Update models for release

.changes/3.109.0

@@ -0,0 +1,22 @@
+[
+    {
+        "type": "api-change",
+        "category": "OpsWorksCM",
+        "description": "This release adds support for Chef Automate 2 specific engine attributes."
+    },
+    {
+        "type": "api-change",
+        "category": "CodeBuild",
+        "description": "CodeBuild adds CloudFormation support for SourceCredential"
+    },
+    {
+        "type": "api-change",
+        "category": "Glue",
+        "description": "You can now use AWS Glue to find matching records across dataset even without identifiers to join on by using the new FindMatches ML Transform. Find related products, places, suppliers, customers, and more by teaching a custom machine learning transformation that you can use to identify matching matching records as part of your analysis, data cleaning, or master data management project by adding the FindMatches transformation to your Glue ETL Jobs. If your problem is more along the lines of deduplication, you can use the FindMatches in much the same way to identify customers who have signed up more than ones, products that have accidentally been added to your product catalog more than once, and so forth. Using the FindMatches MLTransform, you can teach a Transform your definition of a duplicate through examples, and it will use machine learning to identify other potential duplicates in your dataset. As with data integration, you can then use your new Transform in your deduplication projects by adding the FindMatches transformation to your Glue ETL Jobs. This release also contains additional APIs that support AWS Lake Formation."
+    },
+    {
+        "type": "feature",
+        "category": "LakeFormation",
+        "description": "Lake Formation: (New Service) AWS Lake Formation is a fully managed service that makes it easier for customers to build, secure and manage data lakes. AWS Lake Formation simplifies and automates many of the complex manual steps usually required to create data lakes including collecting, cleaning and cataloging data and securely making that data available for analytics and machine learning."
+    }
+]

CHANGELOG.md

@@ -1,5 +1,12 @@
 # CHANGELOG
 
+## next release
+
+* `Aws\CodeBuild` - CodeBuild adds CloudFormation support for SourceCredential
+* `Aws\Glue` - You can now use AWS Glue to find matching records across dataset even without identifiers to join on by using the new FindMatches ML Transform. Find related products, places, suppliers, customers, and more by teaching a custom machine learning transformation that you can use to identify matching matching records as part of your analysis, data cleaning, or master data management project by adding the FindMatches transformation to your Glue ETL Jobs. If your problem is more along the lines of deduplication, you can use the FindMatches in much the same way to identify customers who have signed up more than ones, products that have accidentally been added to your product catalog more than once, and so forth. Using the FindMatches MLTransform, you can teach a Transform your definition of a duplicate through examples, and it will use machine learning to identify other potential duplicates in your dataset. As with data integration, you can then use your new Transform in your deduplication projects by adding the FindMatches transformation to your Glue ETL Jobs. This release also contains additional APIs that support AWS Lake Formation.
+* `Aws\LakeFormation` - Lake Formation: (New Service) AWS Lake Formation is a fully managed service that makes it easier for customers to build, secure and manage data lakes. AWS Lake Formation simplifies and automates many of the complex manual steps usually required to create data lakes including collecting, cleaning and cataloging data and securely making that data available for analytics and machine learning.
+* `Aws\OpsWorksCM` - This release adds support for Chef Automate 2 specific engine attributes.
+
 ## 3.108.6 - 2019-08-07
 
 * `Aws\ApplicationInsights` - CloudWatch Application Insights for .NET and SQL Server now provides integration with AWS Systems Manager OpsCenter. This integration allows you to view and resolve problems and operational issues detected for selected applications.

