amazonka-ml 1.6.1 → 2.0

raw patch · 133 files changed

+16968/−9285 lines, 133 filesdep +case-insensitivedep ~amazonka-coredep ~amazonka-testdep ~basesetup-changedPVP ok

version bump matches the API change (PVP)

Dependencies added: case-insensitive

Dependency ranges changed: amazonka-core, amazonka-test, base

API changes (from Hackage documentation)

Files

• README.md +3/−4
• Setup.hs +0/−2
• amazonka-ml.cabal +128/−102
• fixture/AddTags.yaml +10/−0
• fixture/CreateBatchPrediction.yaml +10/−0
• fixture/CreateDataSourceFromRDS.yaml +10/−0
• fixture/CreateDataSourceFromRedshift.yaml +10/−0
• fixture/CreateDataSourceFromS.yaml +10/−0
• fixture/CreateDataSourceFromS3.yaml +10/−0
• fixture/CreateDataSourceFromSResponse.proto +0/−0
• fixture/CreateEvaluation.yaml +10/−0
• fixture/CreateMLModel.yaml +10/−0
• fixture/CreateRealtimeEndpoint.yaml +10/−0
• fixture/DeleteBatchPrediction.yaml +10/−0
• fixture/DeleteDataSource.yaml +10/−0
• fixture/DeleteEvaluation.yaml +10/−0
• fixture/DeleteMLModel.yaml +10/−0
• fixture/DeleteRealtimeEndpoint.yaml +10/−0
• fixture/DeleteTags.yaml +10/−0
• fixture/DescribeBatchPredictions.yaml +10/−0
• fixture/DescribeDataSources.yaml +10/−0
• fixture/DescribeEvaluations.yaml +10/−0
• fixture/DescribeMLModels.yaml +10/−0
• fixture/DescribeTags.yaml +10/−0
• fixture/GetBatchPrediction.yaml +10/−0
• fixture/GetDataSource.yaml +10/−0
• fixture/GetEvaluation.yaml +10/−0
• fixture/GetMLModel.yaml +10/−0
• fixture/Predict.yaml +10/−0
• fixture/UpdateBatchPrediction.yaml +10/−0
• fixture/UpdateDataSource.yaml +10/−0
• fixture/UpdateEvaluation.yaml +10/−0
• fixture/UpdateMLModel.yaml +10/−0
• gen/Amazonka/MachineLearning.hs +394/−0
• gen/Amazonka/MachineLearning/AddTags.hs +219/−0
• gen/Amazonka/MachineLearning/CreateBatchPrediction.hs +299/−0
• gen/Amazonka/MachineLearning/CreateDataSourceFromRDS.hs +426/−0
• gen/Amazonka/MachineLearning/CreateDataSourceFromRedshift.hs +410/−0
• gen/Amazonka/MachineLearning/CreateDataSourceFromS3.hs +312/−0
• gen/Amazonka/MachineLearning/CreateEvaluation.hs +265/−0
• gen/Amazonka/MachineLearning/CreateMLModel.hs +459/−0
• gen/Amazonka/MachineLearning/CreateRealtimeEndpoint.hs +198/−0
• gen/Amazonka/MachineLearning/DeleteBatchPrediction.hs +194/−0
• gen/Amazonka/MachineLearning/DeleteDataSource.hs +180/−0
• gen/Amazonka/MachineLearning/DeleteEvaluation.hs +185/−0
• gen/Amazonka/MachineLearning/DeleteMLModel.hs +181/−0
• gen/Amazonka/MachineLearning/DeleteRealtimeEndpoint.hs +192/−0
• gen/Amazonka/MachineLearning/DeleteTags.hs +215/−0
• gen/Amazonka/MachineLearning/DescribeBatchPredictions.hs +507/−0
• gen/Amazonka/MachineLearning/DescribeDataSources.hs +480/−0
• gen/Amazonka/MachineLearning/DescribeEvaluations.hs +501/−0
• gen/Amazonka/MachineLearning/DescribeMLModels.hs +510/−0
• gen/Amazonka/MachineLearning/DescribeTags.hs +211/−0
• gen/Amazonka/MachineLearning/GetBatchPrediction.hs +472/−0
• gen/Amazonka/MachineLearning/GetDataSource.hs +527/−0
• gen/Amazonka/MachineLearning/GetEvaluation.hs +472/−0
• gen/Amazonka/MachineLearning/GetMLModel.hs +710/−0
• gen/Amazonka/MachineLearning/Lens.hs +513/−0
• gen/Amazonka/MachineLearning/Predict.hs +198/−0
• gen/Amazonka/MachineLearning/Types.hs +412/−0
• gen/Amazonka/MachineLearning/Types/Algorithm.hs +72/−0
• gen/Amazonka/MachineLearning/Types/BatchPrediction.hs +330/−0
• gen/Amazonka/MachineLearning/Types/BatchPredictionFilterVariable.hs +124/−0
• gen/Amazonka/MachineLearning/Types/DataSource.hs +342/−0
• gen/Amazonka/MachineLearning/Types/DataSourceFilterVariable.hs +110/−0
• gen/Amazonka/MachineLearning/Types/DetailsAttributes.hs +77/−0
• gen/Amazonka/MachineLearning/Types/EntityStatus.hs +97/−0
• gen/Amazonka/MachineLearning/Types/Evaluation.hs +332/−0
• gen/Amazonka/MachineLearning/Types/EvaluationFilterVariable.hs +123/−0
