentation": "

The ARN of the model that you added the retraining scheduler to.

" + }, + "Status": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

The status of the retraining scheduler.

" + } + } + }, "DataDelayOffsetInMinutes": { "type": "long", "max": 60, @@ -1804,7 +2126,7 @@ "members": { "InlineDataSchema": { "shape": "InlineDataSchema", - "documentation": "

", + "documentation": "

The data schema used within the given dataset.

", "jsonvalue": true } }, @@ -1908,7 +2230,7 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model to be deleted.

" + "documentation": "

The name of the machine learning model to be deleted.

" } } }, @@ -1924,6 +2246,18 @@ } } }, + "DeleteRetrainingSchedulerRequest": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model whose retraining scheduler you want to delete.

" + } + } + }, "DescribeDataIngestionJobRequest": { "type": "structure", "required": [ @@ -2087,11 +2421,11 @@ "members": { "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model of the inference scheduler being described.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model of the inference scheduler being described.

" }, "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model of the inference scheduler being described.

" + "documentation": "

The name of the machine learning model of the inference scheduler being described.

" }, "InferenceSchedulerName": { "shape": "InferenceSchedulerName", @@ -2250,7 +2584,7 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model to be described.

" + "documentation": "

The name of the machine learning model to be described.

" } } }, @@ -2259,19 +2593,19 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model being described.

" + "documentation": "

The name of the machine learning model being described.

" }, "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model being described.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model being described.

" }, "DatasetName": { "shape": "DatasetName", - "documentation": "

The name of the dataset being used by the ML being described.

" + "documentation": "

The name of the dataset being used by the machine learning being described.

" }, "DatasetArn": { "shape": "DatasetArn", - "documentation": "

The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.

" + "documentation": "

The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.

" }, "Schema": { "shape": "InlineDataSchema", @@ -2284,23 +2618,23 @@ }, "TrainingDataStartTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.

" }, "TrainingDataEndTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that was used to end the subset of training data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.

" }, "EvaluationDataStartTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.

" }, "EvaluationDataEndTime": { "shape": "Timestamp", - "documentation": "

Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model.

" + "documentation": "

Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.

" }, "RoleArn": { "shape": "IamRoleArn", - "documentation": "

The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML model being described.

" + "documentation": "

The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.

" }, "DataPreProcessingConfiguration": { "shape": "DataPreProcessingConfiguration", @@ -2312,15 +2646,15 @@ }, "TrainingExecutionStartTime": { "shape": "Timestamp", - "documentation": "

Indicates the time at which the training of the ML model began.

" + "documentation": "

Indicates the time at which the training of the machine learning model began.

" }, "TrainingExecutionEndTime": { "shape": "Timestamp", - "documentation": "

Indicates the time at which the training of the ML model was completed.

" + "documentation": "

Indicates the time at which the training of the machine learning model was completed.

" }, "FailedReason": { "shape": "BoundedLengthString", - "documentation": "

If the training of the ML model failed, this indicates the reason for that failure.

" + "documentation": "

If the training of the machine learning model failed, this indicates the reason for that failure.

" }, "ModelMetrics": { "shape": "ModelMetrics", @@ -2329,11 +2663,11 @@ }, "LastUpdatedTime": { "shape": "Timestamp", - "documentation": "

Indicates the last time the ML model was updated. The type of update is not specified.

" + "documentation": "

Indicates the last time the machine learning model was updated. The type of update is not specified.

" }, "CreatedAt": { "shape": "Timestamp", - "documentation": "

Indicates the time and date at which the ML model was created.

" + "documentation": "

Indicates the time and date at which the machine learning model was created.

" }, "ServerSideKmsKeyId": { "shape": "KmsKeyArn", @@ -2378,6 +2712,47 @@ "PreviousModelVersionActivatedAt": { "shape": "Timestamp", "documentation": "

The date and time when the previous active model version was activated.

" + }, + "PriorModelMetrics": { + "shape": "ModelMetrics", + "documentation": "

If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.

", + "jsonvalue": true + }, + "LatestScheduledRetrainingFailedReason": { + "shape": "BoundedLengthString", + "documentation": "

If the model version was generated by retraining and the training failed, this indicates the reason for that failure.

" + }, + "LatestScheduledRetrainingStatus": { + "shape": "ModelVersionStatus", + "documentation": "

Indicates the status of the most recent scheduled retraining run.

" + }, + "LatestScheduledRetrainingModelVersion": { + "shape": "ModelVersion", + "documentation": "

Indicates the most recent model version that was generated by retraining.

" + }, + "LatestScheduledRetrainingStartTime": { + "shape": "Timestamp", + "documentation": "

Indicates the start time of the most recent scheduled retraining run.

" + }, + "LatestScheduledRetrainingAvailableDataInDays": { + "shape": "Integer", + "documentation": "

Indicates the number of days of data used in the most recent scheduled retraining run.

" + }, + "NextScheduledRetrainingStartDate": { + "shape": "Timestamp", + "documentation": "

Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.

" + }, + "AccumulatedInferenceDataStartTime": { + "shape": "Timestamp", + "documentation": "

Indicates the start time of the inference data that has been accumulated.

" + }, + "AccumulatedInferenceDataEndTime": { + "shape": "Timestamp", + "documentation": "

Indicates the end time of the inference data that has been accumulated.

" + }, + "RetrainingSchedulerStatus": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

Indicates the status of the retraining scheduler.

" } } }, @@ -2510,6 +2885,22 @@ "ImportedDataSizeInBytes": { "shape": "DataSizeInBytes", "documentation": "

The size in bytes of the imported data. This field appears if the model version was imported.

" + }, + "PriorModelMetrics": { + "shape": "ModelMetrics", + "documentation": "

If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.

" + }, + "RetrainingAvailableDataInDays": { + "shape": "Integer", + "documentation": "

Indicates the number of days of data used in the most recent scheduled retraining run.

" + }, + "AutoPromotionResult": { + "shape": "AutoPromotionResult", + "documentation": "

Indicates whether the model version was promoted to be the active version after retraining or if there was an error with or cancellation of the retraining.

" + }, + "AutoPromotionResultReason": { + "shape": "AutoPromotionResultReason", + "documentation": "

Indicates the reason for the AutoPromotionResult. For example, a model might not be promoted if its performance was worse than the active version, if there was an error during training, or if the retraining scheduler was using MANUAL promote mode. The model will be promoted in MANAGED promote mode if the performance is better than the previous model.

" } } }, @@ -2546,6 +2937,59 @@ } } }, + "DescribeRetrainingSchedulerRequest": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model that the retraining scheduler is attached to.

" + } + } + }, + "DescribeRetrainingSchedulerResponse": { + "type": "structure", + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model that the retraining scheduler is attached to.

" + }, + "ModelArn": { + "shape": "ModelArn", + "documentation": "

The ARN of the model that the retraining scheduler is attached to.

" + }, + "RetrainingStartDate": { + "shape": "Timestamp", + "documentation": "

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

" + }, + "RetrainingFrequency": { + "shape": "RetrainingFrequency", + "documentation": "

The frequency at which the model retraining is set. This follows the ISO 8601 guidelines.

" + }, + "LookbackWindow": { + "shape": "LookbackWindow", + "documentation": "

The number of past days of data used for retraining.

" + }, + "Status": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

The status of the retraining scheduler.

" + }, + "PromoteMode": { + "shape": "ModelPromoteMode", + "documentation": "

Indicates how the service uses new models. In MANAGED mode, new models are used for inference if they have better performance than the current model. In MANUAL mode, the new models are not used until they are manually activated.

" + }, + "CreatedAt": { + "shape": "Timestamp", + "documentation": "

Indicates the time and date at which the retraining scheduler was created.

" + }, + "UpdatedAt": { + "shape": "Timestamp", + "documentation": "

Indicates the time and date at which the retraining scheduler was updated.

" + } + } + }, "DuplicateTimestamps": { "type": "structure", "required": [ @@ -2692,6 +3136,10 @@ "Tags": { "shape": "TagList", "documentation": "

The tags associated with the machine learning model to be created.

" + }, + "InferenceDataImportStrategy": { + "shape": "InferenceDataImportStrategy", + "documentation": "

Indicates how to import the accumulated inference data when a model version is imported. The possible values are as follows:

" } } }, @@ -2720,6 +3168,14 @@ } } }, + "InferenceDataImportStrategy": { + "type": "string", + "enum": [ + "NO_IMPORT", + "ADD_WHEN_EMPTY", + "OVERWRITE" + ] + }, "InferenceEventSummaries": { "type": "list", "member": { @@ -2775,11 +3231,11 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model being used for the inference execution.

" + "documentation": "

The name of the machine learning model being used for the inference execution.

" }, "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model used for the inference execution.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model used for the inference execution.

" }, "InferenceSchedulerName": { "shape": "InferenceSchedulerName", @@ -2811,7 +3267,7 @@ }, "CustomerResultObject": { "shape": "S3Object", - "documentation": "

" + "documentation": "

The S3 object that the inference execution results were uploaded to.

" }, "Status": { "shape": "InferenceExecutionStatus", @@ -2820,6 +3276,14 @@ "FailedReason": { "shape": "BoundedLengthString", "documentation": "

Specifies the reason for failure when an inference execution has failed.

" + }, + "ModelVersion": { + "shape": "ModelVersion", + "documentation": "

The model version used for the inference execution.

" + }, + "ModelVersionArn": { + "shape": "ModelVersionArn", + "documentation": "

The Amazon Resource Number (ARN) of the model version used for the inference execution.

" } }, "documentation": "

Contains information about the specific inference execution, including input and output data configuration, inference scheduling information, status, and so on.

" @@ -2945,11 +3409,11 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model used for the inference scheduler.

" + "documentation": "

The name of the machine learning model used for the inference scheduler.

" }, "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model used by the inference scheduler.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model used by the inference scheduler.

" }, "InferenceSchedulerName": { "shape": "InferenceSchedulerName", @@ -3432,7 +3896,7 @@ }, "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model used by the inference scheduler to be listed.

" + "documentation": "

The name of the machine learning model used by the inference scheduler to be listed.

" }, "Status": { "shape": "InferenceSchedulerStatus", @@ -3594,23 +4058,23 @@ "members": { "NextToken": { "shape": "NextToken", - "documentation": "

An opaque pagination token indicating where to continue the listing of ML models.

" + "documentation": "

An opaque pagination token indicating where to continue the listing of machine learning models.

" }, "MaxResults": { "shape": "MaxResults", - "documentation": "

Specifies the maximum number of ML models to list.

" + "documentation": "

Specifies the maximum number of machine learning models to list.

" }, "Status": { "shape": "ModelStatus", - "documentation": "

The status of the ML model.

" + "documentation": "

The status of the machine learning model.

" }, "ModelNameBeginsWith": { "shape": "ModelName", - "documentation": "

The beginning of the name of the ML models being listed.

" + "documentation": "

The beginning of the name of the machine learning models being listed.

" }, "DatasetNameBeginsWith": { "shape": "DatasetName", - "documentation": "

The beginning of the name of the dataset of the ML models to be listed.

" + "documentation": "

The beginning of the name of the dataset of the machine learning models to be listed.

" } } }, @@ -3619,7 +4083,7 @@ "members": { "NextToken": { "shape": "NextToken", - "documentation": "

An opaque pagination token indicating where to continue the listing of ML models.

" + "documentation": "

An opaque pagination token indicating where to continue the listing of machine learning models.

" }, "ModelSummaries": { "shape": "ModelSummaries", @@ -3634,6 +4098,40 @@ }, "min": 0 }, + "ListRetrainingSchedulersRequest": { + "type": "structure", + "members": { + "ModelNameBeginsWith": { + "shape": "ModelName", + "documentation": "

Specify this field to only list retraining schedulers whose machine learning models begin with the value you specify.

" + }, + "Status": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

Specify this field to only list retraining schedulers whose status matches the value you specify.

" + }, + "NextToken": { + "shape": "NextToken", + "documentation": "

If the number of results exceeds the maximum, a pagination token is returned. Use the token in the request to show the next page of retraining schedulers.

" + }, + "MaxResults": { + "shape": "MaxResults", + "documentation": "

Specifies the maximum number of retraining schedulers to list.

" + } + } + }, + "ListRetrainingSchedulersResponse": { + "type": "structure", + "members": { + "RetrainingSchedulerSummaries": { + "shape": "RetrainingSchedulerSummaries", + "documentation": "

Provides information on the specified retraining scheduler, including the model name, model ARN, status, and start date.

" + }, + "NextToken": { + "shape": "NextToken", + "documentation": "

If the number of results exceeds the maximum, this pagination token is returned. Use this token in the request to show the next page of retraining schedulers.

" + } + } + }, "ListSensorStatisticsRequest": { "type": "structure", "required": [ @@ -3692,6 +4190,10 @@ } } }, + "LookbackWindow": { + "type": "string", + "pattern": "^P180D$|^P360D$|^P540D$|^P720D$" + }, "MaxResults": { "type": "integer", "max": 500, @@ -3745,6 +4247,13 @@ "min": 1, "pattern": "^[0-9a-zA-Z_-]{1,200}$" }, + "ModelPromoteMode": { + "type": "string", + "enum": [ + "MANAGED", + "MANUAL" + ] + }, "ModelStatus": { "type": "string", "enum": [ @@ -3765,15 +4274,15 @@ "members": { "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model.

" + "documentation": "

The name of the machine learning model.

" }, "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model.

" }, "DatasetName": { "shape": "DatasetName", - "documentation": "

The name of the dataset being used for the ML model.

" + "documentation": "

The name of the dataset being used for the machine learning model.

" }, "DatasetArn": { "shape": "DatasetArn", @@ -3781,7 +4290,7 @@ }, "Status": { "shape": "ModelStatus", - "documentation": "

Indicates the status of the ML model.

" + "documentation": "

Indicates the status of the machine learning model.

" }, "CreatedAt": { "shape": "Timestamp", @@ -3794,9 +4303,29 @@ "ActiveModelVersionArn": { "shape": "ModelVersionArn", "documentation": "

The Amazon Resource Name (ARN) of the model version that is set as active. The active model version is the model version that the inference scheduler uses to run an inference execution.

" + }, + "LatestScheduledRetrainingStatus": { + "shape": "ModelVersionStatus", + "documentation": "

Indicates the status of the most recent scheduled retraining run.

" + }, + "LatestScheduledRetrainingModelVersion": { + "shape": "ModelVersion", + "documentation": "

Indicates the most recent model version that was generated by retraining.

" + }, + "LatestScheduledRetrainingStartTime": { + "shape": "Timestamp", + "documentation": "

Indicates the start time of the most recent scheduled retraining run.

" + }, + "NextScheduledRetrainingStartDate": { + "shape": "Timestamp", + "documentation": "

Indicates the date that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.

" + }, + "RetrainingSchedulerStatus": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

Indicates the status of the retraining scheduler.

" } }, - "documentation": "

Provides information about the specified ML model, including dataset and model names and ARNs, as well as status.

" + "documentation": "

Provides information about the specified machine learning model, including dataset and model names and ARNs, as well as status.

" }, "ModelVersion": { "type": "long", @@ -3977,6 +4506,57 @@ "min": 20, "pattern": "arn:aws(-[^:]+)?:lookoutequipment:[a-zA-Z0-9\\-]*:[0-9]{12}:.+" }, + "RetrainingFrequency": { + "type": "string", + "max": 10, + "min": 1, + "pattern": "^P(\\dY)?(\\d{1,2}M)?(\\d{1,3}D)?$" + }, + "RetrainingSchedulerStatus": { + "type": "string", + "enum": [ + "PENDING", + "RUNNING", + "STOPPING", + "STOPPED" + ] + }, + "RetrainingSchedulerSummaries": { + "type": "list", + "member": { + "shape": "RetrainingSchedulerSummary" + } + }, + "RetrainingSchedulerSummary": { + "type": "structure", + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model that the retraining scheduler is attached to.

" + }, + "ModelArn": { + "shape": "ModelArn", + "documentation": "

The ARN of the model that the retraining scheduler is attached to.

" + }, + "Status": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

The status of the retraining scheduler.

" + }, + "RetrainingStartDate": { + "shape": "Timestamp", + "documentation": "

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

" + }, + "RetrainingFrequency": { + "shape": "RetrainingFrequency", + "documentation": "

The frequency at which the model retraining is set. This follows the ISO 8601 guidelines.

" + }, + "LookbackWindow": { + "shape": "LookbackWindow", + "documentation": "

The number of past days of data used for retraining.

" + } + }, + "documentation": "

Provides information about the specified retraining scheduler, including model name, status, start date, frequency, and lookback window.

" + }, "S3Bucket": { "type": "string", "max": 63, @@ -4154,11 +4734,11 @@ "members": { "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model being used by the inference scheduler.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model being used by the inference scheduler.

" }, "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model being used by the inference scheduler.

" + "documentation": "

The name of the machine learning model being used by the inference scheduler.

" }, "InferenceSchedulerName": { "shape": "InferenceSchedulerName", @@ -4174,6 +4754,35 @@ } } }, + "StartRetrainingSchedulerRequest": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model whose retraining scheduler you want to start.

" + } + } + }, + "StartRetrainingSchedulerResponse": { + "type": "structure", + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model whose retraining scheduler is being started.

" + }, + "ModelArn": { + "shape": "ModelArn", + "documentation": "

The ARN of the model whose retraining scheduler is being started.

" + }, + "Status": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

The status of the retraining scheduler.

" + } + } + }, "StatisticalIssueStatus": { "type": "string", "enum": [ @@ -4198,11 +4807,11 @@ "members": { "ModelArn": { "shape": "ModelArn", - "documentation": "

The Amazon Resource Name (ARN) of the ML model used by the inference scheduler being stopped.

" + "documentation": "

The Amazon Resource Name (ARN) of the machine learning model used by the inference scheduler being stopped.

" }, "ModelName": { "shape": "ModelName", - "documentation": "

The name of the ML model used by the inference scheduler being stopped.

" + "documentation": "

The name of the machine learning model used by the inference scheduler being stopped.

" }, "InferenceSchedulerName": { "shape": "InferenceSchedulerName", @@ -4218,6 +4827,35 @@ } } }, + "StopRetrainingSchedulerRequest": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model whose retraining scheduler you want to stop.

" + } + } + }, + "StopRetrainingSchedulerResponse": { + "type": "structure", + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model whose retraining scheduler is being stopped.

" + }, + "ModelArn": { + "shape": "ModelArn", + "documentation": "

The ARN of the model whose retraining scheduler is being stopped.

" + }, + "Status": { + "shape": "RetrainingSchedulerStatus", + "documentation": "

The status of the retraining scheduler.

" + } + } + }, "Tag": { "type": "structure", "required": [ @@ -4435,6 +5073,53 @@ "documentation": "

Updates the code indicating the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

" } } + }, + "UpdateModelRequest": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model to update.

" + }, + "LabelsInputConfiguration": { + "shape": "LabelsInputConfiguration" + }, + "RoleArn": { + "shape": "IamRoleArn", + "documentation": "

The ARN of the model to update.

" + } + } + }, + "UpdateRetrainingSchedulerRequest": { + "type": "structure", + "required": [ + "ModelName" + ], + "members": { + "ModelName": { + "shape": "ModelName", + "documentation": "

The name of the model whose retraining scheduler you want to update.

" + }, + "RetrainingStartDate": { + "shape": "Timestamp", + "documentation": "

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

" + }, + "RetrainingFrequency": { + "shape": "RetrainingFrequency", + "documentation": "

This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

" + }, + "LookbackWindow": { + "shape": "LookbackWindow", + "documentation": "

The number of past days of data that will be used for retraining.

" + }, + "PromoteMode": { + "shape": "ModelPromoteMode", + "documentation": "

Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.

" + } + } } }, "documentation": "

Amazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance.