src/Glue/GlueClient.php

@@ -29,6 +29,8 @@
  * @method \GuzzleHttp\Promise\Promise batchGetWorkflowsAsync(array $args = [])
  * @method \Aws\Result batchStopJobRun(array $args = [])
  * @method \GuzzleHttp\Promise\Promise batchStopJobRunAsync(array $args = [])
+ * @method \Aws\Result cancelMLTaskRun(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise cancelMLTaskRunAsync(array $args = [])
  * @method \Aws\Result createClassifier(array $args = [])
  * @method \GuzzleHttp\Promise\Promise createClassifierAsync(array $args = [])
  * @method \Aws\Result createConnection(array $args = [])
@@ -41,6 +43,8 @@
  * @method \GuzzleHttp\Promise\Promise createDevEndpointAsync(array $args = [])
  * @method \Aws\Result createJob(array $args = [])
  * @method \GuzzleHttp\Promise\Promise createJobAsync(array $args = [])
+ * @method \Aws\Result createMLTransform(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise createMLTransformAsync(array $args = [])
  * @method \Aws\Result createPartition(array $args = [])
  * @method \GuzzleHttp\Promise\Promise createPartitionAsync(array $args = [])
  * @method \Aws\Result createScript(array $args = [])
@@ -67,6 +71,8 @@
  * @method \GuzzleHttp\Promise\Promise deleteDevEndpointAsync(array $args = [])
  * @method \Aws\Result deleteJob(array $args = [])
  * @method \GuzzleHttp\Promise\Promise deleteJobAsync(array $args = [])
+ * @method \Aws\Result deleteMLTransform(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise deleteMLTransformAsync(array $args = [])
  * @method \Aws\Result deletePartition(array $args = [])
  * @method \GuzzleHttp\Promise\Promise deletePartitionAsync(array $args = [])
  * @method \Aws\Result deleteResourcePolicy(array $args = [])
@@ -123,6 +129,14 @@
  * @method \GuzzleHttp\Promise\Promise getJobRunsAsync(array $args = [])
  * @method \Aws\Result getJobs(array $args = [])
  * @method \GuzzleHttp\Promise\Promise getJobsAsync(array $args = [])
+ * @method \Aws\Result getMLTaskRun(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise getMLTaskRunAsync(array $args = [])
+ * @method \Aws\Result getMLTaskRuns(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise getMLTaskRunsAsync(array $args = [])
+ * @method \Aws\Result getMLTransform(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise getMLTransformAsync(array $args = [])
+ * @method \Aws\Result getMLTransforms(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise getMLTransformsAsync(array $args = [])
  * @method \Aws\Result getMapping(array $args = [])
  * @method \GuzzleHttp\Promise\Promise getMappingAsync(array $args = [])
  * @method \Aws\Result getPartition(array $args = [])
@@ -183,12 +197,22 @@
  * @method \GuzzleHttp\Promise\Promise putWorkflowRunPropertiesAsync(array $args = [])
  * @method \Aws\Result resetJobBookmark(array $args = [])
  * @method \GuzzleHttp\Promise\Promise resetJobBookmarkAsync(array $args = [])
+ * @method \Aws\Result searchTables(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise searchTablesAsync(array $args = [])
  * @method \Aws\Result startCrawler(array $args = [])
  * @method \GuzzleHttp\Promise\Promise startCrawlerAsync(array $args = [])
  * @method \Aws\Result startCrawlerSchedule(array $args = [])
  * @method \GuzzleHttp\Promise\Promise startCrawlerScheduleAsync(array $args = [])
+ * @method \Aws\Result startExportLabelsTaskRun(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise startExportLabelsTaskRunAsync(array $args = [])
+ * @method \Aws\Result startImportLabelsTaskRun(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise startImportLabelsTaskRunAsync(array $args = [])
  * @method \Aws\Result startJobRun(array $args = [])
  * @method \GuzzleHttp\Promise\Promise startJobRunAsync(array $args = [])
+ * @method \Aws\Result startMLEvaluationTaskRun(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise startMLEvaluationTaskRunAsync(array $args = [])
+ * @method \Aws\Result startMLLabelingSetGenerationTaskRun(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise startMLLabelingSetGenerationTaskRunAsync(array $args = [])
  * @method \Aws\Result startTrigger(array $args = [])
  * @method \GuzzleHttp\Promise\Promise startTriggerAsync(array $args = [])
  * @method \Aws\Result startWorkflowRun(array $args = [])
@@ -217,6 +241,8 @@
  * @method \GuzzleHttp\Promise\Promise updateDevEndpointAsync(array $args = [])
  * @method \Aws\Result updateJob(array $args = [])
  * @method \GuzzleHttp\Promise\Promise updateJobAsync(array $args = [])
+ * @method \Aws\Result updateMLTransform(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise updateMLTransformAsync(array $args = [])
  * @method \Aws\Result updatePartition(array $args = [])
  * @method \GuzzleHttp\Promise\Promise updatePartitionAsync(array $args = [])
  * @method \Aws\Result updateTable(array $args = [])