• gen/Amazonka/MachineLearning/Types/MLModel.hs +512/−0
• gen/Amazonka/MachineLearning/Types/MLModelFilterVariable.hs +111/−0
• gen/Amazonka/MachineLearning/Types/MLModelType.hs +76/−0
• gen/Amazonka/MachineLearning/Types/PerformanceMetrics.hs +83/−0
• gen/Amazonka/MachineLearning/Types/Prediction.hs +122/−0
• gen/Amazonka/MachineLearning/Types/RDSDataSpec.hs +623/−0
• gen/Amazonka/MachineLearning/Types/RDSDatabase.hs +98/−0
• gen/Amazonka/MachineLearning/Types/RDSDatabaseCredentials.hs +85/−0
• gen/Amazonka/MachineLearning/Types/RDSMetadata.hs +165/−0
• gen/Amazonka/MachineLearning/Types/RealtimeEndpointInfo.hs +148/−0
• gen/Amazonka/MachineLearning/Types/RealtimeEndpointStatus.hs +81/−0
• gen/Amazonka/MachineLearning/Types/RedshiftDataSpec.hs +526/−0
• gen/Amazonka/MachineLearning/Types/RedshiftDatabase.hs +99/−0
• gen/Amazonka/MachineLearning/Types/RedshiftDatabaseCredentials.hs +86/−0
• gen/Amazonka/MachineLearning/Types/RedshiftMetadata.hs +99/−0
• gen/Amazonka/MachineLearning/Types/S3DataSpec.hs +472/−0
• gen/Amazonka/MachineLearning/Types/SortOrder.hs +77/−0
• gen/Amazonka/MachineLearning/Types/Tag.hs +102/−0
• gen/Amazonka/MachineLearning/Types/TaggableResourceType.hs +81/−0
• gen/Amazonka/MachineLearning/UpdateBatchPrediction.hs +207/−0
• gen/Amazonka/MachineLearning/UpdateDataSource.hs +203/−0
• gen/Amazonka/MachineLearning/UpdateEvaluation.hs +202/−0
• gen/Amazonka/MachineLearning/UpdateMLModel.hs +227/−0
• gen/Amazonka/MachineLearning/Waiters.hs +176/−0
• gen/Network/AWS/MachineLearning.hs +0/−429
• gen/Network/AWS/MachineLearning/AddTags.hs +0/−172
• gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs +0/−193
• gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs +0/−192
• gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs +0/−197
• gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs +0/−182
• gen/Network/AWS/MachineLearning/CreateEvaluation.hs +0/−179
• gen/Network/AWS/MachineLearning/CreateMLModel.hs +0/−213
• gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs +0/−153
• gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs +0/−146
• gen/Network/AWS/MachineLearning/DeleteDataSource.hs +0/−141
• gen/Network/AWS/MachineLearning/DeleteEvaluation.hs +0/−145
• gen/Network/AWS/MachineLearning/DeleteMLModel.hs +0/−141
• gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs +0/−153
• gen/Network/AWS/MachineLearning/DeleteTags.hs +0/−174
• gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs +0/−260
• gen/Network/AWS/MachineLearning/DescribeDataSources.hs +0/−259
• gen/Network/AWS/MachineLearning/DescribeEvaluations.hs +0/−259
• gen/Network/AWS/MachineLearning/DescribeMLModels.hs +0/−257
• gen/Network/AWS/MachineLearning/DescribeTags.hs +0/−169
• gen/Network/AWS/MachineLearning/GetBatchPrediction.hs +0/−302
• gen/Network/AWS/MachineLearning/GetDataSource.hs +0/−340
• gen/Network/AWS/MachineLearning/GetEvaluation.hs +0/−278
• gen/Network/AWS/MachineLearning/GetMLModel.hs +0/−350
• gen/Network/AWS/MachineLearning/Predict.hs +0/−156
• gen/Network/AWS/MachineLearning/Types.hs +0/−351
• gen/Network/AWS/MachineLearning/Types/Product.hs +0/−1616
• gen/Network/AWS/MachineLearning/Types/Sum.hs +0/−447
• gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs +0/−157
• gen/Network/AWS/MachineLearning/UpdateDataSource.hs +0/−152
• gen/Network/AWS/MachineLearning/UpdateEvaluation.hs +0/−152
• gen/Network/AWS/MachineLearning/UpdateMLModel.hs +0/−163
• gen/Network/AWS/MachineLearning/Waiters.hs +0/−105
• test/Main.hs +11/−9
• test/Test/AWS/Gen/MachineLearning.hs +0/−543
• test/Test/AWS/MachineLearning.hs +0/−26
• test/Test/AWS/MachineLearning/Internal.hs +0/−16
• test/Test/Amazonka/Gen/MachineLearning.hs +598/−0
• test/Test/Amazonka/MachineLearning.hs +20/−0
• test/Test/Amazonka/MachineLearning/Internal.hs +8/−0