" diff --git a/apis/lookoutequipment-2020-12-15.paginators.json b/apis/lookoutequipment-2020-12-15.paginators.json index 18e13f7d3a..299bf028eb 100644 --- a/apis/lookoutequipment-2020-12-15.paginators.json +++ b/apis/lookoutequipment-2020-12-15.paginators.json @@ -45,6 +45,11 @@ "output_token": "NextToken", "limit_key": "MaxResults" }, + "ListRetrainingSchedulers": { + "input_token": "NextToken", + "output_token": "NextToken", + "limit_key": "MaxResults" + }, "ListSensorStatistics": { "input_token": "NextToken", "output_token": "NextToken", diff --git a/clients/appstream.d.ts b/clients/appstream.d.ts index bca17150c7..deea78c1fc 100644 --- a/clients/appstream.d.ts +++ b/clients/appstream.d.ts @@ -986,7 +986,11 @@ declare namespace AppStream { /** * The desired number of streaming instances. */ - DesiredInstances: Integer; + DesiredInstances?: Integer; + /** + * The desired number of user sessions for a multi-session fleet. This is not allowed for single-session fleets. When you create a fleet, you must set either the DesiredSessions or DesiredInstances attribute, based on the type of fleet you create. You can’t define both attributes or leave both attributes blank. + */ + DesiredSessions?: Integer; } export interface ComputeCapacityStatus { /** @@ -1005,6 +1009,22 @@ declare namespace AppStream { * The number of currently available instances that can be used to stream sessions. */ Available?: Integer; + /** + * The total number of sessions slots that are either running or pending. This represents the total number of concurrent streaming sessions your fleet can support in a steady state. DesiredUserSessionCapacity = ActualUserSessionCapacity + PendingUserSessionCapacity This only applies to multi-session fleets. + */ + DesiredUserSessions?: Integer; + /** + * The number of idle session slots currently available for user sessions. AvailableUserSessionCapacity = ActualUserSessionCapacity - ActiveUserSessions This only applies to multi-session fleets. + */ + AvailableUserSessions?: Integer; + /** + * The number of user sessions currently being used for streaming sessions. This only applies to multi-session fleets. + */ + ActiveUserSessions?: Integer; + /** + * The total number of session slots that are available for streaming or are currently streaming. ActualUserSessionCapacity = AvailableUserSessionCapacity + ActiveUserSessions This only applies to multi-session fleets. + */ + ActualUserSessions?: Integer; } export interface CopyImageRequest { /** @@ -1266,7 +1286,7 @@ declare namespace AppStream { */ VpcConfig?: VpcConfig; /** - * The maximum amount of time that a streaming session can remain active, in seconds. If users are still connected to a streaming instance five minutes before this limit is reached, they are prompted to save any open documents before being disconnected. After this time elapses, the instance is terminated and replaced by a new instance. Specify a value between 600 and 360000. + * The maximum amount of time that a streaming session can remain active, in seconds. If users are still connected to a streaming instance five minutes before this limit is reached, they are prompted to save any open documents before being disconnected. After this time elapses, the instance is terminated and replaced by a new instance. Specify a value between 600 and 432000. */ MaxUserDurationInSeconds?: Integer; /** @@ -1321,6 +1341,10 @@ declare namespace AppStream { * The S3 location of the session scripts configuration zip file. This only applies to Elastic fleets. */ SessionScriptS3Location?: S3Location; + /** + * The maximum number of user sessions on an instance. This only applies to multi-session fleets. + */ + MaxSessionsPerInstance?: Integer; } export interface CreateFleetResult { /** @@ -1974,11 +1998,11 @@ declare namespace AppStream { /** * The name of the stack. This value is case-sensitive. */ - StackName: String; + StackName: Name; /** * The name of the fleet. This value is case-sensitive. */ - FleetName: String; + FleetName: Name; /** * The user identifier (ID). If you specify a user ID, you must also specify the authentication type. */ @@ -1995,6 +2019,10 @@ declare namespace AppStream { * The authentication method. Specify API for a user authenticated using a streaming URL or SAML for a SAML federated user. The default is to authenticate users using a streaming URL. */ AuthenticationType?: AuthenticationType; + /** + * The identifier for the instance hosting the session. + */ + InstanceId?: String; } export interface DescribeSessionsResult { /** @@ -2385,8 +2413,12 @@ declare namespace AppStream { * The S3 location of the session scripts configuration zip file. This only applies to Elastic fleets. */ SessionScriptS3Location?: S3Location; + /** + * The maximum number of user sessions on an instance. This only applies to multi-session fleets. + */ + MaxSessionsPerInstance?: Integer; } - export type FleetAttribute = "VPC_CONFIGURATION"|"VPC_CONFIGURATION_SECURITY_GROUP_IDS"|"DOMAIN_JOIN_INFO"|"IAM_ROLE_ARN"|"USB_DEVICE_FILTER_STRINGS"|"SESSION_SCRIPT_S3_LOCATION"|string; + export type FleetAttribute = "VPC_CONFIGURATION"|"VPC_CONFIGURATION_SECURITY_GROUP_IDS"|"DOMAIN_JOIN_INFO"|"IAM_ROLE_ARN"|"USB_DEVICE_FILTER_STRINGS"|"SESSION_SCRIPT_S3_LOCATION"|"MAX_SESSIONS_PER_INSTANCE"|string; export type FleetAttributes = FleetAttribute[]; export interface FleetError { /** @@ -2794,6 +2826,10 @@ declare namespace AppStream { * The network details for the streaming session. */ NetworkAccessConfiguration?: NetworkAccessConfiguration; + /** + * The identifier for the instance hosting the session. + */ + InstanceId?: String; } export type SessionConnectionState = "CONNECTED"|"NOT_CONNECTED"|string; export type SessionList = Session[]; @@ -3151,7 +3187,7 @@ declare namespace AppStream { /** * A unique name for the fleet. */ - Name?: String; + Name?: Name; /** * The instance type to use when launching fleet instances. The following instance types are available: stream.standard.small stream.standard.medium stream.standard.large stream.standard.xlarge stream.standard.2xlarge stream.compute.large stream.compute.xlarge stream.compute.2xlarge stream.compute.4xlarge stream.compute.8xlarge stream.memory.large stream.memory.xlarge stream.memory.2xlarge stream.memory.4xlarge stream.memory.8xlarge stream.memory.z1d.large stream.memory.z1d.xlarge stream.memory.z1d.2xlarge stream.memory.z1d.3xlarge stream.memory.z1d.6xlarge stream.memory.z1d.12xlarge stream.graphics-design.large stream.graphics-design.xlarge stream.graphics-design.2xlarge stream.graphics-design.4xlarge stream.graphics-desktop.2xlarge stream.graphics.g4dn.xlarge stream.graphics.g4dn.2xlarge stream.graphics.g4dn.4xlarge stream.graphics.g4dn.8xlarge stream.graphics.g4dn.12xlarge stream.graphics.g4dn.16xlarge stream.graphics-pro.4xlarge stream.graphics-pro.8xlarge stream.graphics-pro.16xlarge The following instance types are available for Elastic fleets: stream.standard.small stream.standard.medium stream.standard.large stream.standard.xlarge stream.standard.2xlarge */ @@ -3224,6 +3260,10 @@ declare namespace AppStream { * The S3 location of the session scripts configuration zip file. This only applies to Elastic fleets. */ SessionScriptS3Location?: S3Location; + /** + * The maximum number of user sessions on an instance. This only applies to multi-session fleets. + */ + MaxSessionsPerInstance?: Integer; } export interface UpdateFleetResult { /** diff --git a/clients/cloudformation.d.ts b/clients/cloudformation.d.ts index d6ff436c1d..b71180529b 100644 --- a/clients/cloudformation.d.ts +++ b/clients/cloudformation.d.ts @@ -1091,7 +1091,7 @@ declare namespace CloudFormation { */ EnableTerminationProtection?: EnableTerminationProtection; /** - * This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute. + * When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain. Default: false */ RetainExceptOnCreate?: RetainExceptOnCreate; } @@ -1730,7 +1730,7 @@ declare namespace CloudFormation { } export interface DescribeStacksInput { /** - * If you don't pass a parameter to StackName, the API returns a response that describes all resources in the account. This requires ListStacks and DescribeStacks permissions. The IAM policy below can be added to IAM policies when you want to limit resource-level permissions and avoid returning a response when no parameter is sent in the request: { "Version": "2012-10-17", "Statement": [{ "Effect": "Deny", "Action": "cloudformation:DescribeStacks", "NotResource": "arn:aws:cloudformation:*:*:stack/**" }] } The name or the unique stack ID that's associated with the stack, which aren't always interchangeable: Running stacks: You can specify either the stack's name or its unique stack ID. Deleted stacks: You must specify the unique stack ID. Default: There is no default value. + * If you don't pass a parameter to StackName, the API returns a response that describes all resources in the account, which can impact performance. This requires ListStacks and DescribeStacks permissions. Consider using the ListStacks API if you're not passing a parameter to StackName. The IAM policy below can be added to IAM policies when you want to limit resource-level permissions and avoid returning a response when no parameter is sent in the request: { "Version": "2012-10-17", "Statement": [{ "Effect": "Deny", "Action": "cloudformation:DescribeStacks", "NotResource": "arn:aws:cloudformation:*:*:stack/**" }] } The name or the unique stack ID that's associated with the stack, which aren't always interchangeable: Running stacks: You can specify either the stack's name or its unique stack ID. Deleted stacks: You must specify the unique stack ID. Default: There is no default value. */ StackName?: StackName; /** @@ -2011,7 +2011,7 @@ declare namespace CloudFormation { */ DisableRollback?: DisableRollback; /** - * This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute. + * When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain. Default: false */ RetainExceptOnCreate?: RetainExceptOnCreate; } @@ -3052,7 +3052,7 @@ declare namespace CloudFormation { */ ClientRequestToken?: ClientRequestToken; /** - * This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute. + * When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain. Default: false */ RetainExceptOnCreate?: RetainExceptOnCreate; } @@ -3246,7 +3246,7 @@ declare namespace CloudFormation { */ DriftInformation?: StackDriftInformation; /** - * This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute. + * When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain. Default: false */ RetainExceptOnCreate?: RetainExceptOnCreate; } @@ -4400,7 +4400,7 @@ declare namespace CloudFormation { */ ClientRequestToken?: ClientRequestToken; /** - * This deletion policy deletes newly created resources, but retains existing resources, when a stack operation is rolled back. This ensures new, empty, and unused resources are deleted, while critical resources and their data are retained. RetainExceptOnCreate can be specified for any resource that supports the DeletionPolicy attribute. + * When set to true, newly created resources are deleted when the operation rolls back. This includes newly created resources marked with a deletion policy of Retain. Default: false */ RetainExceptOnCreate?: RetainExceptOnCreate; } diff --git a/clients/entityresolution.d.ts b/clients/entityresolution.d.ts index d22ac854ab..e333d36c94 100644 --- a/clients/entityresolution.d.ts +++ b/clients/entityresolution.d.ts @@ -84,27 +84,27 @@ declare class EntityResolution extends Service { */ listMatchingJobs(callback?: (err: AWSError, data: EntityResolution.Types.ListMatchingJobsOutput) => void): Request; /** - * Returns a list of all the MatchingWorkflows that have been created for an AWS account. + * Returns a list of all the MatchingWorkflows that have been created for an Amazon Web Services account. */ listMatchingWorkflows(params: EntityResolution.Types.ListMatchingWorkflowsInput, callback?: (err: AWSError, data: EntityResolution.Types.ListMatchingWorkflowsOutput) => void): Request; /** - * Returns a list of all the MatchingWorkflows that have been created for an AWS account. + * Returns a list of all the MatchingWorkflows that have been created for an Amazon Web Services account. */ listMatchingWorkflows(callback?: (err: AWSError, data: EntityResolution.Types.ListMatchingWorkflowsOutput) => void): Request; /** - * Returns a list of all the SchemaMappings that have been created for an AWS account. + * Returns a list of all the SchemaMappings that have been created for an Amazon Web Services account. */ listSchemaMappings(params: EntityResolution.Types.ListSchemaMappingsInput, callback?: (err: AWSError, data: EntityResolution.Types.ListSchemaMappingsOutput) => void): Request; /** - * Returns a list of all the SchemaMappings that have been created for an AWS account. + * Returns a list of all the SchemaMappings that have been created for an Amazon Web Services account. */ listSchemaMappings(callback?: (err: AWSError, data: EntityResolution.Types.ListSchemaMappingsOutput) => void): Request; /** - * Displays the tags associated with an AWS Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. + * Displays the tags associated with an Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. */ listTagsForResource(params: EntityResolution.Types.ListTagsForResourceInput, callback?: (err: AWSError, data: EntityResolution.Types.ListTagsForResourceOutput) => void): Request; /** - * Displays the tags associated with an AWS Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. + * Displays the tags associated with an Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. */ listTagsForResource(callback?: (err: AWSError, data: EntityResolution.Types.ListTagsForResourceOutput) => void): Request; /** @@ -116,19 +116,19 @@ declare class EntityResolution extends Service { */ startMatchingJob(callback?: (err: AWSError, data: EntityResolution.Types.StartMatchingJobOutput) => void): Request; /** - * Assigns one or more tags (key-value pairs) to the specified AWS Entity Resolution resource. Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. Tags don't have any semantic meaning to AWS and are interpreted strictly as strings of characters. You can use the TagResource action with a resource that already has tags. If you specify a new tag key, this tag is appended to the list of tags associated with the resource. If you specify a tag key that is already associated with the resource, the new tag value that you specify replaces the previous value for that tag. + * Assigns one or more tags (key-value pairs) to the specified Entity Resolution resource. Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values. In Entity Resolution, SchemaMapping and MatchingWorkflow can be tagged. Tags don't have any semantic meaning to Amazon Web Services and are interpreted strictly as strings of characters. You can use the TagResource action with a resource that already has tags. If you specify a new tag key, this tag is appended to the list of tags associated with the resource. If you specify a tag key that is already associated with the resource, the new tag value that you specify replaces the previous value for that tag. */ tagResource(params: EntityResolution.Types.TagResourceInput, callback?: (err: AWSError, data: EntityResolution.Types.TagResourceOutput) => void): Request; /** - * Assigns one or more tags (key-value pairs) to the specified AWS Entity Resolution resource. Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. Tags don't have any semantic meaning to AWS and are interpreted strictly as strings of characters. You can use the TagResource action with a resource that already has tags. If you specify a new tag key, this tag is appended to the list of tags associated with the resource. If you specify a tag key that is already associated with the resource, the new tag value that you specify replaces the previous value for that tag. + * Assigns one or more tags (key-value pairs) to the specified Entity Resolution resource. Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values. In Entity Resolution, SchemaMapping and MatchingWorkflow can be tagged. Tags don't have any semantic meaning to Amazon Web Services and are interpreted strictly as strings of characters. You can use the TagResource action with a resource that already has tags. If you specify a new tag key, this tag is appended to the list of tags associated with the resource. If you specify a tag key that is already associated with the resource, the new tag value that you specify replaces the previous value for that tag. */ tagResource(callback?: (err: AWSError, data: EntityResolution.Types.TagResourceOutput) => void): Request; /** - * Removes one or more tags from the specified AWS Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. + * Removes one or more tags from the specified Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. */ untagResource(params: EntityResolution.Types.UntagResourceInput, callback?: (err: AWSError, data: EntityResolution.Types.UntagResourceOutput) => void): Request; /** - * Removes one or more tags from the specified AWS Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. + * Removes one or more tags from the specified Entity Resolution resource. In Entity Resolution, SchemaMapping, and MatchingWorkflow can be tagged. */ untagResource(callback?: (err: AWSError, data: EntityResolution.Types.UntagResourceOutput) => void): Request; /** @@ -162,11 +162,11 @@ declare namespace EntityResolution { */ outputSourceConfig: OutputSourceConfig; /** - * An object which defines the resolutionType and the ruleBasedProperties + * An object which defines the resolutionType and the ruleBasedProperties. */ resolutionTechniques: ResolutionTechniques; /** - * The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. + * The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. */ roleArn: String; /** @@ -196,11 +196,11 @@ declare namespace EntityResolution { */ outputSourceConfig: OutputSourceConfig; /** - * An object which defines the resolutionType and the ruleBasedProperties + * An object which defines the resolutionType and the ruleBasedProperties. */ resolutionTechniques: ResolutionTechniques; /** - * The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. + * The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. */ roleArn: String; /** @@ -220,7 +220,7 @@ declare namespace EntityResolution { /** * A list of MappedInputFields. Each MappedInputField corresponds to a column the source data table, and contains column name plus additional information that Entity Resolution uses for matching. */ - mappedInputFields?: SchemaInputAttributes; + mappedInputFields: SchemaInputAttributes; /** * The name of the schema. There cannot be multiple SchemaMappings with the same name. */ @@ -329,7 +329,7 @@ declare namespace EntityResolution { */ startTime: Timestamp; /** - * The current status of the job. Either running, succeeded, queued, or failed. + * The current status of the job. */ status: JobStatus; } @@ -361,11 +361,11 @@ declare namespace EntityResolution { */ outputSourceConfig: OutputSourceConfig; /** - * An object which defines the resolutionType and the ruleBasedProperties + * An object which defines the resolutionType and the ruleBasedProperties. */ resolutionTechniques: ResolutionTechniques; /** - * The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to access resources on your behalf. + * The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to access resources on your behalf. */ roleArn: String; /** @@ -457,7 +457,7 @@ declare namespace EntityResolution { */ matchIDs?: Integer; /** - * The total number of records that did not get processed, + * The total number of records that did not get processed. */ recordsNotProcessed?: Integer; /** @@ -480,7 +480,7 @@ declare namespace EntityResolution { */ startTime: Timestamp; /** - * The current status of the job. Either running, succeeded, queued, or failed. + * The current status of the job. */ status: JobStatus; } @@ -611,19 +611,18 @@ declare namespace EntityResolution { /** * The S3 path to which Entity Resolution will write the output table. */ - outputS3Path: OutputSourceOutputS3PathString; + outputS3Path: S3Path; } export type OutputSourceConfig = OutputSource[]; export type OutputSourceOutputList = OutputAttribute[]; - export type OutputSourceOutputS3PathString = string; export type RecordAttributeMap = {[key: string]: RecordAttributeMapValueString}; export type RecordAttributeMapKeyString = string; export type RecordAttributeMapValueString = string; export interface ResolutionTechniques { /** - * There are two types of matching, RULE_MATCHING and ML_MATCHING + * The type of matching. There are two types of matching: RULE_MATCHING and ML_MATCHING. */ - resolutionType?: ResolutionType; + resolutionType: ResolutionType; /** * An object which defines the list of matching rules to run and has a field Rules, which is a list of rule objects. */ @@ -642,7 +641,7 @@ declare namespace EntityResolution { } export interface RuleBasedProperties { /** - * You can either choose ONE_TO_ONE or MANY_TO_MANY as the AttributeMatchingModel. When choosing MANY_TO_MANY, the system can match attribute across the sub-types of an attribute type. For example, if the value of the Email