src/LakeFormation/Exception/LakeFormationException.php

@@ -0,0 +1,9 @@
+<?php
+namespace Aws\LakeFormation\Exception;
+
+use Aws\Exception\AwsException;
+
+/**
+ * Represents an error interacting with the **AWS Lake Formation** service.
+ */
+class LakeFormationException extends AwsException {}

src/LakeFormation/LakeFormationClient.php

@@ -0,0 +1,35 @@
+<?php
+namespace Aws\LakeFormation;
+
+use Aws\AwsClient;
+
+/**
+ * This client is used to interact with the **AWS Lake Formation** service.
+ * @method \Aws\Result batchGrantPermissions(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise batchGrantPermissionsAsync(array $args = [])
+ * @method \Aws\Result batchRevokePermissions(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise batchRevokePermissionsAsync(array $args = [])
+ * @method \Aws\Result deregisterResource(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise deregisterResourceAsync(array $args = [])
+ * @method \Aws\Result describeResource(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise describeResourceAsync(array $args = [])
+ * @method \Aws\Result getDataLakeSettings(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise getDataLakeSettingsAsync(array $args = [])
+ * @method \Aws\Result getEffectivePermissionsForPath(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise getEffectivePermissionsForPathAsync(array $args = [])
+ * @method \Aws\Result grantPermissions(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise grantPermissionsAsync(array $args = [])
+ * @method \Aws\Result listPermissions(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise listPermissionsAsync(array $args = [])
+ * @method \Aws\Result listResources(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise listResourcesAsync(array $args = [])
+ * @method \Aws\Result putDataLakeSettings(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise putDataLakeSettingsAsync(array $args = [])
+ * @method \Aws\Result registerResource(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise registerResourceAsync(array $args = [])
+ * @method \Aws\Result revokePermissions(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise revokePermissionsAsync(array $args = [])
+ * @method \Aws\Result updateResource(array $args = [])
+ * @method \GuzzleHttp\Promise\Promise updateResourceAsync(array $args = [])
+ */
+class LakeFormationClient extends AwsClient {}

src/Sdk.php

@@ -208,6 +208,8 @@
  * @method \Aws\MultiRegionClient createMultiRegionKinesisVideoMedia(array $args = [])
  * @method \Aws\Kms\KmsClient createKms(array $args = [])
  * @method \Aws\MultiRegionClient createMultiRegionKms(array $args = [])
+ * @method \Aws\LakeFormation\LakeFormationClient createLakeFormation(array $args = [])
+ * @method \Aws\MultiRegionClient createMultiRegionLakeFormation(array $args = [])
  * @method \Aws\Lambda\LambdaClient createLambda(array $args = [])
  * @method \Aws\MultiRegionClient createMultiRegionLambda(array $args = [])
  * @method \Aws\LexModelBuildingService\LexModelBuildingServiceClient createLexModelBuildingService(array $args = [])

src/data/codebuild/2016-10-06/api-2.json

@@ -126,7 +126,8 @@
       "output":{"shape":"ImportSourceCredentialsOutput"},
       "errors":[
         {"shape":"InvalidInputException"},
-        {"shape":"AccountLimitExceededException"}
+        {"shape":"AccountLimitExceededException"},
+        {"shape":"ResourceAlreadyExistsException"}
       ]
     },
     "InvalidateProjectCache":{
@@ -662,7 +663,8 @@
         "username":{"shape":"NonEmptyString"},
         "token":{"shape":"SensitiveNonEmptyString"},
         "serverType":{"shape":"ServerType"},
-        "authType":{"shape":"AuthType"}
+        "authType":{"shape":"AuthType"},
+        "shouldOverwrite":{"shape":"WrapperBoolean"}
       }
     },
     "ImportSourceCredentialsOutput":{