@@ -7,9 +7,8 @@   ## Version--`1.6.1`-+ +`2.0` - Derived from API version @2014-12-12@ of the AWS service descriptions, licensed under Apache 2.0.  ## Description @@ -26,7 +25,7 @@ The provided lenses should be compatible with any of the major lens libraries [lens](http://hackage.haskell.org/package/lens) or [lens-family-core](http://hackage.haskell.org/package/lens-family-core). -See [Network.AWS.MachineLearning](http://hackage.haskell.org/package/amazonka-ml/docs/Network-AWS-MachineLearning.html)+See [Amazonka.MachineLearning](http://hackage.haskell.org/package/amazonka-ml/docs/Amazonka-MachineLearning.html) or [the AWS documentation](https://aws.amazon.com/documentation/) to get started.  

@@ -1,2 +0,0 @@-import           Distribution.Simple-main = defaultMain

@@ -1,113 +1,139 @@-name:                  amazonka-ml-version:               1.6.1-synopsis:              Amazon Machine Learning SDK.-homepage:              https://github.com/brendanhay/amazonka-bug-reports:           https://github.com/brendanhay/amazonka/issues-license:               MPL-2.0-license-file:          LICENSE-author:                Brendan Hay-maintainer:            Brendan Hay <brendan.g.hay+amazonka@gmail.com>-copyright:             Copyright (c) 2013-2018 Brendan Hay-category:              Network, AWS, Cloud, Distributed Computing-build-type:            Simple-cabal-version:         >= 1.10-extra-source-files:    README.md fixture/*.yaml fixture/*.proto src/.gitkeep+cabal-version:      2.2+name:               amazonka-ml+version:            2.0+synopsis:           Amazon Machine Learning SDK.+homepage:           https://github.com/brendanhay/amazonka+bug-reports:        https://github.com/brendanhay/amazonka/issues+license:            MPL-2.0+license-file:       LICENSE+author:             Brendan Hay+maintainer:+  Brendan Hay <brendan.g.hay+amazonka@gmail.com>, Jack Kelly <jack@jackkelly.name>++copyright:          Copyright (c) 2013-2023 Brendan Hay+category:           AWS+build-type:         Simple+extra-source-files:+  fixture/*.proto+  fixture/*.yaml+  README.md+  src/.gitkeep+ description:-    The types from this library are intended to be used with-    <http://hackage.haskell.org/package/amazonka amazonka>, which provides-    mechanisms for specifying AuthN/AuthZ information, sending requests,-    and receiving responses.-    .-    Lenses are used for constructing and manipulating types,-    due to the depth of nesting of AWS types and transparency regarding-    de/serialisation into more palatable Haskell values.-    The provided lenses should be compatible with any of the major lens libraries-    such as <http://hackage.haskell.org/package/lens lens> or-    <http://hackage.haskell.org/package/lens-family-core lens-family-core>.-    .-    See "Network.AWS.MachineLearning" or <https://aws.amazon.com/documentation/ the AWS documentation>-    to get started.+  Derived from API version @2014-12-12@ of the AWS service descriptions, licensed under Apache 2.0.+  .