field of Profile A and the value of BusinessEmail field of Profile B matches, the two profiles are matched on the Email type. When choosing ONE_TO_ONE the system can only match if the sub-types are exact matches. For example, only when the value of the Email field of Profile A and the value of the Email field of Profile B matches, the two profiles are matched on the Email type. + * The comparison type. You can either choose ONE_TO_ONE or MANY_TO_MANY as the AttributeMatchingModel. When choosing MANY_TO_MANY, the system can match attributes across the sub-types of an attribute type. For example, if the value of the Email field of Profile A and the value of BusinessEmail field of Profile B matches, the two profiles are matched on the Email type. When choosing ONE_TO_ONE ,the system can only match if the sub-types are exact matches. For example, only when the value of the Email field of Profile A and the value of the Email field of Profile B matches, the two profiles are matched on the Email type. */ attributeMatchingModel: AttributeMatchingModel; /** @@ -653,6 +652,7 @@ declare namespace EntityResolution { export type RuleBasedPropertiesRulesList = Rule[]; export type RuleMatchingKeysList = AttributeName[]; export type RuleRuleNameString = string; + export type S3Path = string; export type SchemaAttributeType = "NAME"|"NAME_FIRST"|"NAME_MIDDLE"|"NAME_LAST"|"ADDRESS"|"ADDRESS_STREET1"|"ADDRESS_STREET2"|"ADDRESS_STREET3"|"ADDRESS_CITY"|"ADDRESS_STATE"|"ADDRESS_COUNTRY"|"ADDRESS_POSTALCODE"|"PHONE"|"PHONE_NUMBER"|"PHONE_COUNTRYCODE"|"EMAIL_ADDRESS"|"UNIQUE_ID"|"DATE"|"STRING"|string; export interface SchemaInputAttribute { /** @@ -664,7 +664,7 @@ declare namespace EntityResolution { */ groupName?: AttributeName; /** - * A key that allows grouping of multiple input attributes into a unified matching group. For example, let's consider a scenario where the source table contains various addresses, such as business_address and shipping_address. By assigning the MatchKey Address' to both attributes, Entity Resolution will match records across these fields to create a consolidated matching group. If no MatchKey is specified for a column, it won't be utilized for matching purposes but will still be included in the output table. + * A key that allows grouping of multiple input attributes into a unified matching group. For example, let's consider a scenario where the source table contains various addresses, such as business_address and shipping_address. By assigning the MatchKey Address to both attributes, Entity Resolution will match records across these fields to create a consolidated matching group. If no MatchKey is specified for a column, it won't be utilized for matching purposes but will still be included in the output table. */ matchKey?: AttributeName; /** @@ -753,11 +753,11 @@ declare namespace EntityResolution { */ outputSourceConfig: OutputSourceConfig; /** - * An object which defines the resolutionType and the ruleBasedProperties + * An object which defines the resolutionType and the ruleBasedProperties. */ resolutionTechniques: ResolutionTechniques; /** - * The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. + * The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. */ roleArn: String; /** @@ -787,7 +787,7 @@ declare namespace EntityResolution { */ resolutionTechniques: ResolutionTechniques; /** - * The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. + * The Amazon Resource Name (ARN) of the IAM role. Entity Resolution assumes this role to create resources on your behalf as part of workflow execution. */ roleArn: String; /** diff --git a/clients/lookoutequipment.d.ts b/clients/lookoutequipment.d.ts index cfe1784fcb..8fc1d59c2e 100644 --- a/clients/lookoutequipment.d.ts +++ b/clients/lookoutequipment.d.ts @@ -44,13 +44,21 @@ declare class LookoutEquipment extends Service { */ createLabelGroup(callback?: (err: AWSError, data: LookoutEquipment.Types.CreateLabelGroupResponse) => void): Request; /** - * Creates an ML model for data inference. A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred. Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy. + * Creates a machine learning model for data inference. A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred. Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy. */ createModel(params: LookoutEquipment.Types.CreateModelRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.CreateModelResponse) => void): Request; /** - * Creates an ML model for data inference. A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred. Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy. + * Creates a machine learning model for data inference. A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred. Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy. */ createModel(callback?: (err: AWSError, data: LookoutEquipment.Types.CreateModelResponse) => void): Request; + /** + * Creates a retraining scheduler on the specified model. + */ + createRetrainingScheduler(params: LookoutEquipment.Types.CreateRetrainingSchedulerRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.CreateRetrainingSchedulerResponse) => void): Request; + /** + * Creates a retraining scheduler on the specified model. + */ + createRetrainingScheduler(callback?: (err: AWSError, data: LookoutEquipment.Types.CreateRetrainingSchedulerResponse) => void): Request; /** * Deletes a dataset and associated artifacts. The operation will check to see if any inference scheduler or data ingestion job is currently using the dataset, and if there isn't, the dataset, its metadata, and any associated data stored in S3 will be deleted. This does not affect any models that used this dataset for training and evaluation, but does prevent it from being used in the future. */ @@ -60,11 +68,11 @@ declare class LookoutEquipment extends Service { */ deleteDataset(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** - * Deletes an inference scheduler that has been set up. Already processed output results are not affected. + * Deletes an inference scheduler that has been set up. Prior inference results will not be deleted. */ deleteInferenceScheduler(params: LookoutEquipment.Types.DeleteInferenceSchedulerRequest, callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** - * Deletes an inference scheduler that has been set up. Already processed output results are not affected. + * Deletes an inference scheduler that has been set up. Prior inference results will not be deleted. */ deleteInferenceScheduler(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** @@ -84,11 +92,11 @@ declare class LookoutEquipment extends Service { */ deleteLabelGroup(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** - * Deletes an ML model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up. + * Deletes a machine learning model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up. */ deleteModel(params: LookoutEquipment.Types.DeleteModelRequest, callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** - * Deletes an ML model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up. + * Deletes a machine learning model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up. */ deleteModel(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** @@ -99,6 +107,14 @@ declare class LookoutEquipment extends Service { * Deletes the resource policy attached to the resource. */ deleteResourcePolicy(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; + /** + * Deletes a retraining scheduler from a model. The retraining scheduler must be in the STOPPED status. + */ + deleteRetrainingScheduler(params: LookoutEquipment.Types.DeleteRetrainingSchedulerRequest, callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; + /** + * Deletes a retraining scheduler from a model. The retraining scheduler must be in the STOPPED status. + */ + deleteRetrainingScheduler(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; /** * Provides information on a specific data ingestion job such as creation time, dataset ARN, and status. */ @@ -140,11 +156,11 @@ declare class LookoutEquipment extends Service { */ describeLabelGroup(callback?: (err: AWSError, data: LookoutEquipment.Types.DescribeLabelGroupResponse) => void): Request; /** - * Provides a JSON containing the overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on. + * Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on. */ describeModel(params: LookoutEquipment.Types.DescribeModelRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.DescribeModelResponse) => void): Request; /** - * Provides a JSON containing the overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on. + * Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on. */ describeModel(callback?: (err: AWSError, data: LookoutEquipment.Types.DescribeModelResponse) => void): Request; /** @@ -163,6 +179,14 @@ declare class LookoutEquipment extends Service { * Provides the details of a resource policy attached to a resource. */ describeResourcePolicy(callback?: (err: AWSError, data: LookoutEquipment.Types.DescribeResourcePolicyResponse) => void): Request; + /** + * Provides a description of the retraining scheduler, including information such as the model name and retraining parameters. + */ + describeRetrainingScheduler(params: LookoutEquipment.Types.DescribeRetrainingSchedulerRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.DescribeRetrainingSchedulerResponse) => void): Request; + /** + * Provides a description of the retraining scheduler, including information such as the model name and retraining parameters. + */ + describeRetrainingScheduler(callback?: (err: AWSError, data: LookoutEquipment.Types.DescribeRetrainingSchedulerResponse) => void): Request; /** * Imports a dataset. */ @@ -251,6 +275,14 @@ declare class LookoutEquipment extends Service { * Generates a list of all models in the account, including model name and ARN, dataset, and status. */ listModels(callback?: (err: AWSError, data: LookoutEquipment.Types.ListModelsResponse) => void): Request; + /** + * Lists all retraining schedulers in your account, filtering by model name prefix and status. + */ + listRetrainingSchedulers(params: LookoutEquipment.Types.ListRetrainingSchedulersRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.ListRetrainingSchedulersResponse) => void): Request; + /** + * Lists all retraining schedulers in your account, filtering by model name prefix and status. + */ + listRetrainingSchedulers(callback?: (err: AWSError, data: LookoutEquipment.Types.ListRetrainingSchedulersResponse) => void): Request; /** * Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset. Can also be used to retreive Sensor Statistics for a previous ingestion job. */ @@ -291,6 +323,14 @@ declare class LookoutEquipment extends Service { * Starts an inference scheduler. */ startInferenceScheduler(callback?: (err: AWSError, data: LookoutEquipment.Types.StartInferenceSchedulerResponse) => void): Request; + /** + * Starts a retraining scheduler. + */ + startRetrainingScheduler(params: LookoutEquipment.Types.StartRetrainingSchedulerRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.StartRetrainingSchedulerResponse) => void): Request; + /** + * Starts a retraining scheduler. + */ + startRetrainingScheduler(callback?: (err: AWSError, data: LookoutEquipment.Types.StartRetrainingSchedulerResponse) => void): Request; /** * Stops an inference scheduler. */ @@ -299,6 +339,14 @@ declare class LookoutEquipment extends Service { * Stops an inference scheduler. */ stopInferenceScheduler(callback?: (err: AWSError, data: LookoutEquipment.Types.StopInferenceSchedulerResponse) => void): Request; + /** + * Stops a retraining scheduler. + */ + stopRetrainingScheduler(params: LookoutEquipment.Types.StopRetrainingSchedulerRequest, callback?: (err: AWSError, data: LookoutEquipment.Types.StopRetrainingSchedulerResponse) => void): Request; + /** + * Stops a retraining scheduler. + */ + stopRetrainingScheduler(callback?: (err: AWSError, data: LookoutEquipment.Types.StopRetrainingSchedulerResponse) => void): Request; /** * Associates a given tag to a resource in your account. A tag is a key-value pair which can be added to an Amazon Lookout for Equipment resource as metadata. Tags can be used for organizing your resources as well as helping you to search and filter by tag. Multiple tags can be added to a resource, either when you create it, or later. Up to 50 tags can be associated with each resource. */ @@ -339,9 +387,27 @@ declare class LookoutEquipment extends Service { * Updates the label group. */ updateLabelGroup(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; + /** + * Updates a model in the account. + */ + updateModel(params: LookoutEquipment.Types.UpdateModelRequest, callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; + /** + * Updates a model in the account. + */ + updateModel(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; + /** + * Updates a retraining scheduler. + */ + updateRetrainingScheduler(params: LookoutEquipment.Types.UpdateRetrainingSchedulerRequest, callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; + /** + * Updates a retraining scheduler. + */ + updateRetrainingScheduler(callback?: (err: AWSError, data: {}) => void): Request<{}, AWSError>; } declare namespace LookoutEquipment { export type AmazonResourceArn = string; + export type AutoPromotionResult = "MODEL_PROMOTED"|"MODEL_NOT_PROMOTED"|"RETRAINING_INTERNAL_ERROR"|"RETRAINING_CUSTOMER_ERROR"|"RETRAINING_CANCELLED"|string; + export type AutoPromotionResultReason = string; export type Boolean = boolean; export type BoundedLengthString = string; export interface CategoricalValues { @@ -405,7 +471,7 @@ declare namespace LookoutEquipment { } export interface CreateInferenceSchedulerRequest { /** - * The name of the previously trained ML model being used to create the inference scheduler. + * The name of the previously trained machine learning model being used to create the inference scheduler. */ ModelName: ModelName; /** @@ -529,19 +595,19 @@ declare namespace LookoutEquipment { } export interface CreateModelRequest { /** - * The name for the ML model to be created. + * The name for the machine learning model to be created. */ ModelName: ModelName; /** - * The name of the dataset for the ML model being created. + * The name of the dataset for the machine learning model being created. */ DatasetName: DatasetIdentifier; /** - * The data schema for the ML model being created. + * The data schema for the machine learning model being created. */ DatasetSchema?: DatasetSchema; /** - * The input configuration for the labels being used for the ML model that's being created. + * The input configuration for the labels being used for the machine learning model that's being created. */ LabelsInputConfiguration?: LabelsInputConfiguration; /** @@ -549,23 +615,23 @@ declare namespace LookoutEquipment { */ ClientToken: IdempotenceToken; /** - * Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model. + * Indicates the time reference in the dataset that should be used to begin the subset of training data for the machine learning model. */ TrainingDataStartTime?: Timestamp; /** - * Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model. + * Indicates the time reference in the dataset that should be used to end the subset of training data for the machine learning model. */ TrainingDataEndTime?: Timestamp; /** - * Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model. + * Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the machine learning model. */ EvaluationDataStartTime?: Timestamp; /** - * Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model. + * Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the machine learning model. */ EvaluationDataEndTime?: Timestamp; /** - * The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model. + * The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model. */ RoleArn?: IamRoleArn; /** @@ -577,7 +643,7 @@ declare namespace LookoutEquipment { */ ServerSideKmsKeyId?: NameOrArn; /** - * Any tags associated with the ML model being created. + * Any tags associated with the machine learning model being created. */ Tags?: TagList; /** @@ -595,6 +661,46 @@ declare namespace LookoutEquipment { */ Status?: ModelStatus; } + export interface CreateRetrainingSchedulerRequest { + /** + * The name of the model to add the retraining scheduler to. + */ + ModelName: ModelName; + /** + * The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day. + */ + RetrainingStartDate?: Timestamp; + /** + * This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid: P3M15D – Every 3 months and 15 days P2M – Every 2 months P150D – Every 150 days + */ + RetrainingFrequency: RetrainingFrequency; + /** + * The number of past days of data that will be used for retraining. + */ + LookbackWindow: LookbackWindow; + /** + * Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated. + */ + PromoteMode?: ModelPromoteMode; + /** + * A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. + */ + ClientToken: IdempotenceToken; + } + export interface CreateRetrainingSchedulerResponse { + /** + * The name of the model that you added the retraining scheduler to. + */ + ModelName?: ModelName; + /** + * The ARN of the model that you added the retraining scheduler to. + */ + ModelArn?: ModelArn; + /** + * The status of the retraining scheduler. + */ + Status?: RetrainingSchedulerStatus; + } export type DataDelayOffsetInMinutes = number; export type DataIngestionJobSummaries = DataIngestionJobSummary[]; export interface DataIngestionJobSummary { @@ -654,7 +760,7 @@ declare namespace LookoutEquipment { export type DatasetName = string; export interface DatasetSchema { /** - * + * The data schema used within the given dataset. */ InlineDataSchema?: InlineDataSchema; } @@ -708,7 +814,7 @@ declare namespace LookoutEquipment { } export interface DeleteModelRequest { /** - * The name of the ML model to be deleted. + * The name of the machine learning model to be deleted. */ ModelName: ModelName; } @@ -718,6 +824,12 @@ declare namespace LookoutEquipment { */ ResourceArn: ResourceArn; } + export interface DeleteRetrainingSchedulerRequest { + /** + * The name of the model whose retraining scheduler you want to delete. + */ + ModelName: ModelName; + } export interface DescribeDataIngestionJobRequest { /** * The job ID of the data ingestion job. @@ -851,11 +963,11 @@ declare namespace LookoutEquipment { } export interface DescribeInferenceSchedulerResponse { /** - * The Amazon Resource Name (ARN) of the ML model of the inference scheduler being described. + * The Amazon Resource Name (ARN) of the machine learning model of the inference scheduler being described. */ ModelArn?: ModelArn; /** - * The name of the ML model of the inference scheduler being described. + * The name of the machine learning model of the inference scheduler being described. */ ModelName?: ModelName; /** @@ -989,25 +1101,25 @@ declare namespace LookoutEquipment { } export interface DescribeModelRequest { /** - * The name of the ML model to be described. + * The name of the machine learning model to be described. */ ModelName: ModelName; } export interface DescribeModelResponse { /** - * The name of the ML model being described. + * The name of the machine learning model being described. */ ModelName?: ModelName; /** - * The Amazon Resource Name (ARN) of the ML model being described. + * The Amazon Resource Name (ARN) of the machine learning model being described. */ ModelArn?: ModelArn; /** - * The name of the dataset being used by the ML being described. + * The name of the dataset being used by the machine learning being described. */ DatasetName?: DatasetName; /** - * The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described. + * The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described. */ DatasetArn?: DatasetArn; /** @@ -1019,23 +1131,23 @@ declare namespace LookoutEquipment { */ LabelsInputConfiguration?: LabelsInputConfiguration; /** - * Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model. + * Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model. */ TrainingDataStartTime?: Timestamp; /** - * Indicates the time reference in the dataset that was used to end the subset of training data for the ML model. + * Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model. */ TrainingDataEndTime?: Timestamp; /** - * Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model. + * Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model. */ EvaluationDataStartTime?: Timestamp; /** - * Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model. + * Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model. */ EvaluationDataEndTime?: Timestamp; /** - * The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML model being described. + * The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described. */ RoleArn?: IamRoleArn; /** @@ -1047,15 +1159,15 @@ declare namespace LookoutEquipment { */ Status?: ModelStatus; /** - * Indicates the time at which the training of the ML model began. + * Indicates the time at which the training of the machine learning model began. */ TrainingExecutionStartTime?: Timestamp; /** - * Indicates the time at which the training of the ML model was completed. + * Indicates the time at which the training of the