src/data/codebuild/2016-10-06/docs-2.json

@@ -933,9 +933,10 @@
         "BuildArtifacts$encryptionDisabled": "<p> Information that tells you if encryption for build artifacts is disabled. </p>",
         "CreateProjectInput$badgeEnabled": "<p>Set this to true to generate a publicly accessible URL for your project's build badge.</p>",
         "GitSubmodulesConfig$fetchSubmodules": "<p> Set to true to fetch Git submodules for your AWS CodeBuild build project. </p>",
+        "ImportSourceCredentialsInput$shouldOverwrite": "<p> Set to <code>false</code> to prevent overwriting the repository source credentials. Set to <code>true</code> to overwrite the repository source credentials. The default value is <code>true</code>. </p>",
         "ProjectArtifacts$overrideArtifactName": "<p> If this flag is set, a name specified in the build spec file overrides the artifact name. The name specified in a build spec file is calculated at build time and uses the Shell Command Language. For example, you can append a date and time to your artifact name so that it is always unique. </p>",
         "ProjectArtifacts$encryptionDisabled": "<p> Set to true if you do not want your output artifacts encrypted. This option is valid only if your artifacts type is Amazon Simple Storage Service (Amazon S3). If this is set with another artifacts type, an invalidInputException is thrown. </p>",
-        "ProjectEnvironment$privilegedMode": "<p>Enables running the Docker daemon inside a Docker container. Set to true only if the build project is be used to build Docker images, and the specified build environment image is not provided by AWS CodeBuild with Docker support. Otherwise, all associated builds that attempt to interact with the Docker daemon fail. You must also start the Docker daemon so that builds can interact with it. One way to do this is to initialize the Docker daemon during the install phase of your build spec by running the following build commands. (Do not run these commands if the specified build environment image is provided by AWS CodeBuild with Docker support.)</p> <p>If the operating system's base image is Ubuntu Linux:</p> <p> <code>- nohup /usr/local/bin/dockerd --host=unix:///var/run/docker.sock --host=tcp://0.0.0.0:2375 --storage-driver=overlay&amp;</code> </p> <p> <code>- timeout 15 sh -c \"until docker info; do echo .; sleep 1; done\"</code> </p> <p>If the operating system's base image is Alpine Linux and the previous command does not work, add the <code>-t</code> argument to <code>timeout</code>:</p> <p> <code>- nohup /usr/local/bin/dockerd --host=unix:///var/run/docker.sock --host=tcp://0.0.0.0:2375 --storage-driver=overlay&amp;</code> </p> <p> <code>- timeout -t 15 sh -c \"until docker info; do echo .; sleep 1; done\"</code> </p>",
+        "ProjectEnvironment$privilegedMode": "<p>Enables running the Docker daemon inside a Docker container. Set to true only if the build project is used to build Docker images. Otherwise, a build that attempts to interact with the Docker daemon fails.</p> <p>You can initialize the Docker daemon during the install phase of your build by adding one of the following sets of commands to the install phase of your buildspec file:</p> <p>If the operating system's base image is Ubuntu Linux:</p> <p> <code>- nohup /usr/local/bin/dockerd --host=unix:///var/run/docker.sock --host=tcp://0.0.0.0:2375 --storage-driver=overlay&amp;</code> </p> <p> <code>- timeout 15 sh -c \"until docker info; do echo .; sleep 1; done\"</code> </p> <p>If the operating system's base image is Alpine Linux and the previous command does not work, add the <code>-t</code> argument to <code>timeout</code>:</p> <p> <code>- nohup /usr/local/bin/dockerd --host=unix:///var/run/docker.sock --host=tcp://0.0.0.0:2375 --storage-driver=overlay&amp;</code> </p> <p> <code>- timeout -t 15 sh -c \"until docker info; do echo .; sleep 1; done\"</code> </p>",
         "ProjectSource$reportBuildStatus": "<p> Set to true to report the status of a build's start and finish to your source provider. This option is valid only when your source provider is GitHub, GitHub Enterprise, or Bitbucket. If this is set and you use a different source provider, an invalidInputException is thrown. </p>",
         "ProjectSource$insecureSsl": "<p>Enable this flag to ignore SSL warnings while connecting to the project source code.</p>",
         "S3LogsConfig$encryptionDisabled": "<p> Set to true if you do not want your S3 build log output encrypted. By default S3 build logs are encrypted. </p>",

src/data/endpoints.json

@@ -627,6 +627,7 @@
           "eu-west-1" : { },
           "eu-west-2" : { },
           "eu-west-3" : { },
+          "me-south-1" : { },
           "us-east-1" : { },
           "us-east-2" : { },
           "us-west-1" : { },
@@ -4416,6 +4417,9 @@
           "protocols" : [ "https" ]
         },
         "endpoints" : {
+          "us-gov-east-1" : {
+            "protocols" : [ "https" ]
+          },
           "us-gov-west-1" : {
             "protocols" : [ "https" ]
           }