machine learning model was completed. */ TrainingExecutionEndTime?: Timestamp; /** - * If the training of the ML model failed, this indicates the reason for that failure. + * If the training of the machine learning model failed, this indicates the reason for that failure. */ FailedReason?: BoundedLengthString; /** @@ -1063,11 +1175,11 @@ declare namespace LookoutEquipment { */ ModelMetrics?: ModelMetrics; /** - * Indicates the last time the ML model was updated. The type of update is not specified. + * Indicates the last time the machine learning model was updated. The type of update is not specified. */ LastUpdatedTime?: Timestamp; /** - * Indicates the time and date at which the ML model was created. + * Indicates the time and date at which the machine learning model was created. */ CreatedAt?: Timestamp; /** @@ -1114,6 +1226,46 @@ declare namespace LookoutEquipment { * The date and time when the previous active model version was activated. */ PreviousModelVersionActivatedAt?: Timestamp; + /** + * If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version. + */ + PriorModelMetrics?: ModelMetrics; + /** + * If the model version was generated by retraining and the training failed, this indicates the reason for that failure. + */ + LatestScheduledRetrainingFailedReason?: BoundedLengthString; + /** + * Indicates the status of the most recent scheduled retraining run. + */ + LatestScheduledRetrainingStatus?: ModelVersionStatus; + /** + * Indicates the most recent model version that was generated by retraining. + */ + LatestScheduledRetrainingModelVersion?: ModelVersion; + /** + * Indicates the start time of the most recent scheduled retraining run. + */ + LatestScheduledRetrainingStartTime?: Timestamp; + /** + * Indicates the number of days of data used in the most recent scheduled retraining run. + */ + LatestScheduledRetrainingAvailableDataInDays?: Integer; + /** + * Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day. + */ + NextScheduledRetrainingStartDate?: Timestamp; + /** + * Indicates the start time of the inference data that has been accumulated. + */ + AccumulatedInferenceDataStartTime?: Timestamp; + /** + * Indicates the end time of the inference data that has been accumulated. + */ + AccumulatedInferenceDataEndTime?: Timestamp; + /** + * Indicates the status of the retraining scheduler. + */ + RetrainingSchedulerStatus?: RetrainingSchedulerStatus; } export interface DescribeModelVersionRequest { /** @@ -1232,6 +1384,22 @@ declare namespace LookoutEquipment { * The size in bytes of the imported data. This field appears if the model version was imported. */ ImportedDataSizeInBytes?: DataSizeInBytes; + /** + * If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version. + */ + PriorModelMetrics?: ModelMetrics; + /** + * Indicates the number of days of data used in the most recent scheduled retraining run. + */ + RetrainingAvailableDataInDays?: Integer; + /** + * Indicates whether the model version was promoted to be the active version after retraining or if there was an error with or cancellation of the retraining. + */ + AutoPromotionResult?: AutoPromotionResult; + /** + * Indicates the reason for the AutoPromotionResult. For example, a model might not be promoted if its performance was worse than the active version, if there was an error during training, or if the retraining scheduler was using MANUAL promote mode. The model will be promoted in MANAGED promote mode if the performance is better than the previous model. + */ + AutoPromotionResultReason?: AutoPromotionResultReason; } export interface DescribeResourcePolicyRequest { /** @@ -1257,6 +1425,50 @@ declare namespace LookoutEquipment { */ LastModifiedTime?: Timestamp; } + export interface DescribeRetrainingSchedulerRequest { + /** + * The name of the model that the retraining scheduler is attached to. + */ + ModelName: ModelName; + } + export interface DescribeRetrainingSchedulerResponse { + /** + * The name of the model that the retraining scheduler is attached to. + */ + ModelName?: ModelName; + /** + * The ARN of the model that the retraining scheduler is attached to. + */ + ModelArn?: ModelArn; + /** + * The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day. + */ + RetrainingStartDate?: Timestamp; + /** + * The frequency at which the model retraining is set. This follows the ISO 8601 guidelines. + */ + RetrainingFrequency?: RetrainingFrequency; + /** + * The number of past days of data used for retraining. + */ + LookbackWindow?: LookbackWindow; + /** + * The status of the retraining scheduler. + */ + Status?: RetrainingSchedulerStatus; + /** + * Indicates how the service uses new models. In MANAGED mode, new models are used for inference if they have better performance than the current model. In MANUAL mode, the new models are not used until they are manually activated. + */ + PromoteMode?: ModelPromoteMode; + /** + * Indicates the time and date at which the retraining scheduler was created. + */ + CreatedAt?: Timestamp; + /** + * Indicates the time and date at which the retraining scheduler was updated. + */ + UpdatedAt?: Timestamp; + } export interface DuplicateTimestamps { /** * Indicates the total number of duplicate timestamps. @@ -1341,6 +1553,10 @@ declare namespace LookoutEquipment { * The tags associated with the machine learning model to be created. */ Tags?: TagList; + /** + * Indicates how to import the accumulated inference data when a model version is imported. The possible values are as follows: NO_IMPORT – Don't import the data. ADD_WHEN_EMPTY – Only import the data from the source model if there is no existing data in the target model. OVERWRITE – Import the data from the source model and overwrite the existing data in the target model. + */ + InferenceDataImportStrategy?: InferenceDataImportStrategy; } export interface ImportModelVersionResponse { /** @@ -1364,6 +1580,7 @@ declare namespace LookoutEquipment { */ Status?: ModelVersionStatus; } + export type InferenceDataImportStrategy = "NO_IMPORT"|"ADD_WHEN_EMPTY"|"OVERWRITE"|string; export type InferenceEventSummaries = InferenceEventSummary[]; export interface InferenceEventSummary { /** @@ -1395,11 +1612,11 @@ declare namespace LookoutEquipment { export type InferenceExecutionSummaries = InferenceExecutionSummary[]; export interface InferenceExecutionSummary { /** - * The name of the ML model being used for the inference execution. + * The name of the machine learning model being used for the inference execution. */ ModelName?: ModelName; /** - * The Amazon Resource Name (ARN) of the ML model used for the inference execution. + * The Amazon Resource Name (ARN) of the machine learning model used for the inference execution. */ ModelArn?: ModelArn; /** @@ -1431,7 +1648,7 @@ declare namespace LookoutEquipment { */ DataOutputConfiguration?: InferenceOutputConfiguration; /** - * + * The S3 object that the inference execution results were uploaded to. */ CustomerResultObject?: S3Object; /** @@ -1442,6 +1659,14 @@ declare namespace LookoutEquipment { * Specifies the reason for failure when an inference execution has failed. */ FailedReason?: BoundedLengthString; + /** + * The model version used for the inference execution. + */ + ModelVersion?: ModelVersion; + /** + * The Amazon Resource Number (ARN) of the model version used for the inference execution. + */ + ModelVersionArn?: ModelVersionArn; } export interface InferenceInputConfiguration { /** @@ -1504,11 +1729,11 @@ declare namespace LookoutEquipment { export type InferenceSchedulerSummaries = InferenceSchedulerSummary[]; export interface InferenceSchedulerSummary { /** - * The name of the ML model used for the inference scheduler. + * The name of the machine learning model used for the inference scheduler. */ ModelName?: ModelName; /** - * The Amazon Resource Name (ARN) of the ML model used by the inference scheduler. + * The Amazon Resource Name (ARN) of the machine learning model used by the inference scheduler. */ ModelArn?: ModelArn; /** @@ -1827,7 +2052,7 @@ declare namespace LookoutEquipment { */ InferenceSchedulerNameBeginsWith?: InferenceSchedulerIdentifier; /** - * The name of the ML model used by the inference scheduler to be listed. + * The name of the machine learning model used by the inference scheduler to be listed. */ ModelName?: ModelName; /** @@ -1959,29 +2184,29 @@ declare namespace LookoutEquipment { } export interface ListModelsRequest { /** - * An opaque pagination token indicating where to continue the listing of ML models. + * An opaque pagination token indicating where to continue the listing of machine learning models. */ NextToken?: NextToken; /** - * Specifies the maximum number of ML models to list. + * Specifies the maximum number of machine learning models to list. */ MaxResults?: MaxResults; /** - * The status of the ML model. + * The status of the machine learning model. */ Status?: ModelStatus; /** - * The beginning of the name of the ML models being listed. + * The beginning of the name of the machine learning models being listed. */ ModelNameBeginsWith?: ModelName; /** - * The beginning of the name of the dataset of the ML models to be listed. + * The beginning of the name of the dataset of the machine learning models to be listed. */ DatasetNameBeginsWith?: DatasetName; } export interface ListModelsResponse { /** - * An opaque pagination token indicating where to continue the listing of ML models. + * An opaque pagination token indicating where to continue the listing of machine learning models. */ NextToken?: NextToken; /** @@ -1990,6 +2215,34 @@ declare namespace LookoutEquipment { ModelSummaries?: ModelSummaries; } export type ListOfDiscardedFiles = S3Object[]; + export interface ListRetrainingSchedulersRequest { + /** + * Specify this field to only list retraining schedulers whose machine learning models begin with the value you specify. + */ + ModelNameBeginsWith?: ModelName; + /** + * Specify this field to only list retraining schedulers whose status matches the value you specify. + */ + Status?: RetrainingSchedulerStatus; + /** + * If the number of results exceeds the maximum, a pagination token is returned. Use the token in the request to show the next page of retraining schedulers. + */ + NextToken?: NextToken; + /** + * Specifies the maximum number of retraining schedulers to list. + */ + MaxResults?: MaxResults; + } + export interface ListRetrainingSchedulersResponse { + /** + * Provides information on the specified retraining scheduler, including the model name, model ARN, status, and start date. + */ + RetrainingSchedulerSummaries?: RetrainingSchedulerSummaries; + /** + * If the number of results exceeds the maximum, this pagination token is returned. Use this token in the request to show the next page of retraining schedulers. + */ + NextToken?: NextToken; + } export interface ListSensorStatisticsRequest { /** * The name of the dataset associated with the list of Sensor Statistics. @@ -2030,6 +2283,7 @@ declare namespace LookoutEquipment { */ Tags?: TagList; } + export type LookbackWindow = string; export type MaxResults = number; export interface MissingCompleteSensorData { /** @@ -2050,19 +2304,20 @@ declare namespace LookoutEquipment { export type ModelArn = string; export type ModelMetrics = string; export type ModelName = string; + export type ModelPromoteMode = "MANAGED"|"MANUAL"|string; export type ModelStatus = "IN_PROGRESS"|"SUCCESS"|"FAILED"|"IMPORT_IN_PROGRESS"|string; export type ModelSummaries = ModelSummary[]; export interface ModelSummary { /** - * The name of the ML model. + * The name of the machine learning model. */ ModelName?: ModelName; /** - * The Amazon Resource Name (ARN) of the ML model. + * The Amazon Resource Name (ARN) of the machine learning model. */ ModelArn?: ModelArn; /** - * The name of the dataset being used for the ML model. + * The name of the dataset being used for the machine learning model. */ DatasetName?: DatasetName; /** @@ -2070,7 +2325,7 @@ declare namespace LookoutEquipment { */ DatasetArn?: DatasetArn; /** - * Indicates the status of the ML model. + * Indicates the status of the machine learning model. */ Status?: ModelStatus; /** @@ -2085,6 +2340,26 @@ declare namespace LookoutEquipment { * The Amazon Resource Name (ARN) of the model version that is set as active. The active model version is the model version that the inference scheduler uses to run an inference execution. */ ActiveModelVersionArn?: ModelVersionArn; + /** + * Indicates the status of the most recent scheduled retraining run. + */ + LatestScheduledRetrainingStatus?: ModelVersionStatus; + /** + * Indicates the most recent model version that was generated by retraining. + */ + LatestScheduledRetrainingModelVersion?: ModelVersion; + /** + * Indicates the start time of the most recent scheduled retraining run. + */ + LatestScheduledRetrainingStartTime?: Timestamp; + /** + * Indicates the date that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day. + */ + NextScheduledRetrainingStartDate?: Timestamp; + /** + * Indicates the status of the retraining scheduler. + */ + RetrainingSchedulerStatus?: RetrainingSchedulerStatus; } export type ModelVersion = number; export type ModelVersionArn = string; @@ -2172,6 +2447,35 @@ declare namespace LookoutEquipment { PolicyRevisionId?: PolicyRevisionId; } export type ResourceArn = string; + export type RetrainingFrequency = string; + export type RetrainingSchedulerStatus = "PENDING"|"RUNNING"|"STOPPING"|"STOPPED"|string; + export type RetrainingSchedulerSummaries = RetrainingSchedulerSummary[]; + export interface RetrainingSchedulerSummary { + /** + * The name of the model that the retraining scheduler is attached to. + */ + ModelName?: ModelName; + /** + * The ARN of the model that the retraining scheduler is attached to. + */ + ModelArn?: ModelArn; + /** + * The status of the retraining scheduler. + */ + Status?: RetrainingSchedulerStatus; + /** + * The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day. + */ + RetrainingStartDate?: Timestamp; + /** + * The frequency at which the model retraining is set. This follows the ISO 8601 guidelines. + */ + RetrainingFrequency?: RetrainingFrequency; + /** + * The number of past days of data used for retraining. + */ + LookbackWindow?: LookbackWindow; + } export type S3Bucket = string; export type S3Key = string; export interface S3Object { @@ -2283,11 +2587,11 @@ declare namespace LookoutEquipment { } export interface StartInferenceSchedulerResponse { /** - * The Amazon Resource Name (ARN) of the ML model being used by the inference scheduler. + * The Amazon Resource Name (ARN) of the machine learning model being used by the inference scheduler. */ ModelArn?: ModelArn; /** - * The name of the ML model being used by the inference scheduler. + * The name of the machine learning model being used by the inference scheduler. */ ModelName?: ModelName; /** @@ -2303,6 +2607,26 @@ declare namespace LookoutEquipment { */ Status?: InferenceSchedulerStatus; } + export interface StartRetrainingSchedulerRequest { + /** + * The name of the model whose retraining scheduler you want to start. + */ + ModelName: ModelName; + } + export interface StartRetrainingSchedulerResponse { + /** + * The name of the model whose retraining scheduler is being started. + */ + ModelName?: ModelName; + /** + * The ARN of the model whose retraining scheduler is being started. + */ + ModelArn?: ModelArn; + /** + * The status of the retraining scheduler. + */ + Status?: RetrainingSchedulerStatus; + } export type StatisticalIssueStatus = "POTENTIAL_ISSUE_DETECTED"|"NO_ISSUE_DETECTED"|string; export interface StopInferenceSchedulerRequest { /** @@ -2312,11 +2636,11 @@ declare namespace LookoutEquipment { } export interface StopInferenceSchedulerResponse { /** - * The Amazon Resource Name (ARN) of the ML model used by the inference scheduler being stopped. + * The Amazon Resource Name (ARN) of the machine learning model used by the inference scheduler being stopped. */ ModelArn?: ModelArn; /** - * The name of the ML model used by the inference scheduler being stopped. + * The name of the machine learning model used by the inference scheduler being stopped. */ ModelName?: ModelName; /** @@ -2332,6 +2656,26 @@ declare namespace LookoutEquipment { */ Status?: InferenceSchedulerStatus; } + export interface StopRetrainingSchedulerRequest { + /** + * The name of the model whose retraining scheduler you want to stop. + */ + ModelName: ModelName; + } + export interface StopRetrainingSchedulerResponse { + /** + * The name of the model whose retraining scheduler is being stopped. + */ + ModelName?: ModelName; + /** + * The ARN of the model whose retraining scheduler is being stopped. + */ + ModelArn?: ModelArn; + /** + * The status of the retraining scheduler. + */ + Status?: RetrainingSchedulerStatus; + } export interface Tag { /** * The key for the specified tag. @@ -2451,6 +2795,39 @@ declare namespace LookoutEquipment { */ FaultCodes?: FaultCodes; } + export interface UpdateModelRequest { + /** + * The name of the model to update. + */ + ModelName: ModelName; + LabelsInputConfiguration?: LabelsInputConfiguration; + /** + * The ARN of the model to update. + */ + RoleArn?: IamRoleArn; + } + export interface UpdateRetrainingSchedulerRequest { + /** + * The name of the model whose retraining scheduler you want to update. + */ + ModelName: ModelName; + /** + * The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day. + */ + RetrainingStartDate?: Timestamp; + /** + * This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid: P3M15D – Every 3 months and 15 days P2M – Every 2 months P150D – Every 150 days + */ + RetrainingFrequency?: RetrainingFrequency; + /** + * The number of past days of data that will be used for retraining. + */ + LookbackWindow?: LookbackWindow; + /** + * Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated. + */ + PromoteMode?: ModelPromoteMode; + } /** * A string in YYYY-MM-DD format that represents the latest possible API version that can be used in this service. Specify 'latest' to use the latest possible version. */ diff --git a/dist/aws-sdk-core-react-native.js b/dist/aws-sdk-core-react-native.js index ede689514f..258b024995 100644 --- a/dist/aws-sdk-core-react-native.js +++ b/dist/aws-sdk-core-react-native.js @@ -83,7 +83,7 @@ return /******/ (function(modules) { // webpackBootstrap /** * @constant */ - VERSION: '2.1457.0', + VERSION: '2.1458.0', /** * @api private diff --git a/dist/aws-sdk-react-native.js b/dist/aws-sdk-react-native.js index b41d93c139..baa7bdc2bd 100644 --- a/dist/aws-sdk-react-native.js +++ b/dist/aws-sdk-react-native.js @@ -395,7 +395,7 @@ return /******/ (function(modules) { // webpackBootstrap /** * @constant */ - VERSION: '2.1457.0', + VERSION: '2.1458.0', /** * @api private @@ -35495,7 +35495,7 @@ return /******/ (function(modules) { // webpackBootstrap /* 62 */ /***/ (function(module, exports) { - module.exports = 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e=this,t=e.buffer,r=e.state,a=r[0],i=r[1],p=r[2],m=r[3];a=s(a,i,p,m,t.getUint32(0,!0),7,3614090360),m=s(m,a,i,p,t.getUint32(4,!0),12,3905402710),p=s(p,m,a,i,t.getUint32(8,!0),17,606105819),i=s(i,p,m,a,t.getUint32(12,!0),22,3250441966),a=s(a,i,p,m,t.getUint32(16,!0),7,4118548399),m=s(m,a,i,p,t.getUint32(20,!0),12,1200080426),p=s(p,m,a,i,t.getUint32(24,!0),17,2821735955),i=s(i,p,m,a,t.getUint32(28,!0),22,4249261313),a=s(a,i,p,m,t.getUint32(32,!0),7,1770035416),m=s(m,a,i,p,t.getUint32(36,!0),12,2336552879),p=s(p,m,a,i,t.getUint32(40,!0),17,4294925233),i=s(i,p,m,a,t.getUint32(44,!0),22,2304563134),a=s(a,i,p,m,t.getUint32(48,!0),7,1804603682),m=s(m,a,i,p,t.getUint32(52,!0),12,4254626195),p=s(p,m,a,i,t.getUint32(56,!0),17,2792965006),i=s(i,p,m,a,t.getUint32(60,!0),22,1236535329),a=o(a,i,p,m,t.getUint32(4,!0),5,4129170786),m=o(m,a,i,p,t.getUint32(24,!0),9,3225465664),p=o(p,m,a,i,t.getUint32(44,!0),14,643717713),i=o(i,p,m,a,t.getUint32(0,!0),20,3921069994),a=o(a,i,p,m,t.getUint32(20,!0),5,3593408605),m=o(m,a,i,p,t.getUint32(40,!0),9,38016083),p=o(p,m,a,i,t.getUint32(60,!0),14,3634488961),i=o(i,p,m,a,t.getUint32(16,!0),20,3889429448),a=o(a,i,p,m,t.getUint32(36,!0),5,568446438),m=o(m,a,i,p,t.getUint32(56,!0),9,3275163606),p=o(p,m,a,i,t.getUint32(12,!0),14,4107603335),i=o(i,p,m,a,t.getUint32(32,!0),20,1163531501),a=o(a,i,p,m,t.getUint32(52,!0),5,2850285829),m=o(m,a,i,p,t.getUint32(8,!0),9,4243563512),p=o(p,m,a,i,t.getUint32(28,!0),14,1735328473),i=o(i,p,m,a,t.getUint32(48,!0),20,2368359562),a=n(a,i,p,m,t.getUint32(20,!0),4,4294588738),m=n(m,a,i,p,t.getUint32(32,!0),11,2272392833),p=n(p,m,a,i,t.getUint32(44,!0),16,1839030562),i=n(i,p,m,a,t.getUint32(56,!0),23,4259657740),a=n(a,i,p,m,t.getUint32(4,!0),4,2763975236),m=n(m,a,i,p,t.getUint32(16,!0),11,1272893353),p=n(p,m,a,i,t.getUint32(28,!0),16,4139469664),i=n(i,p,m,a,t.getUint32(40,!0),23,3200236656),a=n(a,i,p,m,t.getUint32(52,!0),4,681279174),m=n(m,a,i,p,t.getUint32(0,!0),11,3936430074),p=n(p,m,a,i,t.getUint32(12,!0),16,3572445317),i=n(i,p,m,a,t.getUint32(24,!0),23,76029189),a=n(a,i,p,m,t.getUint32(36,!0),4,3654602809),m=n(m,a,i,p,t.getUint32(48,!0),11,3873151461),p=n(p,m,a,i,t.getUint32(60,!0),16,530742520),i=n(i,p,m,a,t.getUint32(8,!0),23,3299628645),a=u(a,i,p,m,t.getUint32(0,!0),6,4096336452),m=u(m,a,i,p,t.getUint32(28,!0),10,1126891415),p=u(p,m,a,i,t.getUint32(56,!0),15,2878612391),i=u(i,p,m,a,t.getUint32(20,!0),21,4237533241),a=u(a,i,p,m,t.getUint32(48,!0),6,1700485571),m=u(m,a,i,p,t.getUint32(12,!0),10,2399980690),p=u(p,m,a,i,t.getUint32(40,!0),15,4293915773),i=u(i,p,m,a,t.getUint32(4,!0),21,2240044497),a=u(a,i,p,m,t.getUint32(32,!0),6,1873313359),m=u(m,a,i,p,t.getUint32(60,!0),10,4264355552),p=u(p,m,a,i,t.getUint32(24,!0),15,2734768916),i=u(i,p,m,a,t.getUint32(52,!0),21,1309151649),a=u(a,i,p,m,t.getUint32(16,!0),6,4149444226),m=u(m,a,i,p,t.getUint32(44,!0),10,3174756917),p=u(p,m,a,i,t.getUint32(8,!0),15,718787259),i=u(i,p,m,a,t.getUint32(36,!0),21,3951481745),r[0]=a+r[0]&4294967295,r[1]=i+r[1]&4294967295,r[2]=p+r[2]&4294967295,r[3]=m+r[3]&4294967295}},{"./browserHashUtils":341,"buffer/":440}],344:[function(e,t,r){function a(){this.h0=1732584193,this.h1=4023233417,this.h2=2562383102,this.h3=271733878,this.h4=3285377520,this.block=new Uint32Array(80),this.offset=0,this.shift=24,this.totalLength=0}var i=e("buffer/").Buffer,s=e("./browserHashUtils");new Uint32Array([1518500249,1859775393,-1894007588,-899497514]),Math.pow(2,53);t.exports=a,a.BLOCK_SIZE=64,a.prototype.update=function(e){if(this.finished)throw new Error("Attempted to update an already finished hash.");if(s.isEmptyData(e))return this;e=s.convertToBuffer(e);var t=e.length;this.totalLength+=8*t;for(var r=0;r14||14===this.offset&&this.shift<24)&&this.processBlock(),this.offset=14,this.shift=24,this.write(0),this.write(0),this.write(this.totalLength>0xffffffffff?this.totalLength/1099511627776:0),this.write(this.totalLength>4294967295?this.totalLength/4294967296:0);for(var t=24;t>=0;t-=8)this.write(this.totalLength>>t);var r=new i(20),a=new DataView(r.buffer);return a.setUint32(0,this.h0,!1),a.setUint32(4,this.h1,!1),a.setUint32(8,this.h2,!1),a.setUint32(12,this.h3,!1),a.setUint32(16,this.h4,!1),e?r.toString(e):r},a.prototype.processBlock=function(){for(var e=16;e<80;e++){var t=this.block[e-3]^this.block[e-8]^this.block[e-14]^this.block[e-16];this.block[e]=t<<1|t>>>31}var r,a,i=this.h0,s=this.h1,o=this.h2,n=this.h3,u=this.h4;for(e=0;e<80;e++){e<20?(r=n^s&(o^n),a=1518500249):e<40?(r=s^o^n,a=1859775393):e<60?(r=s&o|n&(s|o),a=2400959708):(r=s^o^n,a=3395469782);var p=(i<<5|i>>>27)+r+u+a+(0|this.block[e]);u=n,n=o,o=s<<30|s>>>2,s=i,i=p}for(this.h0=this.h0+i|0,this.h1=this.h1+s|0,this.h2=this.h2+o|0,this.h3=this.h3+n|0,this.h4=this.h4+u|0,this.offset=0,e=0;e<16;e++)this.block[e]=0}},{"./browserHashUtils":341,"buffer/":440}],345:[function(e,t,r){function a(){this.state=[1779033703,3144134277,1013904242,2773480762,1359893119,2600822924,528734635,1541459225],this.temp=new Int32Array(64),this.buffer=new Uint8Array(64),this.bufferLength=0,this.bytesHashed=0,this.finished=!1}var i=e("buffer/").Buffer,s=e("./browserHashUtils"),o=new Uint32Array([1116352408,1899447441,3049323471,3921009573,961987163,1508970993,2453635748,2870763221,3624381080,310598401,607225278,1426881987,1925078388,2162078206,2614888103,3248222580,3835390401,4022224774,264347078,604807628,770255983,1249150122,1555081692,1996064986,2554220882,2821834349,2952996808,3210313671,3336571891,3584528711,113926993,338241895,666307205,773529912,1294757372,1396182291,1695183700,1986661051,2177026350,2456956037,2730485921,2820302411,3259730800,3345764771,3516065817,3600352804,4094571909,275423344,430227734,506948616,659060556,883997877,958139571,1322822218,1537002063,1747873779,1955562222,2024104815,2227730452,2361852424,2428436474,2756734187,3204031479,3329325298]),n=Math.pow(2,53)-1;t.exports=a,a.BLOCK_SIZE=64,a.prototype.update=function(e){if(this.finished)throw new Error("Attempted to update an already finished hash.");if(s.isEmptyData(e))return this;e=s.convertToBuffer(e);var t=0,r=e.byteLength;if(this.bytesHashed+=r,8*this.bytesHashed>n)throw new Error("Cannot hash more than 2^53 - 1 bits");for(;r>0;)this.buffer[this.bufferLength++]=e[t++],r--,64===this.bufferLength&&(this.hashBuffer(),this.bufferLength=0);return this},a.prototype.digest=function(e){if(!this.finished){var t=8*this.bytesHashed,r=new DataView(this.buffer.buffer,this.buffer.byteOffset,this.buffer.byteLength),a=this.bufferLength;if(r.setUint8(this.bufferLength++,128),a%64>=56){for(var s=this.bufferLength;s<64;s++)r.setUint8(s,0);this.hashBuffer(),this.bufferLength=0}for(var s=this.bufferLength;s<56;s++)r.setUint8(s,0);r.setUint32(56,Math.floor(t/4294967296),!0),r.setUint32(60,t),this.hashBuffer(),this.finished=!0}for(var o=new i(32),s=0;s<8;s++)o[4*s]=this.state[s]>>>24&255,o[4*s+1]=this.state[s]>>>16&255,o[4*s+2]=this.state[s]>>>8&255,o[4*s+3]=this.state[s]>>>0&255;return e?o.toString(e):o},a.prototype.hashBuffer=function(){for(var e=this,t=e.buffer,r=e.state,a=r[0],i=r[1],s=r[2],n=r[3],u=r[4],p=r[5],m=r[6],c=r[7],l=0;l<64;l++){if(l<16)this.temp[l]=(255&t[4*l])<<24|(255&t[4*l+1])<<16|(255&t[4*l+2])<<8|255&t[4*l+3];else{var d=this.temp[l-2],y=(d>>>17|d<<15)^(d>>>19|d<<13)^d>>>10;d=this.temp[l-15];var b=(d>>>7|d<<25)^(d>>>18|d<<14)^d>>>3;this.temp[l]=(y+this.temp[l-7]|0)+(b+this.temp[l-16]|0)}var S=(((u>>>6|u<<26)^(u>>>11|u<<21)^(u>>>25|u<<7))+(u&p^~u&m)|0)+(c+(o[l]+this.temp[l]|0)|0)|0,g=((a>>>2|a<<30)^(a>>>13|a<<19)^(a>>>22|a<<10))+(a&i^a&s^i&s)|0;c=m,m=p,p=u,u=n+S|0,n=s,s=i,i=a,a=S+g|0}r[0]+=a,r[1]+=i,r[2]+=s,r[3]+=n,r[4]+=u,r[5]+=p,r[6]+=m,r[7]+=c}},{"./browserHashUtils":341,"buffer/":440}],346:[function(e,t,r){(function(r){(function(){var r=e("./util");r.crypto.lib=e("./browserCryptoLib"),r.Buffer=e("buffer/").Buffer,r.url=e("url/"),r.querystring=e("querystring/"),r.realClock=e("./realclock/browserClock"),r.environment="js",r.createEventStream=e("./event-stream/buffered-create-event-stream").createEventStream,r.isBrowser=function(){return!0},r.isNode=function(){return!1};var a=e("./core");if(t.exports=a,e("./credentials"),e("./credentials/credential_provider_chain"),e("./credentials/temporary_credentials"),e("./credentials/chainable_temporary_credentials"),e("./credentials/web_identity_credentials"),e("./credentials/cognito_identity_credentials"),e("./credentials/saml_credentials"),a.XML.Parser=e("./xml/browser_parser"),e("./http/xhr"),void 0===i)var i={browser:!0}}).call(this)}).call(this,e("_process"))},{"./browserCryptoLib":340,"./core":350,"./credentials":351, -"./credentials/chainable_temporary_credentials":352,"./credentials/cognito_identity_credentials":353,"./credentials/credential_provider_chain":354,"./credentials/saml_credentials":355,"./credentials/temporary_credentials":356,"./credentials/web_identity_credentials":357,"./event-stream/buffered-create-event-stream":365,"./http/xhr":373,"./realclock/browserClock":393,"./util":428,"./xml/browser_parser":429,_process:445,"buffer/":440,"querystring/":452,"url/":454}],347:[function(e,t,r){var a=e("../core"),i=a.util.url,s=a.util.crypto.lib,o=a.util.base64.encode,n=a.util.inherit,u=function(e){var t={"+":"-","=":"_","/":"~"};return e.replace(/[\+=\/]/g,function(e){return t[e]})},p=function(e,t){var r=s.createSign("RSA-SHA1");return r.write(e),u(r.sign(t,"base64"))},m=function(e,t,r,a){var i=JSON.stringify({Statement:[{Resource:e,Condition:{DateLessThan:{"AWS:EpochTime":t}}}]});return{Expires:t,"Key-Pair-Id":r,Signature:p(i.toString(),a)}},c=function(e,t,r){return e=e.replace(/\s/gm,""),{Policy:u(o(e)),"Key-Pair-Id":t,Signature:p(e,r)}},l=function(e){var t=e.split("://");if(t.length<2)throw new Error("Invalid URL.");return t[0].replace("*","")},d=function(e){var t=i.parse(e);return t.path.replace(/^\//,"")+(t.hash||"")},y=function(e){switch(l(e)){case"http":case"https":return e;case"rtmp":return d(e);default:throw new Error("Invalid URI scheme. Scheme must be one of http, https, or rtmp")}},b=function(e,t){if(!t||"function"!=typeof t)throw e;t(e)},S=function(e,t){if(!t||"function"!=typeof t)return e;t(null,e)};a.CloudFront.Signer=n({constructor:function(e,t){if(void 0===e||void 0===t)throw new Error("A key pair ID and private key are required");this.keyPairId=e,this.privateKey=t},getSignedCookie:function(e,t){var r="policy"in e?c(e.policy,this.keyPairId,this.privateKey):m(e.url,e.expires,this.keyPairId,this.privateKey),a={};for(var i in r)Object.prototype.hasOwnProperty.call(r,i)&&(a["CloudFront-"+i]=r[i]);return S(a,t)},getSignedUrl:function(e,t){try{var r=y(e.url)}catch(e){return b(e,t)}var a=i.parse(e.url,!0),s=Object.prototype.hasOwnProperty.call(e,"policy")?c(e.policy,this.keyPairId,this.privateKey):m(r,e.expires,this.keyPairId,this.privateKey);a.search=null;for(var o in s)Object.prototype.hasOwnProperty.call(s,o)&&(a.query[o]=s[o]);try{var n="rtmp"===l(e.url)?d(i.format(a)):i.format(a)}catch(e){return b(e,t)}return S(n,t)}}),t.exports=a.CloudFront.Signer},{"../core":350}],348:[function(e,t,r){var a=e("./core");e("./credentials"),e("./credentials/credential_provider_chain");var i;a.Config=a.util.inherit({constructor:function(e){void 0===e&&(e={}),e=this.extractCredentials(e),a.util.each.call(this,this.keys,function(t,r){this.set(t,e[t],r)})},getCredentials:function(e){function t(t){e(t,t?null:i.credentials)}function r(e,t){return new a.util.error(t||new Error,{code:"CredentialsError",message:e,name:"CredentialsError"})}var i=this;i.credentials?"function"==typeof i.credentials.get?function(){i.credentials.get(function(e){e&&(e=r("Could not load credentials from "+i.credentials.constructor.name,e)),t(e)})}():function(){var e=null;i.credentials.accessKeyId&&i.credentials.secretAccessKey||(e=r("Missing credentials")),t(e)}():i.credentialProvider?i.credentialProvider.resolve(function(e,a){e&&(e=r("Could not load credentials from any providers",e)),i.credentials=a,t(e)}):t(r("No credentials to load"))},getToken:function(e){function t(t){e(t,t?null:i.token)}function r(e,t){return new a.util.error(t||new Error,{code:"TokenError",message:e,name:"TokenError"})}var i=this;i.token?"function"==typeof i.token.get?function(){i.token.get(function(e){e&&(e=r("Could not load token from "+i.token.constructor.name,e)),t(e)})}():function(){var e=null;i.token.token||(e=r("Missing token")),t(e)}():i.tokenProvider?i.tokenProvider.resolve(function(e,a){e&&(e=r("Could not load token from any providers",e)),i.token=a,t(e)}):t(r("No token to load"))},update:function(e,t){t=t||!1,e=this.extractCredentials(e),a.util.each.call(this,e,function(e,r){(t||Object.prototype.hasOwnProperty.call(this.keys,e)||a.Service.hasService(e))&&this.set(e,r)})},loadFromPath:function(e){this.clear();var t=JSON.parse(a.util.readFileSync(e)),r=new a.FileSystemCredentials(e),i=new a.CredentialProviderChain;return i.providers.unshift(r),i.resolve(function(e,r){if(e)throw e;t.credentials=r}),this.constructor(t),this},clear:function(){a.util.each.call(this,this.keys,function(e){delete this[e]}),this.set("credentials",void 0),this.set("credentialProvider",void 0)},set:function(e,t,r){void 0===t?(void 0===r&&(r=this.keys[e]),this[e]="function"==typeof r?r.call(this):r):"httpOptions"===e&&this[e]?this[e]=a.util.merge(this[e],t):this[e]=t},keys:{credentials:null,credentialProvider:null,region:null,logger:null,apiVersions:{},apiVersion:null,endpoint:void 0,httpOptions:{timeout:12e4},maxRetries:void 0,maxRedirects:10,paramValidation:!0,sslEnabled:!0,s3ForcePathStyle:!1,s3BucketEndpoint:!1,s3DisableBodySigning:!0,s3UsEast1RegionalEndpoint:"legacy",s3UseArnRegion:void 0,computeChecksums:!0,convertResponseTypes:!0,correctClockSkew:!1,customUserAgent:null,dynamoDbCrc32:!0,systemClockOffset:0,signatureVersion:null,signatureCache:!0,retryDelayOptions:{},useAccelerateEndpoint:!1,clientSideMonitoring:!1,endpointDiscoveryEnabled:void 0,endpointCacheSize:1e3,hostPrefixEnabled:!0,stsRegionalEndpoints:"legacy",useFipsEndpoint:!1,useDualstackEndpoint:!1,token:null},extractCredentials:function(e){return e.accessKeyId&&e.secretAccessKey&&(e=a.util.copy(e),e.credentials=new a.Credentials(e)),e},setPromisesDependency:function(e){i=e,null===e&&"function"==typeof Promise&&(i=Promise);var t=[a.Request,a.Credentials,a.CredentialProviderChain];a.S3&&(t.push(a.S3),a.S3.ManagedUpload&&t.push(a.S3.ManagedUpload)),a.util.addPromises(t,i)},getPromisesDependency:function(){return i}}),a.config=new a.Config},{"./core":350,"./credentials":351,"./credentials/credential_provider_chain":354}],349:[function(e,t,r){(function(r){(function(){function a(e,t){if("string"==typeof e){if(["legacy","regional"].indexOf(e.toLowerCase())>=0)return e.toLowerCase();throw s.util.error(new Error,t)}}function i(e,t){e=e||{};var i;if(e[t.clientConfig]&&(i=a(e[t.clientConfig],{code:"InvalidConfiguration",message:'invalid "'+t.clientConfig+'" configuration. Expect "legacy" or "regional". Got "'+e[t.clientConfig]+'".'})))return i;if(!s.util.isNode())return i;if(Object.prototype.hasOwnProperty.call(r.env,t.env)){if(i=a(r.env[t.env],{code:"InvalidEnvironmentalVariable",message:"invalid "+t.env+' environmental variable. Expect "legacy" or "regional". Got "'+r.env[t.env]+'".'}))return i}var o={};try{o=s.util.getProfilesFromSharedConfig(s.util.iniLoader)[r.env.AWS_PROFILE||s.util.defaultProfile]}catch(e){}if(o&&Object.prototype.hasOwnProperty.call(o,t.sharedConfig)){if(i=a(o[t.sharedConfig],{code:"InvalidConfiguration",message:"invalid "+t.sharedConfig+' profile config. Expect "legacy" or "regional". Got "'+o[t.sharedConfig]+'".'}))return i}return i}var s=e("./core");t.exports=i}).call(this)}).call(this,e("_process"))},{"./core":350,_process:445}],350:[function(e,t,r){var a={util:e("./util")};({}).toString(),t.exports=a,a.util.update(a,{VERSION:"2.1457.0",Signers:{},Protocol:{Json:e("./protocol/json"),Query:e("./protocol/query"),Rest:e("./protocol/rest"),RestJson:e("./protocol/rest_json"),RestXml:e("./protocol/rest_xml")},XML:{Builder:e("./xml/builder"),Parser:null},JSON:{Builder:e("./json/builder"),Parser:e("./json/parser")},Model:{Api:e("./model/api"),Operation:e("./model/operation"),Shape:e("./model/shape"),Paginator:e("./model/paginator"),ResourceWaiter:e("./model/resource_waiter")},apiLoader:e("./api_loader"),EndpointCache:e("../vendor/endpoint-cache").EndpointCache}),e("./sequential_executor"),e("./service"),e("./config"),e("./http"),e("./event_listeners"),e("./request"),e("./response"),e("./resource_waiter"),e("./signers/request_signer"),e("./param_validator"),e("./maintenance_mode_message"),a.events=new a.SequentialExecutor,a.util.memoizedProperty(a,"endpointCache",function(){return new a.EndpointCache(a.config.endpointCacheSize)},!0)},{"../vendor/endpoint-cache":465,"./api_loader":339,"./config":348,"./event_listeners":371,"./http":372,"./json/builder":374,"./json/parser":375,"./maintenance_mode_message":376,"./model/api":377,"./model/operation":379,"./model/paginator":380,"./model/resource_waiter":381,"./model/shape":382,"./param_validator":383,"./protocol/json":386,"./protocol/query":387,"./protocol/rest":388,"./protocol/rest_json":389,"./protocol/rest_xml":390,"./request":397,"./resource_waiter":398,"./response":399,"./sequential_executor":401,"./service":402,"./signers/request_signer":420,"./util":428,"./xml/builder":430}],351:[function(e,t,r){var a=e("./core");a.Credentials=a.util.inherit({constructor:function(){if(a.util.hideProperties(this,["secretAccessKey"]),this.expired=!1,this.expireTime=null,this.refreshCallbacks=[],1===arguments.length&&"object"==typeof arguments[0]){var e=arguments[0].credentials||arguments[0];this.accessKeyId=e.accessKeyId,this.secretAccessKey=e.secretAccessKey,this.sessionToken=e.sessionToken}else this.accessKeyId=arguments[0],this.secretAccessKey=arguments[1],this.sessionToken=arguments[2]},expiryWindow:15,needsRefresh:function(){var e=a.util.date.getDate().getTime(),t=new Date(e+1e3*this.expiryWindow);return!!(this.expireTime&&t>this.expireTime)||(this.expired||!this.accessKeyId||!this.secretAccessKey)},get:function(e){var t=this;this.needsRefresh()?this.refresh(function(r){r||(t.expired=!1),e&&e(r)}):e&&e()},refresh:function(e){this.expired=!1,e()},coalesceRefresh:function(e,t){var r=this;1===r.refreshCallbacks.push(e)&&r.load(function(e){a.util.arrayEach(r.refreshCallbacks,function(r){t?r(e):a.util.defer(function(){r(e)})}),r.refreshCallbacks.length=0})},load:function(e){e()}}),a.Credentials.addPromisesToClass=function(e){this.prototype.getPromise=a.util.promisifyMethod("get",e),this.prototype.refreshPromise=a.util.promisifyMethod("refresh",e)},a.Credentials.deletePromisesFromClass=function(){delete this.prototype.getPromise,delete this.prototype.refreshPromise},a.util.addPromises(a.Credentials)},{"./core":350}],352:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.ChainableTemporaryCredentials=a.util.inherit(a.Credentials,{constructor:function(e){a.Credentials.call(this),e=e||{},this.errorCode="ChainableTemporaryCredentialsProviderFailure",this.expired=!0,this.tokenCodeFn=null;var t=a.util.copy(e.params)||{};if(t.RoleArn&&(t.RoleSessionName=t.RoleSessionName||"temporary-credentials"),t.SerialNumber){if(!e.tokenCodeFn||"function"!=typeof e.tokenCodeFn)throw new a.util.error(new Error("tokenCodeFn must be a function when params.SerialNumber is given"),{code:this.errorCode});this.tokenCodeFn=e.tokenCodeFn}var r=a.util.merge({params:t,credentials:e.masterCredentials||a.config.credentials},e.stsConfig||{});this.service=new i(r)},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this,r=t.service.config.params.RoleArn?"assumeRole":"getSessionToken";this.getTokenCode(function(a,i){var s={};if(a)return void e(a);i&&(s.TokenCode=i),t.service[r](s,function(r,a){r||t.service.credentialsFrom(a,t),e(r)})})},getTokenCode:function(e){var t=this;this.tokenCodeFn?this.tokenCodeFn(this.service.config.params.SerialNumber,function(r,i){if(r){var s=r;return r instanceof Error&&(s=r.message),void e(a.util.error(new Error("Error fetching MFA token: "+s),{code:t.errorCode}))}e(null,i)}):e(null)}})},{"../../clients/sts":334,"../core":350}],353:[function(e,t,r){var a=e("../core"),i=e("../../clients/cognitoidentity"),s=e("../../clients/sts");a.CognitoIdentityCredentials=a.util.inherit(a.Credentials,{localStorageKey:{id:"aws.cognito.identity-id.",providers:"aws.cognito.identity-providers."},constructor:function(e,t){a.Credentials.call(this),this.expired=!0,this.params=e,this.data=null,this._identityId=null,this._clientConfig=a.util.copy(t||{}),this.loadCachedId();var r=this;Object.defineProperty(this,"identityId",{get:function(){return r.loadCachedId(),r._identityId||r.params.IdentityId},set:function(e){r._identityId=e}})},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.data=null,t._identityId=null,t.getId(function(r){r?(t.clearIdOnNotAuthorized(r),e(r)):t.params.RoleArn?t.getCredentialsFromSTS(e):t.getCredentialsForIdentity(e)})},clearCachedId:function(){this._identityId=null,delete this.params.IdentityId;var e=this.params.IdentityPoolId,t=this.params.LoginId||"";delete this.storage[this.localStorageKey.id+e+t],delete this.storage[this.localStorageKey.providers+e+t]},clearIdOnNotAuthorized:function(e){var t=this;"NotAuthorizedException"==e.code&&t.clearCachedId()},getId:function(e){var t=this;if("string"==typeof t.params.IdentityId)return e(null,t.params.IdentityId);t.cognito.getId(function(r,a){!r&&a.IdentityId?(t.params.IdentityId=a.IdentityId,e(null,a.IdentityId)):e(r)})},loadCredentials:function(e,t){e&&t&&(t.expired=!1,t.accessKeyId=e.Credentials.AccessKeyId,t.secretAccessKey=e.Credentials.SecretKey,t.sessionToken=e.Credentials.SessionToken,t.expireTime=e.Credentials.Expiration)},getCredentialsForIdentity:function(e){var t=this;t.cognito.getCredentialsForIdentity(function(r,a){r?t.clearIdOnNotAuthorized(r):(t.cacheId(a),t.data=a,t.loadCredentials(t.data,t)),e(r)})},getCredentialsFromSTS:function(e){var t=this;t.cognito.getOpenIdToken(function(r,a){r?(t.clearIdOnNotAuthorized(r),e(r)):(t.cacheId(a),t.params.WebIdentityToken=a.Token,t.webIdentityCredentials.refresh(function(r){r||(t.data=t.webIdentityCredentials.data,t.sts.credentialsFrom(t.data,t)),e(r)}))})},loadCachedId:function(){var e=this;if(a.util.isBrowser()&&!e.params.IdentityId){var t=e.getStorage("id");if(t&&e.params.Logins){var r=Object.keys(e.params.Logins);0!==(e.getStorage("providers")||"").split(",").filter(function(e){return-1!==r.indexOf(e)}).length&&(e.params.IdentityId=t)}else t&&(e.params.IdentityId=t)}},createClients:function(){var e=this._clientConfig;if(this.webIdentityCredentials=this.webIdentityCredentials||new a.WebIdentityCredentials(this.params,e),!this.cognito){var t=a.util.merge({},e);t.params=this.params,this.cognito=new i(t)}this.sts=this.sts||new s(e)},cacheId:function(e){this._identityId=e.IdentityId,this.params.IdentityId=this._identityId,a.util.isBrowser()&&(this.setStorage("id",e.IdentityId),this.params.Logins&&this.setStorage("providers",Object.keys(this.params.Logins).join(",")))},getStorage:function(e){return this.storage[this.localStorageKey[e]+this.params.IdentityPoolId+(this.params.LoginId||"")]},setStorage:function(e,t){try{this.storage[this.localStorageKey[e]+this.params.IdentityPoolId+(this.params.LoginId||"")]=t}catch(e){}},storage:function(){try{var e=a.util.isBrowser()&&null!==window.localStorage&&"object"==typeof window.localStorage?window.localStorage:{};return e["aws.test-storage"]="foobar",delete e["aws.test-storage"],e}catch(e){return{}}}()})},{"../../clients/cognitoidentity":265,"../../clients/sts":334,"../core":350}],354:[function(e,t,r){var a=e("../core");a.CredentialProviderChain=a.util.inherit(a.Credentials,{constructor:function(e){this.providers=e||a.CredentialProviderChain.defaultProviders.slice(0),this.resolveCallbacks=[]},resolve:function(e){function t(e,o){if(!e&&o||i===s.length)return a.util.arrayEach(r.resolveCallbacks,function(t){t(e,o)}),void(r.resolveCallbacks.length=0);var n=s[i++];o="function"==typeof n?n.call():n,o.get?o.get(function(e){t(e,e?null:o)}):t(null,o)}var r=this;if(0===r.providers.length)return e(new Error("No providers")),r;if(1===r.resolveCallbacks.push(e)){var i=0,s=r.providers.slice(0);t()}return r}}),a.CredentialProviderChain.defaultProviders=[],a.CredentialProviderChain.addPromisesToClass=function(e){this.prototype.resolvePromise=a.util.promisifyMethod("resolve",e)},a.CredentialProviderChain.deletePromisesFromClass=function(){delete this.prototype.resolvePromise},a.util.addPromises(a.CredentialProviderChain)},{"../core":350}],355:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.SAMLCredentials=a.util.inherit(a.Credentials,{constructor:function(e){a.Credentials.call(this),this.expired=!0,this.params=e},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.service.assumeRoleWithSAML(function(r,a){r||t.service.credentialsFrom(a,t),e(r)})},createClients:function(){this.service=this.service||new i({params:this.params})}})},{"../../clients/sts":334,"../core":350}],356:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.TemporaryCredentials=a.util.inherit(a.Credentials,{constructor:function(e,t){a.Credentials.call(this),this.loadMasterCredentials(t),this.expired=!0,this.params=e||{},this.params.RoleArn&&(this.params.RoleSessionName=this.params.RoleSessionName||"temporary-credentials")},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.masterCredentials.get(function(){t.service.config.credentials=t.masterCredentials,(t.params.RoleArn?t.service.assumeRole:t.service.getSessionToken).call(t.service,function(r,a){r||t.service.credentialsFrom(a,t),e(r)})})},loadMasterCredentials:function(e){for(this.masterCredentials=e||a.config.credentials;this.masterCredentials.masterCredentials;)this.masterCredentials=this.masterCredentials.masterCredentials;"function"!=typeof this.masterCredentials.get&&(this.masterCredentials=new a.Credentials(this.masterCredentials))},createClients:function(){this.service=this.service||new i({params:this.params})}})},{"../../clients/sts":334,"../core":350}],357:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.WebIdentityCredentials=a.util.inherit(a.Credentials,{constructor:function(e,t){a.Credentials.call(this),this.expired=!0,this.params=e,this.params.RoleSessionName=this.params.RoleSessionName||"web-identity",this.data=null,this._clientConfig=a.util.copy(t||{})},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.service.assumeRoleWithWebIdentity(function(r,a){t.data=null,r||(t.data=a,t.service.credentialsFrom(a,t)),e(r)})},createClients:function(){if(!this.service){var e=a.util.merge({},this._clientConfig);e.params=this.params,this.service=new i(e)}}})},{"../../clients/sts":334,"../core":350}],358:[function(e,t,r){(function(r){(function(){function a(e){var t=e.service,r=t.api||{},a={};return t.config.region&&(a.region=t.config.region),r.serviceId&&(a.serviceId=r.serviceId),t.config.credentials.accessKeyId&&(a.accessKeyId=t.config.credentials.accessKeyId),a}function i(e,t,r){r&&void 0!==t&&null!==t&&"structure"===r.type&&r.required&&r.required.length>0&&b.arrayEach(r.required,function(a){var s=r.members[a];if(!0===s.endpointDiscoveryId){var o=s.isLocationName?s.name:a;e[o]=String(t[a])}else i(e,t[a],s)})}function s(e,t){var r={};return i(r,e.params,t),r}function o(e){var t=e.service,r=t.api,i=r.operations?r.operations[e.operation]:void 0,o=i?i.input:void 0,n=s(e,o),p=a(e);Object.keys(n).length>0&&(p=b.update(p,n),i&&(p.operation=i.name));var m=y.endpointCache.get(p);if(!m||1!==m.length||""!==m[0].Address)if(m&&m.length>0)e.httpRequest.updateEndpoint(m[0].Address);else{var c=t.makeRequest(r.endpointOperation,{Operation:i.name,Identifiers:n});u(c),c.removeListener("validate",y.EventListeners.Core.VALIDATE_PARAMETERS),c.removeListener("retry",y.EventListeners.Core.RETRY_CHECK),y.endpointCache.put(p,[{Address:"",CachePeriodInMinutes:1}]),c.send(function(e,t){t&&t.Endpoints?y.endpointCache.put(p,t.Endpoints):e&&y.endpointCache.put(p,[{Address:"",CachePeriodInMinutes:1}])})}}function n(e,t){var r=e.service,i=r.api,o=i.operations?i.operations[e.operation]:void 0,n=o?o.input:void 0,p=s(e,n),m=a(e);Object.keys(p).length>0&&(m=b.update(m,p),o&&(m.operation=o.name));var c=y.EndpointCache.getKeyString(m),l=y.endpointCache.get(c);if(l&&1===l.length&&""===l[0].Address)return g[c]||(g[c]=[]),void g[c].push({request:e,callback:t});if(l&&l.length>0)e.httpRequest.updateEndpoint(l[0].Address),t();else{var d=r.makeRequest(i.endpointOperation,{Operation:o.name,Identifiers:p});d.removeListener("validate",y.EventListeners.Core.VALIDATE_PARAMETERS),u(d),y.endpointCache.put(c,[{Address:"",CachePeriodInMinutes:60}]),d.send(function(r,a){if(r){if(e.response.error=b.error(r,{retryable:!1}),y.endpointCache.remove(m),g[c]){var i=g[c];b.arrayEach(i,function(e){e.request.response.error=b.error(r,{retryable:!1}),e.callback()}),delete g[c]}}else if(a&&(y.endpointCache.put(c,a.Endpoints),e.httpRequest.updateEndpoint(a.Endpoints[0].Address),g[c])){var i=g[c];b.arrayEach(i,function(e){e.request.httpRequest.updateEndpoint(a.Endpoints[0].Address),e.callback()}),delete g[c]}t()})}}function u(e){var t=e.service.api,r=t.apiVersion;r&&!e.httpRequest.headers["x-amz-api-version"]&&(e.httpRequest.headers["x-amz-api-version"]=r)}function p(e){var t=e.error,r=e.httpResponse;if(t&&("InvalidEndpointException"===t.code||421===r.statusCode)){var i=e.request,o=i.service.api.operations||{},n=o[i.operation]?o[i.operation].input:void 0,u=s(i,n),p=a(i);Object.keys(u).length>0&&(p=b.update(p,u),o[i.operation]&&(p.operation=o[i.operation].name)),y.endpointCache.remove(p)}}function m(e){if(e._originalConfig&&e._originalConfig.endpoint&&!0===e._originalConfig.endpointDiscoveryEnabled)throw b.error(new Error,{code:"ConfigurationException",message:"Custom endpoint is supplied; endpointDiscoveryEnabled must not be true."});var t=y.config[e.serviceIdentifier]||{};return Boolean(y.config.endpoint||t.endpoint||e._originalConfig&&e._originalConfig.endpoint)}function c(e){return["false","0"].indexOf(e)>=0}function l(e){var t=e.service||{};if(void 0!==t.config.endpointDiscoveryEnabled)return t.config.endpointDiscoveryEnabled;if(!b.isBrowser()){for(var a=0;a=0)return e.toLowerCase();throw s.util.error(new Error,t)}}function i(e,t){e=e||{};var i;if(e[t.clientConfig]&&(i=a(e[t.clientConfig],{code:"InvalidConfiguration",message:'invalid "'+t.clientConfig+'" configuration. Expect "legacy" or "regional". Got "'+e[t.clientConfig]+'".'})))return i;if(!s.util.isNode())return i;if(Object.prototype.hasOwnProperty.call(r.env,t.env)){if(i=a(r.env[t.env],{code:"InvalidEnvironmentalVariable",message:"invalid "+t.env+' environmental variable. Expect "legacy" or "regional". Got "'+r.env[t.env]+'".'}))return i}var o={};try{o=s.util.getProfilesFromSharedConfig(s.util.iniLoader)[r.env.AWS_PROFILE||s.util.defaultProfile]}catch(e){}if(o&&Object.prototype.hasOwnProperty.call(o,t.sharedConfig)){if(i=a(o[t.sharedConfig],{code:"InvalidConfiguration",message:"invalid "+t.sharedConfig+' profile config. Expect "legacy" or "regional". Got "'+o[t.sharedConfig]+'".'}))return i}return i}var s=e("./core");t.exports=i}).call(this)}).call(this,e("_process"))},{"./core":350,_process:445}],350:[function(e,t,r){var a={util:e("./util")};({}).toString(),t.exports=a,a.util.update(a,{VERSION:"2.1458.0",Signers:{},Protocol:{Json:e("./protocol/json"),Query:e("./protocol/query"),Rest:e("./protocol/rest"),RestJson:e("./protocol/rest_json"),RestXml:e("./protocol/rest_xml")},XML:{Builder:e("./xml/builder"),Parser:null},JSON:{Builder:e("./json/builder"),Parser:e("./json/parser")},Model:{Api:e("./model/api"),Operation:e("./model/operation"),Shape:e("./model/shape"),Paginator:e("./model/paginator"),ResourceWaiter:e("./model/resource_waiter")},apiLoader:e("./api_loader"),EndpointCache:e("../vendor/endpoint-cache").EndpointCache}),e("./sequential_executor"),e("./service"),e("./config"),e("./http"),e("./event_listeners"),e("./request"),e("./response"),e("./resource_waiter"),e("./signers/request_signer"),e("./param_validator"),e("./maintenance_mode_message"),a.events=new a.SequentialExecutor,a.util.memoizedProperty(a,"endpointCache",function(){return new a.EndpointCache(a.config.endpointCacheSize)},!0)},{"../vendor/endpoint-cache":465,"./api_loader":339,"./config":348,"./event_listeners":371,"./http":372,"./json/builder":374,"./json/parser":375,"./maintenance_mode_message":376,"./model/api":377,"./model/operation":379,"./model/paginator":380,"./model/resource_waiter":381,"./model/shape":382,"./param_validator":383,"./protocol/json":386,"./protocol/query":387,"./protocol/rest":388,"./protocol/rest_json":389,"./protocol/rest_xml":390,"./request":397,"./resource_waiter":398,"./response":399,"./sequential_executor":401,"./service":402,"./signers/request_signer":420,"./util":428,"./xml/builder":430}],351:[function(e,t,r){var a=e("./core");a.Credentials=a.util.inherit({constructor:function(){if(a.util.hideProperties(this,["secretAccessKey"]),this.expired=!1,this.expireTime=null,this.refreshCallbacks=[],1===arguments.length&&"object"==typeof arguments[0]){var e=arguments[0].credentials||arguments[0];this.accessKeyId=e.accessKeyId,this.secretAccessKey=e.secretAccessKey,this.sessionToken=e.sessionToken}else this.accessKeyId=arguments[0],this.secretAccessKey=arguments[1],this.sessionToken=arguments[2]},expiryWindow:15,needsRefresh:function(){var e=a.util.date.getDate().getTime(),t=new Date(e+1e3*this.expiryWindow);return!!(this.expireTime&&t>this.expireTime)||(this.expired||!this.accessKeyId||!this.secretAccessKey)},get:function(e){var t=this;this.needsRefresh()?this.refresh(function(r){r||(t.expired=!1),e&&e(r)}):e&&e()},refresh:function(e){this.expired=!1,e()},coalesceRefresh:function(e,t){var r=this;1===r.refreshCallbacks.push(e)&&r.load(function(e){a.util.arrayEach(r.refreshCallbacks,function(r){t?r(e):a.util.defer(function(){r(e)})}),r.refreshCallbacks.length=0})},load:function(e){e()}}),a.Credentials.addPromisesToClass=function(e){this.prototype.getPromise=a.util.promisifyMethod("get",e),this.prototype.refreshPromise=a.util.promisifyMethod("refresh",e)},a.Credentials.deletePromisesFromClass=function(){delete this.prototype.getPromise,delete this.prototype.refreshPromise},a.util.addPromises(a.Credentials)},{"./core":350}],352:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.ChainableTemporaryCredentials=a.util.inherit(a.Credentials,{constructor:function(e){a.Credentials.call(this),e=e||{},this.errorCode="ChainableTemporaryCredentialsProviderFailure",this.expired=!0,this.tokenCodeFn=null;var t=a.util.copy(e.params)||{};if(t.RoleArn&&(t.RoleSessionName=t.RoleSessionName||"temporary-credentials"),t.SerialNumber){if(!e.tokenCodeFn||"function"!=typeof e.tokenCodeFn)throw new a.util.error(new Error("tokenCodeFn must be a function when params.SerialNumber is given"),{code:this.errorCode});this.tokenCodeFn=e.tokenCodeFn}var r=a.util.merge({params:t,credentials:e.masterCredentials||a.config.credentials},e.stsConfig||{});this.service=new i(r)},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this,r=t.service.config.params.RoleArn?"assumeRole":"getSessionToken";this.getTokenCode(function(a,i){var s={};if(a)return void e(a);i&&(s.TokenCode=i),t.service[r](s,function(r,a){r||t.service.credentialsFrom(a,t),e(r)})})},getTokenCode:function(e){var t=this;this.tokenCodeFn?this.tokenCodeFn(this.service.config.params.SerialNumber,function(r,i){if(r){var s=r;return r instanceof Error&&(s=r.message),void e(a.util.error(new Error("Error fetching MFA token: "+s),{code:t.errorCode}))}e(null,i)}):e(null)}})},{"../../clients/sts":334,"../core":350}],353:[function(e,t,r){var a=e("../core"),i=e("../../clients/cognitoidentity"),s=e("../../clients/sts");a.CognitoIdentityCredentials=a.util.inherit(a.Credentials,{localStorageKey:{id:"aws.cognito.identity-id.",providers:"aws.cognito.identity-providers."},constructor:function(e,t){a.Credentials.call(this),this.expired=!0,this.params=e,this.data=null,this._identityId=null,this._clientConfig=a.util.copy(t||{}),this.loadCachedId();var r=this;Object.defineProperty(this,"identityId",{get:function(){return r.loadCachedId(),r._identityId||r.params.IdentityId},set:function(e){r._identityId=e}})},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.data=null,t._identityId=null,t.getId(function(r){r?(t.clearIdOnNotAuthorized(r),e(r)):t.params.RoleArn?t.getCredentialsFromSTS(e):t.getCredentialsForIdentity(e)})},clearCachedId:function(){this._identityId=null,delete this.params.IdentityId;var e=this.params.IdentityPoolId,t=this.params.LoginId||"";delete this.storage[this.localStorageKey.id+e+t],delete this.storage[this.localStorageKey.providers+e+t]},clearIdOnNotAuthorized:function(e){var t=this;"NotAuthorizedException"==e.code&&t.clearCachedId()},getId:function(e){var t=this;if("string"==typeof t.params.IdentityId)return e(null,t.params.IdentityId);t.cognito.getId(function(r,a){!r&&a.IdentityId?(t.params.IdentityId=a.IdentityId,e(null,a.IdentityId)):e(r)})},loadCredentials:function(e,t){e&&t&&(t.expired=!1,t.accessKeyId=e.Credentials.AccessKeyId,t.secretAccessKey=e.Credentials.SecretKey,t.sessionToken=e.Credentials.SessionToken,t.expireTime=e.Credentials.Expiration)},getCredentialsForIdentity:function(e){var t=this;t.cognito.getCredentialsForIdentity(function(r,a){r?t.clearIdOnNotAuthorized(r):(t.cacheId(a),t.data=a,t.loadCredentials(t.data,t)),e(r)})},getCredentialsFromSTS:function(e){var t=this;t.cognito.getOpenIdToken(function(r,a){r?(t.clearIdOnNotAuthorized(r),e(r)):(t.cacheId(a),t.params.WebIdentityToken=a.Token,t.webIdentityCredentials.refresh(function(r){r||(t.data=t.webIdentityCredentials.data,t.sts.credentialsFrom(t.data,t)),e(r)}))})},loadCachedId:function(){var e=this;if(a.util.isBrowser()&&!e.params.IdentityId){var t=e.getStorage("id");if(t&&e.params.Logins){var r=Object.keys(e.params.Logins);0!==(e.getStorage("providers")||"").split(",").filter(function(e){return-1!==r.indexOf(e)}).length&&(e.params.IdentityId=t)}else t&&(e.params.IdentityId=t)}},createClients:function(){var e=this._clientConfig;if(this.webIdentityCredentials=this.webIdentityCredentials||new a.WebIdentityCredentials(this.params,e),!this.cognito){var t=a.util.merge({},e);t.params=this.params,this.cognito=new i(t)}this.sts=this.sts||new s(e)},cacheId:function(e){this._identityId=e.IdentityId,this.params.IdentityId=this._identityId,a.util.isBrowser()&&(this.setStorage("id",e.IdentityId),this.params.Logins&&this.setStorage("providers",Object.keys(this.params.Logins).join(",")))},getStorage:function(e){return this.storage[this.localStorageKey[e]+this.params.IdentityPoolId+(this.params.LoginId||"")]},setStorage:function(e,t){try{this.storage[this.localStorageKey[e]+this.params.IdentityPoolId+(this.params.LoginId||"")]=t}catch(e){}},storage:function(){try{var e=a.util.isBrowser()&&null!==window.localStorage&&"object"==typeof window.localStorage?window.localStorage:{};return e["aws.test-storage"]="foobar",delete e["aws.test-storage"],e}catch(e){return{}}}()})},{"../../clients/cognitoidentity":265,"../../clients/sts":334,"../core":350}],354:[function(e,t,r){var a=e("../core");a.CredentialProviderChain=a.util.inherit(a.Credentials,{constructor:function(e){this.providers=e||a.CredentialProviderChain.defaultProviders.slice(0),this.resolveCallbacks=[]},resolve:function(e){function t(e,o){if(!e&&o||i===s.length)return a.util.arrayEach(r.resolveCallbacks,function(t){t(e,o)}),void(r.resolveCallbacks.length=0);var n=s[i++];o="function"==typeof n?n.call():n,o.get?o.get(function(e){t(e,e?null:o)}):t(null,o)}var r=this;if(0===r.providers.length)return e(new Error("No providers")),r;if(1===r.resolveCallbacks.push(e)){var i=0,s=r.providers.slice(0);t()}return r}}),a.CredentialProviderChain.defaultProviders=[],a.CredentialProviderChain.addPromisesToClass=function(e){this.prototype.resolvePromise=a.util.promisifyMethod("resolve",e)},a.CredentialProviderChain.deletePromisesFromClass=function(){delete this.prototype.resolvePromise},a.util.addPromises(a.CredentialProviderChain)},{"../core":350}],355:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.SAMLCredentials=a.util.inherit(a.Credentials,{constructor:function(e){a.Credentials.call(this),this.expired=!0,this.params=e},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.service.assumeRoleWithSAML(function(r,a){r||t.service.credentialsFrom(a,t),e(r)})},createClients:function(){this.service=this.service||new i({params:this.params})}})},{"../../clients/sts":334,"../core":350}],356:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.TemporaryCredentials=a.util.inherit(a.Credentials,{constructor:function(e,t){a.Credentials.call(this),this.loadMasterCredentials(t),this.expired=!0,this.params=e||{},this.params.RoleArn&&(this.params.RoleSessionName=this.params.RoleSessionName||"temporary-credentials")},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.masterCredentials.get(function(){t.service.config.credentials=t.masterCredentials,(t.params.RoleArn?t.service.assumeRole:t.service.getSessionToken).call(t.service,function(r,a){r||t.service.credentialsFrom(a,t),e(r)})})},loadMasterCredentials:function(e){for(this.masterCredentials=e||a.config.credentials;this.masterCredentials.masterCredentials;)this.masterCredentials=this.masterCredentials.masterCredentials;"function"!=typeof this.masterCredentials.get&&(this.masterCredentials=new a.Credentials(this.masterCredentials))},createClients:function(){this.service=this.service||new i({params:this.params})}})},{"../../clients/sts":334,"../core":350}],357:[function(e,t,r){var a=e("../core"),i=e("../../clients/sts");a.WebIdentityCredentials=a.util.inherit(a.Credentials,{constructor:function(e,t){a.Credentials.call(this),this.expired=!0,this.params=e,this.params.RoleSessionName=this.params.RoleSessionName||"web-identity",this.data=null,this._clientConfig=a.util.copy(t||{})},refresh:function(e){this.coalesceRefresh(e||a.util.fn.callback)},load:function(e){var t=this;t.createClients(),t.service.assumeRoleWithWebIdentity(function(r,a){t.data=null,r||(t.data=a,t.service.credentialsFrom(a,t)),e(r)})},createClients:function(){if(!this.service){var e=a.util.merge({},this._clientConfig);e.params=this.params,this.service=new i(e)}}})},{"../../clients/sts":334,"../core":350}],358:[function(e,t,r){(function(r){(function(){function a(e){var t=e.service,r=t.api||{},a={};return t.config.region&&(a.region=t.config.region),r.serviceId&&(a.serviceId=r.serviceId),t.config.credentials.accessKeyId&&(a.accessKeyId=t.config.credentials.accessKeyId),a}function i(e,t,r){r&&void 0!==t&&null!==t&&"structure"===r.type&&r.required&&r.required.length>0&&b.arrayEach(r.required,function(a){var s=r.members[a];if(!0===s.endpointDiscoveryId){var o=s.isLocationName?s.name:a;e[o]=String(t[a])}else i(e,t[a],s)})}function s(e,t){var r={};return i(r,e.params,t),r}function o(e){var t=e.service,r=t.api,i=r.operations?r.operations[e.operation]:void 0,o=i?i.input:void 0,n=s(e,o),p=a(e);Object.keys(n).length>0&&(p=b.update(p,n),i&&(p.operation=i.name));var m=y.endpointCache.get(p);if(!m||1!==m.length||""!==m[0].Address)if(m&&m.length>0)e.httpRequest.updateEndpoint(m[0].Address);else{var c=t.makeRequest(r.endpointOperation,{Operation:i.name,Identifiers:n});u(c),c.removeListener("validate",y.EventListeners.Core.VALIDATE_PARAMETERS),c.removeListener("retry",y.EventListeners.Core.RETRY_CHECK),y.endpointCache.put(p,[{Address:"",CachePeriodInMinutes:1}]),c.send(function(e,t){t&&t.Endpoints?y.endpointCache.put(p,t.Endpoints):e&&y.endpointCache.put(p,[{Address:"",CachePeriodInMinutes:1}])})}}function n(e,t){var r=e.service,i=r.api,o=i.operations?i.operations[e.operation]:void 0,n=o?o.input:void 0,p=s(e,n),m=a(e);Object.keys(p).length>0&&(m=b.update(m,p),o&&(m.operation=o.name));var c=y.EndpointCache.getKeyString(m),l=y.endpointCache.get(c);if(l&&1===l.length&&""===l[0].Address)return g[c]||(g[c]=[]),void g[c].push({request:e,callback:t});if(l&&l.length>0)e.httpRequest.updateEndpoint(l[0].Address),t();else{var d=r.makeRequest(i.endpointOperation,{Operation:o.name,Identifiers:p});d.removeListener("validate",y.EventListeners.Core.VALIDATE_PARAMETERS),u(d),y.endpointCache.put(c,[{Address:"",CachePeriodInMinutes:60}]),d.send(function(r,a){if(r){if(e.response.error=b.error(r,{retryable:!1}),y.endpointCache.remove(m),g[c]){var i=g[c];b.arrayEach(i,function(e){e.request.response.error=b.error(r,{retryable:!1}),e.callback()}),delete g[c]}}else if(a&&(y.endpointCache.put(c,a.Endpoints),e.httpRequest.updateEndpoint(a.Endpoints[0].Address),g[c])){var i=g[c];b.arrayEach(i,function(e){e.request.httpRequest.updateEndpoint(a.Endpoints[0].Address),e.callback()}),delete g[c]}t()})}}function u(e){var t=e.service.api,r=t.apiVersion;r&&!e.httpRequest.headers["x-amz-api-version"]&&(e.httpRequest.headers["x-amz-api-version"]=r)}function p(e){var t=e.error,r=e.httpResponse;if(t&&("InvalidEndpointException"===t.code||421===r.statusCode)){var i=e.request,o=i.service.api.operations||{},n=o[i.operation]?o[i.operation].input:void 0,u=s(i,n),p=a(i);Object.keys(u).length>0&&(p=b.update(p,u),o[i.operation]&&(p.operation=o[i.operation].name)),y.endpointCache.remove(p)}}function m(e){if(e._originalConfig&&e._originalConfig.endpoint&&!0===e._originalConfig.endpointDiscoveryEnabled)throw b.error(new Error,{code:"ConfigurationException",message:"Custom endpoint is supplied; endpointDiscoveryEnabled must not be true."});var t=y.config[e.serviceIdentifier]||{};return Boolean(y.config.endpoint||t.endpoint||e._originalConfig&&e._originalConfig.endpoint)}function c(e){return["false","0"].indexOf(e)>=0}function l(e){var t=e.service||{};if(void 0!==t.config.endpointDiscoveryEnabled)return t.config.endpointDiscoveryEnabled;if(!b.isBrowser()){for(var a=0;a-1&&0===++e[t];t--);}var s=e("../core").util,o=s.buffer.toBuffer;a.fromNumber=function(e){if(e>0x8000000000000000||e<-0x8000000000000000)throw new Error(e+" is too large (or, if negative, too small) to represent as an Int64");for(var t=new Uint8Array(8),r=7,s=Math.abs(Math.round(e));r>-1&&s>0;r--,s/=256)t[r]=s;return e<0&&i(t),new a(t)},a.prototype.valueOf=function(){var e=this.bytes.slice(0),t=128&e[0];return t&&i(e),parseInt(e.toString("hex"),16)*(t?-1:1)},a.prototype.toString=function(){return String(this.valueOf())},t.exports={Int64:a}},{"../core":350}],368:[function(e,t,r){function a(e,t,r){var a=s(t),o=a.headers[":message-type"];if(o){if("error"===o.value)throw i(a);if("event"!==o.value)return}var n=a.headers[":event-type"],u=r.members[n.value];if(u){var p={},m=u.eventPayloadMemberName;if(m){var c=u.members[m];"binary"===c.type?p[m]=a.body:p[m]=e.parse(a.body.toString(),c)}for(var l=u.eventHeaderMemberNames,d=0;d=0)return e.httpRequest.headers["X-Amz-Content-Sha256"]="UNSIGNED-PAYLOAD",t();i.util.computeSha256(s,function(r,a){r?t(r):(e.httpRequest.headers["X-Amz-Content-Sha256"]=a,t())})}else t()}}),e("SET_CONTENT_LENGTH","afterBuild",function(e){var t=r(e),a=i.util.getRequestPayloadShape(e);if(void 0===e.httpRequest.headers["Content-Length"])try{var s=i.util.string.byteLength(e.httpRequest.body);e.httpRequest.headers["Content-Length"]=s}catch(r){if(a&&a.isStreaming){if(a.requiresLength)throw r;if(t.indexOf("unsigned-body")>=0)return void(e.httpRequest.headers["Transfer-Encoding"]="chunked");throw r}throw r}}),e("SET_HTTP_HOST","afterBuild",function(e){e.httpRequest.headers.Host=e.httpRequest.endpoint.host}),e("SET_TRACE_ID","afterBuild",function(e){if(i.util.isNode()&&!Object.hasOwnProperty.call(e.httpRequest.headers,"X-Amzn-Trace-Id")){var r=t.env.AWS_LAMBDA_FUNCTION_NAME,a=t.env._X_AMZN_TRACE_ID;"string"==typeof r&&r.length>0&&"string"==typeof a&&a.length>0&&(e.httpRequest.headers["X-Amzn-Trace-Id"]=a)}}),e("RESTART","restart",function(){var e=this.response.error;e&&e.retryable&&(this.httpRequest=new i.HttpRequest(this.service.endpoint,this.service.region),this.response.retryCount=600?this.emit("sign",[this],function(e){e?t(e):o()}):o()}),e("HTTP_HEADERS","httpHeaders",function(e,t,r,a){r.httpResponse.statusCode=e,r.httpResponse.statusMessage=a,r.httpResponse.headers=t,r.httpResponse.body=i.util.buffer.toBuffer(""),r.httpResponse.buffers=[],r.httpResponse.numBytes=0;var s=t.date||t.Date,o=r.request.service;if(s){var n=Date.parse(s);o.config.correctClockSkew&&o.isClockSkewed(n)&&o.applyClockOffset(n)}}),e("HTTP_DATA","httpData",function(e,t){if(e){if(i.util.isNode()){t.httpResponse.numBytes+=e.length;var r=t.httpResponse.headers["content-length"],a={loaded:t.httpResponse.numBytes,total:r};t.request.emit("httpDownloadProgress",[a,t])}t.httpResponse.buffers.push(i.util.buffer.toBuffer(e))}}),e("HTTP_DONE","httpDone",function(e){if(e.httpResponse.buffers&&e.httpResponse.buffers.length>0){var t=i.util.buffer.concat(e.httpResponse.buffers);e.httpResponse.body=t}delete e.httpResponse.numBytes,delete e.httpResponse.buffers}),e("FINALIZE_ERROR","retry",function(e){e.httpResponse.statusCode&&(e.error.statusCode=e.httpResponse.statusCode,void 0===e.error.retryable&&(e.error.retryable=this.service.retryableError(e.error,this)))}),e("INVALIDATE_CREDENTIALS","retry",function(e){if(e.error)switch(e.error.code){case"RequestExpired":case"ExpiredTokenException":case"ExpiredToken":e.error.retryable=!0,e.request.service.config.credentials.expired=!0}}),e("EXPIRED_SIGNATURE","retry",function(e){var t=e.error;t&&"string"==typeof t.code&&"string"==typeof t.message&&t.code.match(/Signature/)&&t.message.match(/expired/)&&(e.error.retryable=!0)}),e("CLOCK_SKEWED","retry",function(e){e.error&&this.service.clockSkewError(e.error)&&this.service.config.correctClockSkew&&(e.error.retryable=!0)}),e("REDIRECT","retry",function(e){e.error&&e.error.statusCode>=300&&e.error.statusCode<400&&e.httpResponse.headers.location&&(this.httpRequest.endpoint=new i.Endpoint(e.httpResponse.headers.location),this.httpRequest.headers.Host=this.httpRequest.endpoint.host,e.error.redirect=!0,e.error.retryable=!0)}),e("RETRY_CHECK","retry",function(e){e.error&&(e.error.redirect&&e.redirectCount=0?(e.error=null,setTimeout(t,r)):t()})}),CorePost:(new s).addNamedListeners(function(e){e("EXTRACT_REQUEST_ID","extractData",i.util.extractRequestId),e("EXTRACT_REQUEST_ID","extractError",i.util.extractRequestId),e("ENOTFOUND_ERROR","httpError",function(e){if("NetworkingError"===e.code&&function(e){return"ENOTFOUND"===e.errno||"number"==typeof e.errno&&"function"==typeof i.util.getSystemErrorName&&["EAI_NONAME","EAI_NODATA"].indexOf(i.util.getSystemErrorName(e.errno)>=0)}(e)){var t="Inaccessible host: `"+e.hostname+"' at port `"+e.port+"'. This service may not be available in the `"+e.region+"' region.";this.response.error=i.util.error(new Error(t),{code:"UnknownEndpoint",region:e.region,hostname:e.hostname,retryable:!0,originalError:e})}})}),Logger:(new s).addNamedListeners(function(t){t("LOG_REQUEST","complete",function(t){function r(e,t){if(!t)return t;if(e.isSensitive)return"***SensitiveInformation***";switch(e.type){case"structure":var a={};return i.util.each(t,function(t,i){Object.prototype.hasOwnProperty.call(e.members,t)?a[t]=r(e.members[t],i):a[t]=i}),a;case"list":var s=[];return i.util.arrayEach(t,function(t,a){s.push(r(e.member,t))}),s;case"map":var o={};return i.util.each(t,function(t,a){o[t]=r(e.value,a)}),o;default:return t}}var a=t.request,s=a.service.config.logger;if(s){var o=function(){var o=t.request.service.getSkewCorrectedDate().getTime(),n=(o-a.startTime.getTime())/1e3,u=!!s.isTTY,p=t.httpResponse.statusCode,m=a.params;if(a.service.api.operations&&a.service.api.operations[a.operation]&&a.service.api.operations[a.operation].input){m=r(a.service.api.operations[a.operation].input,a.params)}var c=e("util").inspect(m,!0,null),l="";return u&&(l+=""),l+="[AWS "+a.service.serviceIdentifier+" "+p,l+=" "+n.toString()+"s "+t.retryCount+" retries]",u&&(l+=""),l+=" "+i.util.string.lowerFirst(a.operation),l+="("+c+")",u&&(l+=""),l}();"function"==typeof s.log?s.log(o):"function"==typeof s.write&&s.write(o+"\n")}})}),Json:(new s).addNamedListeners(function(t){var r=e("./protocol/json");t("BUILD","build",r.buildRequest),t("EXTRACT_DATA","extractData",r.extractData),t("EXTRACT_ERROR","extractError",r.extractError)}),Rest:(new s).addNamedListeners(function(t){var r=e("./protocol/rest");t("BUILD","build",r.buildRequest),t("EXTRACT_DATA","extractData",r.extractData),t("EXTRACT_ERROR","extractError",r.extractError)}),RestJson:(new s).addNamedListeners(function(t){var r=e("./protocol/rest_json");t("BUILD","build",r.buildRequest),t("EXTRACT_DATA","extractData",r.extractData),t("EXTRACT_ERROR","extractError",r.extractError),t("UNSET_CONTENT_LENGTH","afterBuild",r.unsetContentLength)}),RestXml:(new s).addNamedListeners(function(t){var r=e("./protocol/rest_xml");t("BUILD","build",r.buildRequest),t("EXTRACT_DATA","extractData",r.extractData),t("EXTRACT_ERROR","extractError",r.extractError)}),Query:(new s).addNamedListeners(function(t){var r=e("./protocol/query");t("BUILD","build",r.buildRequest),t("EXTRACT_DATA","extractData",r.extractData),t("EXTRACT_ERROR","extractError",r.extractError)})}}).call(this)}).call(this,e("_process"))},{"./core":350,"./discover_endpoint":358,"./protocol/json":386,"./protocol/query":387,"./protocol/rest":388,"./protocol/rest_json":389,"./protocol/rest_xml":390,"./sequential_executor":401,_process:445,util:439}],372:[function(e,t,r){var a=e("./core"),i=a.util.inherit;a.Endpoint=i({constructor:function(e,t){if(a.util.hideProperties(this,["slashes","auth","hash","search","query"]),void 0===e||null===e)throw new Error("Invalid endpoint: "+e);if("string"!=typeof e)return a.util.copy(e);if(!e.match(/^http/)){e=((t&&void 0!==t.sslEnabled?t.sslEnabled:a.config.sslEnabled)?"https":"http")+"://"+e}a.util.update(this,a.util.urlParse(e)),this.port?this.port=parseInt(this.port,10):this.port="https:"===this.protocol?443:80}}),a.HttpRequest=i({constructor:function(e,t){e=new a.Endpoint(e),this.method="POST",this.path=e.path||"/",this.headers={},this.body="",this.endpoint=e,this.region=t,this._userAgent="",this.setUserAgent()},setUserAgent:function(){this._userAgent=this.headers[this.getUserAgentHeaderName()]=a.util.userAgent()},getUserAgentHeaderName:function(){return(a.util.isBrowser()?"X-Amz-":"")+"User-Agent"},appendToUserAgent:function(e){"string"==typeof e&&e&&(this._userAgent+=" "+e),this.headers[this.getUserAgentHeaderName()]=this._userAgent},getUserAgent:function(){return this._userAgent},pathname:function(){return this.path.split("?",1)[0]},search:function(){var e=this.path.split("?",2)[1];return e?(e=a.util.queryStringParse(e),a.util.queryParamsToString(e)):""},updateEndpoint:function(e){var t=new a.Endpoint(e);this.endpoint=t,this.path=t.path||"/",this.headers.Host&&(this.headers.Host=t.host)}}),a.HttpResponse=i({constructor:function(){this.statusCode=void 0,this.headers={},this.body=void 0,this.streaming=!1,this.stream=null},createUnbufferedStream:function(){return this.streaming=!0,this.stream}}),a.HttpClient=i({}),a.HttpClient.getInstance=function(){return void 0===this.singleton&&(this.singleton=new this),this.singleton}},{"./core":350}],373:[function(e,t,r){var a=e("../core"),i=e("events").EventEmitter;e("../http"),a.XHRClient=a.util.inherit({handleRequest:function(e,t,r,s){var o=this,n=e.endpoint,u=new i,p=n.protocol+"//"+n.hostname;80!==n.port&&443!==n.port&&(p+=":"+n.port),p+=e.path;var m=new XMLHttpRequest,c=!1;e.stream=m,m.addEventListener("readystatechange",function(){try{if(0===m.status)return}catch(e){return}this.readyState>=this.HEADERS_RECEIVED&&!c&&(u.statusCode=m.status,u.headers=o.parseHeaders(m.getAllResponseHeaders()),u.emit("headers",u.statusCode,u.headers,m.statusText),c=!0),this.readyState===this.DONE&&o.finishRequest(m,u)},!1),m.upload.addEventListener("progress",function(e){u.emit("sendProgress",e)}),m.addEventListener("progress",function(e){u.emit("receiveProgress",e)},!1),m.addEventListener("timeout",function(){s(a.util.error(new Error("Timeout"),{code:"TimeoutError"}))},!1),m.addEventListener("error",function(){s(a.util.error(new Error("Network Failure"),{code:"NetworkingError"}))},!1),m.addEventListener("abort",function(){s(a.util.error(new Error("Request aborted"),{code:"RequestAbortedError"}))},!1),r(u),m.open(e.method,p,!1!==t.xhrAsync),a.util.each(e.headers,function(e,t){"Content-Length"!==e&&"User-Agent"!==e&&"Host"!==e&&m.setRequestHeader(e,t)}),t.timeout&&!1!==t.xhrAsync&&(m.timeout=t.timeout),t.xhrWithCredentials&&(m.withCredentials=!0);try{m.responseType="arraybuffer"}catch(e){}try{e.body?m.send(e.body):m.send()}catch(t){if(!e.body||"object"!=typeof e.body.buffer)throw t;m.send(e.body.buffer)}return u},parseHeaders:function(e){var t={};return a.util.arrayEach(e.split(/\r?\n/),function(e){var r=e.split(":",1)[0],a=e.substring(r.length+2);r.length>0&&(t[r.toLowerCase()]=a)}),t},finishRequest:function(e,t){var r;if("arraybuffer"===e.responseType&&e.response){var i=e.response;r=new a.util.Buffer(i.byteLength);for(var s=new Uint8Array(i),o=0;o-1?t||"":t,this.isJsonValue?JSON.parse(t):t&&"function"==typeof t.toString?t.toString():t},this.toWireFormat=function(e){return this.isJsonValue?JSON.stringify(e):e}}function l(){s.apply(this,arguments),this.toType=function(e){return null===e||void 0===e?null:parseFloat(e)},this.toWireFormat=this.toType}function d(){s.apply(this,arguments),this.toType=function(e){return null===e||void 0===e?null:parseInt(e,10)},this.toWireFormat=this.toType}function y(){s.apply(this,arguments),this.toType=function(e){var t=h.base64.decode(e);if(this.isSensitive&&h.isNode()&&"function"==typeof h.Buffer.alloc){ var r=h.Buffer.alloc(t.length,t);t.fill(0),t=r}return t},this.toWireFormat=h.base64.encode}function b(){y.apply(this,arguments)}function S(){s.apply(this,arguments),this.toType=function(e){return"boolean"==typeof e?e:null===e||void 0===e?null:"true"===e}}var g=e("./collection"),h=e("../util");s.normalizedTypes={character:"string",double:"float",long:"integer",short:"integer",biginteger:"integer",bigdecimal:"float",blob:"binary"},s.types={structure:n,list:u,map:p,boolean:S,timestamp:m,float:l,integer:d,string:c,base64:b,binary:y},s.resolve=function(e,t){if(e.shape){var r=t.api.shapes[e.shape];if(!r)throw new Error("Cannot find shape reference: "+e.shape);return r}return null},s.create=function(e,t,r){if(e.isShape)return e;var a=s.resolve(e,t);if(a){var i=Object.keys(e);t.documentation||(i=i.filter(function(e){return!e.match(/documentation/)}));var o=function(){a.constructor.call(this,e,t,r)};return o.prototype=a,new o}e.type||(e.members?e.type="structure":e.member?e.type="list":e.key?e.type="map":e.type="string");var n=e.type;if(s.normalizedTypes[e.type]&&(e.type=s.normalizedTypes[e.type]),s.types[e.type])return new s.types[e.type](e,t,r);throw new Error("Unrecognized shape type: "+n)},s.shapes={StructureShape:n,ListShape:u,MapShape:p,StringShape:c,BooleanShape:S,Base64Shape:b},t.exports=s},{"../util":428,"./collection":378}],383:[function(e,t,r){var a=e("./core");a.ParamValidator=a.util.inherit({constructor:function(e){!0!==e&&void 0!==e||(e={min:!0}),this.validation=e},validate:function(e,t,r){if(this.errors=[],this.validateMember(e,t||{},r||"params"),this.errors.length>1){var i=this.errors.join("\n* ");throw i="There were "+this.errors.length+" validation errors:\n* "+i,a.util.error(new Error(i),{code:"MultipleValidationErrors",errors:this.errors})}if(1===this.errors.length)throw this.errors[0];return!0},fail:function(e,t){this.errors.push(a.util.error(new Error(t),{code:e}))},validateStructure:function(e,t,r){if(e.isDocument)return!0;this.validateType(t,r,["object"],"structure");for(var a,i=0;e.required&&i= 1, but found "'+t+'" for '+r)},validatePattern:function(e,t,r){this.validation.pattern&&void 0!==e.pattern&&(new RegExp(e.pattern).test(t)||this.fail("PatternMatchError",'Provided value "'+t+'" does not match regex pattern /'+e.pattern+"/ for "+r))},validateRange:function(e,t,r,a){this.validation.min&&void 0!==e.min&&t= "+e.min+", but found "+t+" for "+r),this.validation.max&&void 0!==e.max&&t>e.max&&this.fail("MaxRangeError","Expected "+a+" <= "+e.max+", but found "+t+" for "+r)},validateEnum:function(e,t,r){this.validation.enum&&void 0!==e.enum&&-1===e.enum.indexOf(t)&&this.fail("EnumError","Found string value of "+t+", but expected "+e.enum.join("|")+" for "+r)},validateType:function(e,t,r,i){if(null===e||void 0===e)return!1;for(var s=!1,o=0;o63)throw u.error(new Error,{code:"ValidationError",message:"Hostname label length should be between 1 to 63 characters, inclusive."});if(!r.test(e))throw p.util.error(new Error,{code:"ValidationError",message:e+" is not hostname compatible."})})}var u=e("../util"),p=e("../core");t.exports={populateHostPrefix:a}},{"../core":350,"../util":428}],386:[function(e,t,r){function a(e){var t=e.httpRequest,r=e.service.api,a=r.targetPrefix+"."+r.operations[e.operation].name,i=r.jsonVersion||"1.0",s=r.operations[e.operation].input,o=new n;1===i&&(i="1.0"),r.awsQueryCompatible&&(t.params||(t.params={}),Object.assign(t.params,e.params)),t.body=o.build(e.params||{},s),t.headers["Content-Type"]="application/x-amz-json-"+i,t.headers["X-Amz-Target"]=a,p(e)}function i(e){var t={},r=e.httpResponse;if(t.code=r.headers["x-amzn-errortype"]||"UnknownError","string"==typeof t.code&&(t.code=t.code.split(":")[0]),r.body.length>0)try{var a=JSON.parse(r.body.toString()),i=a.__type||a.code||a.Code;i&&(t.code=i.split("#").pop()),"RequestEntityTooLarge"===t.code?t.message="Request body must be less than 1 MB":t.message=a.message||a.Message||null;for(var s in a||{})"code"!==s&&"message"!==s&&(t["["+s+"]"]="See error."+s+" for details.",Object.defineProperty(t,s,{value:a[s],enumerable:!1,writable:!0}))}catch(a){t.statusCode=r.statusCode,t.message=r.statusMessage}else t.statusCode=r.statusCode,t.message=r.statusCode.toString();e.error=o.error(new Error,t)}function s(e){var t=e.httpResponse.body.toString()||"{}";if(!1===e.request.service.config.convertResponseTypes)e.data=JSON.parse(t);else{var r=e.request.service.api.operations[e.request.operation],a=r.output||{},i=new u;e.data=i.parse(t,a)}}var o=e("../util"),n=e("../json/builder"),u=e("../json/parser"),p=e("./helpers").populateHostPrefix;t.exports={buildRequest:a,extractError:i,extractData:s}},{"../json/builder":374,"../json/parser":375,"../util":428,"./helpers":385}],387:[function(e,t,r){function a(e){var t=e.service.api.operations[e.operation],r=e.httpRequest;r.headers["Content-Type"]="application/x-www-form-urlencoded; charset=utf-8",r.params={Version:e.service.api.apiVersion,Action:t.name},(new u).serialize(e.params,t.input,function(e,t){r.params[e]=t}),r.body=n.queryParamsToString(r.params),m(e)}function i(e){var t,r=e.httpResponse.body.toString();if(r.match("=0?"&":"?";var n=[];m.arrayEach(Object.keys(s).sort(),function(e){Array.isArray(s[e])||(s[e]=[s[e]]);for(var t=0;t=0&&delete e.httpRequest.headers["Content-Length"]}function i(e){var t=new l,r=e.service.api.operations[e.operation].input;if(r.payload){var a={},i=r.members[r.payload];a=e.params[r.payload],"structure"===i.type?(e.httpRequest.body=t.build(a||{},i),s(e)):void 0!==a&&(e.httpRequest.body=a,("binary"===i.type||i.isStreaming)&&s(e,!0))}else e.httpRequest.body=t.build(e.params,r),s(e)}function s(e,t){if(!e.httpRequest.headers["Content-Type"]){var r=t?"binary/octet-stream":"application/json";e.httpRequest.headers["Content-Type"]=r}}function o(e){m.buildRequest(e),y.indexOf(e.httpRequest.method)<0&&i(e)}function n(e){c.extractError(e)}function u(e){m.extractData(e);var t,r=e.request,a=r.service.api.operations[r.operation],i=r.service.api.operations[r.operation].output||{};a.hasEventOutput;if(i.payload){var s=i.members[i.payload],o=e.httpResponse.body;if(s.isEventStream)t=new d,e.data[payload]=p.createEventStream(2===AWS.HttpClient.streamsApiVersion?e.httpResponse.stream:o,t,s);else if("structure"===s.type||"list"===s.type){var t=new d;e.data[i.payload]=t.parse(o,s)}else"binary"===s.type||s.isStreaming?e.data[i.payload]=o:e.data[i.payload]=s.toType(o)}else{var n=e.data;c.extractData(e),e.data=p.merge(n,e.data)}}var p=e("../util"),m=e("./rest"),c=e("./json"),l=e("../json/builder"),d=e("../json/parser"),y=["GET","HEAD","DELETE"];t.exports={buildRequest:o,extractError:n,extractData:u,unsetContentLength:a}},{"../json/builder":374,"../json/parser":375,"../util":428,"./json":386,"./rest":388}],390:[function(e,t,r){function a(e){var t=e.service.api.operations[e.operation].input,r=new n.XML.Builder,a=e.params,i=t.payload;if(i){var s=t.members[i];if(void 0===(a=a[i]))return;if("structure"===s.type){var o=s.name;e.httpRequest.body=r.toXML(a,s,o,!0)}else e.httpRequest.body=a}else e.httpRequest.body=r.toXML(a,t,t.name||t.shape||u.string.upperFirst(e.operation)+"Request")}function i(e){p.buildRequest(e),["GET","HEAD"].indexOf(e.httpRequest.method)<0&&a(e)}function s(e){p.extractError(e);var t;try{t=(new n.XML.Parser).parse(e.httpResponse.body.toString())}catch(r){t={Code:e.httpResponse.statusCode,Message:e.httpResponse.statusMessage}}t.Errors&&(t=t.Errors),t.Error&&(t=t.Error),t.Code?e.error=u.error(new Error,{code:t.Code,message:t.Message}):e.error=u.error(new Error,{code:e.httpResponse.statusCode,message:null})}function o(e){p.extractData(e);var t,r=e.request,a=e.httpResponse.body,i=r.service.api.operations[r.operation],s=i.output,o=(i.hasEventOutput,s.payload);if(o){var m=s.members[o];m.isEventStream?(t=new n.XML.Parser,e.data[o]=u.createEventStream(2===n.HttpClient.streamsApiVersion?e.httpResponse.stream:e.httpResponse.body,t,m)):"structure"===m.type?(t=new n.XML.Parser,e.data[o]=t.parse(a.toString(),m)):"binary"===m.type||m.isStreaming?e.data[o]=a:e.data[o]=m.toType(a)}else if(a.length>0){t=new n.XML.Parser;var c=t.parse(a.toString(),s);u.update(e.data,c)}}var n=e("../core"),u=e("../util"),p=e("./rest");t.exports={buildRequest:i,extractError:s,extractData:o}},{"../core":350,"../util":428,"./rest":388}],391:[function(e,t,r){function a(){}function i(e){return e.isQueryName||"ec2"!==e.api.protocol?e.name:e.name[0].toUpperCase()+e.name.substr(1)}function s(e,t,r,a){p.each(r.members,function(r,s){var o=t[r];if(null!==o&&void 0!==o){var n=i(s);n=e?e+"."+n:n,u(n,o,s,a)}})}function o(e,t,r,a){var i=1;p.each(t,function(t,s){var o=r.flattened?".":".entry.",n=o+i+++".",p=n+(r.key.name||"key"),m=n+(r.value.name||"value");u(e+p,t,r.key,a),u(e+m,s,r.value,a)})}function n(e,t,r,a){var s=r.member||{};if(0===t.length)return void a.call(this,e,null);p.arrayEach(t,function(t,o){var n="."+(o+1);if("ec2"===r.api.protocol)n+="";else if(r.flattened){if(s.name){var p=e.split(".");p.pop(),p.push(i(s)),e=p.join(".")}}else n="."+(s.name?s.name:"member")+n;u(e+n,t,s,a)})}function u(e,t,r,a){null!==t&&void 0!==t&&("structure"===r.type?s(e,t,r,a):"list"===r.type?n(e,t,r,a):"map"===r.type?o(e,t,r,a):a(e,r.toWireFormat(t).toString()))}var p=e("../util");a.prototype.serialize=function(e,t,r){s("",e,t,r)},t.exports=a},{"../util":428}],392:[function(e,t,r){var a=e("../core"),i=null,s={signatureVersion:"v4",signingName:"rds-db",operations:{}},o={region:"string",hostname:"string",port:"number",username:"string"};a.RDS.Signer=a.util.inherit({constructor:function(e){this.options=e||{}},convertUrlToAuthToken:function(e){if(0===e.indexOf("https://"))return e.substring("https://".length)},getAuthToken:function(e,t){"function"==typeof e&&void 0===t&&(t=e,e={});var r=this,o="function"==typeof t;e=a.util.merge(this.options,e);var n=this.validateAuthTokenOptions(e);if(!0!==n){if(o)return t(n,null);throw n}var u={region:e.region,endpoint:new a.Endpoint(e.hostname+":"+e.port),paramValidation:!1,signatureVersion:"v4"};e.credentials&&(u.credentials=e.credentials),i=new a.Service(u),i.api=s;var p=i.makeRequest();if(this.modifyRequestForAuthToken(p,e),!o){var m=p.presign(900);return this.convertUrlToAuthToken(m)}p.presign(900,function(e,a){a&&(a=r.convertUrlToAuthToken(a)),t(e,a)})},modifyRequestForAuthToken:function(e,t){e.on("build",e.buildAsGet),e.httpRequest.body=a.util.queryParamsToString({Action:"connect",DBUser:t.username})},validateAuthTokenOptions:function(e){var t="";e=e||{};for(var r in o)Object.prototype.hasOwnProperty.call(o,r)&&typeof e[r]!==o[r]&&(t+="option '"+r+"' should have been type '"+o[r]+"', was '"+typeof e[r]+"'.\n");return!t.length||a.util.error(new Error,{code:"InvalidParameter",message:t})}})},{"../core":350}],393:[function(e,t,r){t.exports={now:function(){return"undefined"!=typeof performance&&"function"==typeof performance.now?performance.now():Date.now()}}},{}],394:[function(e,t,r){function a(e){return"string"==typeof e&&(e.startsWith("fips-")||e.endsWith("-fips"))}function i(e){return"string"==typeof e&&["aws-global","aws-us-gov-global"].includes(e)}function s(e){return["fips-aws-global","aws-fips","aws-global"].includes(e)?"us-east-1":["fips-aws-us-gov-global","aws-us-gov-global"].includes(e)?"us-gov-west-1":e.replace(/fips-(dkr-|prod-)?|-fips/,"")}t.exports={isFipsRegion:a,isGlobalRegion:i,getRealRegion:s}},{}],395:[function(e,t,r){function a(e){if(!e)return null;var t=e.split("-");return t.length<3?null:t.slice(0,t.length-2).join("-")+"-*"}function i(e){var t=e.config.region,r=a(t),i=e.api.endpointPrefix;return[[t,i],[r,i],[t,"*"],[r,"*"],["*",i],[t,"internal-*"],["*","*"]].map(function(e){return e[0]&&e[1]?e.join("/"):null})}function s(e,t){u.each(t,function(t,r){"globalEndpoint"!==t&&(void 0!==e.config[t]&&null!==e.config[t]||(e.config[t]=r))})}function o(e){for(var t=i(e),r=e.config.useFipsEndpoint,a=e.config.useDualstackEndpoint,o=0;o=0){u=!0;var p=0}var m=function(){u&&p!==n?i.emit("error",a.util.error(new Error("Stream content length mismatch. Received "+p+" of "+n+" bytes."),{code:"StreamContentLengthMismatch"})):2===a.HttpClient.streamsApiVersion?i.end():i.emit("end")},c=o.httpResponse.createUnbufferedStream();if(2===a.HttpClient.streamsApiVersion)if(u){var l=new e.PassThrough;l._write=function(t){return t&&t.length&&(p+=t.length),e.PassThrough.prototype._write.apply(this,arguments)},l.on("end",m),i.on("error",function(e){u=!1,c.unpipe(l),l.emit("end"),l.end()}),c.pipe(l).pipe(i,{end:!1})}else c.pipe(i);else u&&c.on("data",function(e){e&&e.length&&(p+=e.length)}),c.on("data",function(e){i.emit("data",e)}),c.on("end",m);c.on("error",function(e){u=!1,i.emit("error",e)})}}),i},emitEvent:function(e,t,r){"function"==typeof t&&(r=t,t=null),r||(r=function(){}),t||(t=this.eventParameters(e,this.response)),a.SequentialExecutor.prototype.emit.call(this,e,t,function(e){e&&(this.response.error=e),r.call(this,e)})},eventParameters:function(e){switch(e){case"restart":case"validate":case"sign":case"build":case"afterValidate":case"afterBuild":return[this];case"error":return[this.response.error,this.response];default:return[this.response]}},presign:function(e,t){return t||"function"!=typeof e||(t=e,e=null),(new a.Signers.Presign).sign(this.toGet(),e,t)},isPresigned:function(){return Object.prototype.hasOwnProperty.call(this.httpRequest.headers,"presigned-expires")},toUnauthenticated:function(){return this._unAuthenticated=!0,this.removeListener("validate",a.EventListeners.Core.VALIDATE_CREDENTIALS),this.removeListener("sign",a.EventListeners.Core.SIGN),this},toGet:function(){return"query"!==this.service.api.protocol&&"ec2"!==this.service.api.protocol||(this.removeListener("build",this.buildAsGet),this.addListener("build",this.buildAsGet)),this},buildAsGet:function(e){e.httpRequest.method="GET",e.httpRequest.path=e.service.endpoint.path+"?"+e.httpRequest.body,e.httpRequest.body="",delete e.httpRequest.headers["Content-Length"],delete e.httpRequest.headers["Content-Type"]},haltHandlersOnError:function(){this._haltHandlersOnError=!0}}),a.Request.addPromisesToClass=function(e){this.prototype.promise=function(){var t=this;return this.httpRequest.appendToUserAgent("promise"),new e(function(e,r){t.on("complete",function(t){t.error?r(t.error):e(Object.defineProperty(t.data||{},"$response",{value:t}))}),t.runTo()})}},a.Request.deletePromisesFromClass=function(){delete this.prototype.promise},a.util.addPromises(a.Request),a.util.mixin(a.Request,a.SequentialExecutor)}).call(this)}).call(this,e("_process"))},{"./core":350,"./state_machine":427,_process:445,jmespath:444}],398:[function(e,t,r){function a(e){var t=e.request._waiter,r=t.config.acceptors,a=!1,i="retry";r.forEach(function(r){if(!a){var s=t.matchers[r.matcher];s&&s(e,r.expected,r.argument)&&(a=!0,i=r.state)}}),!a&&e.error&&(i="failure"),"success"===i?t.setSuccess(e):t.setError(e,"retry"===i)}var i=e("./core"),s=i.util.inherit,o=e("jmespath");i.ResourceWaiter=s({constructor:function(e,t){this.service=e,this.state=t,this.loadWaiterConfig(this.state)},service:null,state:null,config:null,matchers:{path:function(e,t,r){try{var a=o.search(e.data,r)}catch(e){return!1}return o.strictDeepEqual(a,t)},pathAll:function(e,t,r){try{var a=o.search(e.data,r)}catch(e){return!1}Array.isArray(a)||(a=[a]);var i=a.length;if(!i)return!1;for(var s=0;s=1&&t.doneParts===t.numParts&&t.finishMultiPart()}))}r&&t.fillQueue.call(t)},abort:function(){var e=this;!0===e.isDoneChunking&&1===e.totalPartNumbers&&e.singlePart?e.singlePart.abort():e.cleanup(a.util.error(new Error("Request aborted by user"),{code:"RequestAbortedError",retryable:!1}))},validateBody:function(){var e=this;if(e.body=e.service.config.params.Body,"string"==typeof e.body)e.body=a.util.buffer.toBuffer(e.body);else if(!e.body)throw new Error("params.Body is required");e.sliceFn=a.util.arraySliceFn(e.body)},bindServiceObject:function(e){e=e||{};var t=this;if(t.service){var r=t.service,i=a.util.copy(r.config);i.signatureVersion=r.getSignatureVersion(),t.service=new r.constructor.__super__(i),t.service.config.params=a.util.merge(t.service.config.params||{},e),Object.defineProperty(t.service,"_originalConfig",{get:function(){return r._originalConfig},enumerable:!1,configurable:!0})}else t.service=new a.S3({params:e})},adjustTotalBytes:function(){var e=this;try{e.totalBytes=i(e.body)}catch(e){}if(e.totalBytes){var t=Math.ceil(e.totalBytes/e.maxTotalParts);t>e.partSize&&(e.partSize=t)}else e.totalBytes=void 0},isDoneChunking:!1,partPos:0,totalChunkedBytes:0,totalUploadedBytes:0,totalBytes:void 0,numParts:0,totalPartNumbers:0,activeParts:0,doneParts:0,parts:null,completeInfo:null,failed:!1,multipartReq:null,partBuffers:null,partBufferLength:0,fillBuffer:function(){var e=this,t=i(e.body);if(0===t)return e.isDoneChunking=!0,e.numParts=1,void e.nextChunk(e.body);for(;e.activeParts=e.queueSize)){var t=e.body.read(e.partSize-e.partBufferLength)||e.body.read();if(t&&(e.partBuffers.push(t),e.partBufferLength+=t.length,e.totalChunkedBytes+=t.length),e.partBufferLength>=e.partSize){var r=1===e.partBuffers.length?e.partBuffers[0]:s.concat(e.partBuffers);if(e.partBuffers=[],e.partBufferLength=0,r.length>e.partSize){var a=r.slice(e.partSize);e.partBuffers.push(a),e.partBufferLength+=a.length,r=r.slice(0,e.partSize)}e.nextChunk(r)}e.isDoneChunking&&!e.isDoneSending&&(r=1===e.partBuffers.length?e.partBuffers[0]:s.concat(e.partBuffers),e.partBuffers=[],e.partBufferLength=0,e.totalBytes=e.totalChunkedBytes,e.isDoneSending=!0,(0===e.numParts||r.length>0)&&(e.numParts++,e.nextChunk(r))),e.body.read(0)}},nextChunk:function(e){var t=this;if(t.failed)return null;var r=++t.totalPartNumbers;if(t.isDoneChunking&&1===r){var i={Body:e};this.tags&&(i.Tagging=this.getTaggingHeader());var s=t.service.putObject(i);return s._managedUpload=t,s.on("httpUploadProgress",t.progress).send(t.finishSinglePart),t.singlePart=s,null}if(t.service.config.params.ContentMD5){var o=a.util.error(new Error("The Content-MD5 you specified is invalid for multi-part uploads."),{code:"InvalidDigest",retryable:!1});return t.cleanup(o),null}if(t.completeInfo[r]&&null!==t.completeInfo[r].ETag)return null;t.activeParts++,t.service.config.params.UploadId?t.uploadPart(e,r):t.multipartReq?t.queueChunks(e,r):(t.multipartReq=t.service.createMultipartUpload(),t.multipartReq.on("success",function(e){t.service.config.params.UploadId=e.data.UploadId,t.multipartReq=null}),t.queueChunks(e,r),t.multipartReq.on("error",function(e){t.cleanup(e)}),t.multipartReq.send())},getTaggingHeader:function(){for(var e=[],t=0;t-1&&r.splice(i,1)}return this},removeAllListeners:function(e){return e?delete this._events[e]:this._events={},this},emit:function(e,t,r){r||(r=function(){});var a=this.listeners(e),i=a.length;return this.callListeners(a,t,r),i>0},callListeners:function(e,t,r,i){function s(i){if(i&&(n=a.util.error(n||new Error,i),o._haltHandlersOnError))return r.call(o,n);o.callListeners(e,t,r,n)}for(var o=this,n=i||null;e.length>0;){var u=e.shift();if(u._isAsync)return void u.apply(o,t.concat([s]));try{u.apply(o,t)}catch(e){n=a.util.error(n||new Error,e)}if(n&&o._haltHandlersOnError)return void r.call(o,n)}r.call(o,n)},addListeners:function(e){var t=this;return e._events&&(e=e._events),a.util.each(e,function(e,r){"function"==typeof r&&(r=[r]),a.util.arrayEach(r,function(r){t.on(e,r)})}),t},addNamedListener:function(e,t,r,a){return this[e]=r,this.addListener(t,r,a),this},addNamedAsyncListener:function(e,t,r,a){return r._isAsync=!0,this.addNamedListener(e,t,r,a)},addNamedListeners:function(e){var t=this;return e(function(){t.addNamedListener.apply(t,arguments)},function(){t.addNamedAsyncListener.apply(t,arguments)}),this}}),a.SequentialExecutor.prototype.addListener=a.SequentialExecutor.prototype.on,t.exports=a.SequentialExecutor},{"./core":350}],402:[function(e,t,r){(function(r){(function(){var a=e("./core"),i=e("./model/api"),s=e("./region_config"),o=a.util.inherit,n=0,u=e("./region/utils");a.Service=o({constructor:function(e){if(!this.loadServiceClass)throw a.util.error(new Error,"Service must be constructed with `new' operator");if(e){if(e.region){var t=e.region;u.isFipsRegion(t)&&(e.region=u.getRealRegion(t),e.useFipsEndpoint=!0),u.isGlobalRegion(t)&&(e.region=u.getRealRegion(t))}"boolean"==typeof e.useDualstack&&"boolean"!=typeof e.useDualstackEndpoint&&(e.useDualstackEndpoint=e.useDualstack)}var r=this.loadServiceClass(e||{});if(r){var i=a.util.copy(e),s=new r(e);return Object.defineProperty(s,"_originalConfig",{get:function(){return i},enumerable:!1,configurable:!0}),s._clientId=++n,s}this.initialize(e)},initialize:function(e){var t=a.config[this.serviceIdentifier];if(this.config=new a.Config(a.config),t&&this.config.update(t,!0),e&&this.config.update(e,!0),this.validateService(),this.config.endpoint||s.configureEndpoint(this),this.config.endpoint=this.endpointFromTemplate(this.config.endpoint),this.setEndpoint(this.config.endpoint),a.SequentialExecutor.call(this),a.Service.addDefaultMonitoringListeners(this),(this.config.clientSideMonitoring||a.Service._clientSideMonitoring)&&this.publisher){var i=this.publisher;this.addNamedListener("PUBLISH_API_CALL","apiCall",function(e){r.nextTick(function(){i.eventHandler(e)})}),this.addNamedListener("PUBLISH_API_ATTEMPT","apiCallAttempt",function(e){r.nextTick(function(){i.eventHandler(e)})})}},validateService:function(){},loadServiceClass:function(e){var t=e;if(a.util.isEmpty(this.api)){if(t.apiConfig)return a.Service.defineServiceApi(this.constructor,t.apiConfig);if(this.constructor.services){t=new a.Config(a.config),t.update(e,!0);var r=t.apiVersions[this.constructor.serviceIdentifier];return r=r||t.apiVersion,this.getLatestServiceClass(r)}return null}return null},getLatestServiceClass:function(e){return e=this.getLatestServiceVersion(e),null===this.constructor.services[e]&&a.Service.defineServiceApi(this.constructor,e),this.constructor.services[e]},getLatestServiceVersion:function(e){if(!this.constructor.services||0===this.constructor.services.length)throw new Error("No services defined on "+this.constructor.serviceIdentifier);if(e?a.util.isType(e,Date)&&(e=a.util.date.iso8601(e).split("T")[0]):e="latest",Object.hasOwnProperty(this.constructor.services,e))return e;for(var t=Object.keys(this.constructor.services).sort(),r=null,i=t.length-1;i>=0;i--)if("*"!==t[i][t[i].length-1]&&(r=t[i]),t[i].substr(0,10)<=e)return r;throw new Error("Could not find "+this.constructor.serviceIdentifier+" API to satisfy version constraint `"+e+"'")},api:{},defaultRetryCount:3,customizeRequests:function(e){if(e){if("function"!=typeof e)throw new Error("Invalid callback type '"+typeof e+"' provided in customizeRequests");this.customRequestHandler=e}else this.customRequestHandler=null},makeRequest:function(e,t,r){if("function"==typeof t&&(r=t,t=null),t=t||{},this.config.params){var i=this.api.operations[e];i&&(t=a.util.copy(t),a.util.each(this.config.params,function(e,r){i.input.members[e]&&(void 0!==t[e]&&null!==t[e]||(t[e]=r))}))}var s=new a.Request(this,e,t);return this.addAllRequestListeners(s),this.attachMonitoringEmitter(s),r&&s.send(r),s},makeUnauthenticatedRequest:function(e,t,r){"function"==typeof t&&(r=t,t={});var a=this.makeRequest(e,t).toUnauthenticated();return r?a.send(r):a},waitFor:function(e,t,r){return new a.ResourceWaiter(this,e).wait(t,r)},addAllRequestListeners:function(e){for(var t=[a.events,a.EventListeners.Core,this.serviceInterface(),a.EventListeners.CorePost],r=0;r299?(i.code&&(r.FinalAwsException=i.code),i.message&&(r.FinalAwsExceptionMessage=i.message)):((i.code||i.name)&&(r.FinalSdkException=i.code||i.name),i.message&&(r.FinalSdkExceptionMessage=i.message))}return r},apiAttemptEvent:function(e){var t=e.service.api.operations[e.operation],r={Type:"ApiCallAttempt",Api:t?t.name:e.operation,Version:1,Service:e.service.api.serviceId||e.service.api.endpointPrefix,Fqdn:e.httpRequest.endpoint.hostname,UserAgent:e.httpRequest.getUserAgent()},a=e.response;return a.httpResponse.statusCode&&(r.HttpStatusCode=a.httpResponse.statusCode),!e._unAuthenticated&&e.service.config.credentials&&e.service.config.credentials.accessKeyId&&(r.AccessKey=e.service.config.credentials.accessKeyId),a.httpResponse.headers?(e.httpRequest.headers["x-amz-security-token"]&&(r.SessionToken=e.httpRequest.headers["x-amz-security-token"]),a.httpResponse.headers["x-amzn-requestid"]&&(r.XAmznRequestId=a.httpResponse.headers["x-amzn-requestid"]),a.httpResponse.headers["x-amz-request-id"]&&(r.XAmzRequestId=a.httpResponse.headers["x-amz-request-id"]),a.httpResponse.headers["x-amz-id-2"]&&(r.XAmzId2=a.httpResponse.headers["x-amz-id-2"]),r):r},attemptFailEvent:function(e){var t=this.apiAttemptEvent(e),r=e.response,a=r.error;return r.httpResponse.statusCode>299?(a.code&&(t.AwsException=a.code),a.message&&(t.AwsExceptionMessage=a.message)):((a.code||a.name)&&(t.SdkException=a.code||a.name),a.message&&(t.SdkExceptionMessage=a.message)),t},attachMonitoringEmitter:function(e){var t,r,i,s,o,n,u=0,p=this;e.on("validate",function(){s=a.util.realClock.now(),n=Date.now()},!0),e.on("sign",function(){r=a.util.realClock.now(),t=Date.now(),o=e.httpRequest.region,u++},!0),e.on("validateResponse",function(){i=Math.round(a.util.realClock.now()-r)}),e.addNamedListener("API_CALL_ATTEMPT","success",function(){var r=p.apiAttemptEvent(e);r.Timestamp=t,r.AttemptLatency=i>=0?i:0,r.Region=o,p.emit("apiCallAttempt",[r])}),e.addNamedListener("API_CALL_ATTEMPT_RETRY","retry",function(){var s=p.attemptFailEvent(e);s.Timestamp=t,i=i||Math.round(a.util.realClock.now()-r),s.AttemptLatency=i>=0?i:0,s.Region=o,p.emit("apiCallAttempt",[s])}),e.addNamedListener("API_CALL","complete",function(){var t=p.apiCallEvent(e);if(t.AttemptCount=u,!(t.AttemptCount<=0)){t.Timestamp=n;var r=Math.round(a.util.realClock.now()-s);t.Latency=r>=0?r:0;var i=e.response;i.error&&i.error.retryable&&"number"==typeof i.retryCount&&"number"==typeof i.maxRetries&&i.retryCount>=i.maxRetries&&(t.MaxRetriesExceeded=1),p.emit("apiCall",[t])}})},setupRequestListeners:function(e){},getSigningName:function(){return this.api.signingName||this.api.endpointPrefix},getSignerClass:function(e){var t,r=null,i="";if(e){r=(e.service.api.operations||{})[e.operation]||null,i=r?r.authtype:""}return t=this.config.signatureVersion?this.config.signatureVersion:"v4"===i||"v4-unsigned-body"===i?"v4":"bearer"===i?"bearer":this.api.signatureVersion,a.Signers.RequestSigner.getVersion(t)},serviceInterface:function(){switch(this.api.protocol){case"ec2":case"query":return a.EventListeners.Query;case"json":return a.EventListeners.Json;case"rest-json":return a.EventListeners.RestJson;case"rest-xml":return a.EventListeners.RestXml}if(this.api.protocol)throw new Error("Invalid service `protocol' "+this.api.protocol+" in API config")},successfulResponse:function(e){return e.httpResponse.statusCode<300},numRetries:function(){return void 0!==this.config.maxRetries?this.config.maxRetries:this.defaultRetryCount},retryDelays:function(e,t){return a.util.calculateRetryDelay(e,this.config.retryDelayOptions,t)},retryableError:function(e){return!!this.timeoutError(e)||(!!this.networkingError(e)||(!!this.expiredCredentialsError(e)||(!!this.throttledError(e)||e.statusCode>=500)))},networkingError:function(e){return"NetworkingError"===e.code},timeoutError:function(e){return"TimeoutError"===e.code},expiredCredentialsError:function(e){return"ExpiredTokenException"===e.code},clockSkewError:function(e){switch(e.code){case"RequestTimeTooSkewed":case"RequestExpired":case"InvalidSignatureException":case"SignatureDoesNotMatch":case"AuthFailure":case"RequestInTheFuture":return!0;default:return!1}},getSkewCorrectedDate:function(){return new Date(Date.now()+this.config.systemClockOffset)},applyClockOffset:function(e){e&&(this.config.systemClockOffset=e-Date.now())},isClockSkewed:function(e){if(e)return Math.abs(this.getSkewCorrectedDate().getTime()-e)>=3e5},throttledError:function(e){if(429===e.statusCode)return!0;switch(e.code){case"ProvisionedThroughputExceededException":case"Throttling":case"ThrottlingException":case"RequestLimitExceeded":case"RequestThrottled":case"RequestThrottledException":case"TooManyRequestsException":case"TransactionInProgressException":case"EC2ThrottledException":return!0;default:return!1}},endpointFromTemplate:function(e){if("string"!=typeof e)return e;var t=e;return t=t.replace(/\{service\}/g,this.api.endpointPrefix),t=t.replace(/\{region\}/g,this.config.region),t=t.replace(/\{scheme\}/g,this.config.sslEnabled?"https":"http")},setEndpoint:function(e){this.endpoint=new a.Endpoint(e,this.config)},paginationConfig:function(e,t){var r=this.api.operations[e].paginator;if(!r){if(t){var i=new Error;throw a.util.error(i,"No pagination configuration for "+e)}return null}return r}}),a.util.update(a.Service,{defineMethods:function(e){a.util.each(e.prototype.api.operations,function(t){if(!e.prototype[t]){"none"===e.prototype.api.operations[t].authtype?e.prototype[t]=function(e,r){return this.makeUnauthenticatedRequest(t,e,r)}:e.prototype[t]=function(e,r){return this.makeRequest(t,e,r)}}})},defineService:function(e,t,r){a.Service._serviceMap[e]=!0,Array.isArray(t)||(r=t,t=[]);var i=o(a.Service,r||{});if("string"==typeof e){a.Service.addVersions(i,t);var s=i.serviceIdentifier||e;i.serviceIdentifier=s}else i.prototype.api=e,a.Service.defineMethods(i);if(a.SequentialExecutor.call(this.prototype),!this.prototype.publisher&&a.util.clientSideMonitoring){var n=a.util.clientSideMonitoring.Publisher,u=a.util.clientSideMonitoring.configProvider,p=u();this.prototype.publisher=new n(p),p.enabled&&(a.Service._clientSideMonitoring=!0)}return a.SequentialExecutor.call(i.prototype),a.Service.addDefaultMonitoringListeners(i.prototype),i},addVersions:function(e,t){Array.isArray(t)||(t=[t]),e.services=e.services||{};for(var r=0;r=0){throw a.util.error(new Error,{name:"InvalidEndpoint",message:"AWS.IotData requires an explicit `endpoint' configuration option."})}},setupRequestListeners:function(e){e.addListener("validateResponse",this.validateResponseBody), diff --git a/lib/core.js b/lib/core.js index 9104a6a7e1..c40e0eb5d6 100644 --- a/lib/core.js +++ b/lib/core.js @@ -20,7 +20,7 @@ AWS.util.update(AWS, { /** * @constant */ - VERSION: '2.1457.0', + VERSION: '2.1458.0', /** * @api private diff --git a/package.json b/package.json index 00ac7b43d0..08968f422c 100644 --- a/package.json +++ b/package.json @@ -1,7 +1,7 @@ { "name": "aws-sdk", "description": "AWS SDK for JavaScript", - "version": "2.1457.0", + "version": "2.1458.0", "author": { "name": "Amazon Web Services", "email": "",