+  The types from this library are intended to be used with <http://hackage.haskell.org/package/amazonka amazonka>,+  which provides mechanisms for specifying AuthN/AuthZ information, sending requests, and receiving responses.+  .+  It is recommended to use generic lenses or optics from packages such as <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify optional fields and deconstruct responses.+  .+  Generated lenses can be found in "Amazonka.MachineLearning.Lens" and are+  suitable for use with a lens package such as <http://hackage.haskell.org/package/lens lens> or <http://hackage.haskell.org/package/lens-family-core lens-family-core>.+  .+  See "Amazonka.MachineLearning" and the <https://aws.amazon.com/documentation/ AWS documentation> to get started.  source-repository head-    type:              git-    location:          git://github.com/brendanhay/amazonka.git-    subdir:            amazonka-ml+  type:     git+  location: git://github.com/brendanhay/amazonka.git+  subdir:   amazonka-ml  library-    default-language:  Haskell2010-    hs-source-dirs:    src gen--    ghc-options:-        -Wall-        -fwarn-incomplete-uni-patterns-        -fwarn-incomplete-record-updates-        -funbox-strict-fields--    exposed-modules:-          Network.AWS.MachineLearning-        , Network.AWS.MachineLearning.AddTags-        , Network.AWS.MachineLearning.CreateBatchPrediction-        , Network.AWS.MachineLearning.CreateDataSourceFromRDS-        , Network.AWS.MachineLearning.CreateDataSourceFromRedshift-        , Network.AWS.MachineLearning.CreateDataSourceFromS3-        , Network.AWS.MachineLearning.CreateEvaluation-        , Network.AWS.MachineLearning.CreateMLModel-        , Network.AWS.MachineLearning.CreateRealtimeEndpoint-        , Network.AWS.MachineLearning.DeleteBatchPrediction-        , Network.AWS.MachineLearning.DeleteDataSource-        , Network.AWS.MachineLearning.DeleteEvaluation-        , Network.AWS.MachineLearning.DeleteMLModel-        , Network.AWS.MachineLearning.DeleteRealtimeEndpoint-        , Network.AWS.MachineLearning.DeleteTags-        , Network.AWS.MachineLearning.DescribeBatchPredictions-        , Network.AWS.MachineLearning.DescribeDataSources-        , Network.AWS.MachineLearning.DescribeEvaluations-        , Network.AWS.MachineLearning.DescribeMLModels-        , Network.AWS.MachineLearning.DescribeTags-        , Network.AWS.MachineLearning.GetBatchPrediction-        , Network.AWS.MachineLearning.GetDataSource-        , Network.AWS.MachineLearning.GetEvaluation-        , Network.AWS.MachineLearning.GetMLModel-        , Network.AWS.MachineLearning.Predict-        , Network.AWS.MachineLearning.Types-        , Network.AWS.MachineLearning.UpdateBatchPrediction-        , Network.AWS.MachineLearning.UpdateDataSource-        , Network.AWS.MachineLearning.UpdateEvaluation-        , Network.AWS.MachineLearning.UpdateMLModel-        , Network.AWS.MachineLearning.Waiters+  default-language: Haskell2010+  hs-source-dirs:   src gen+  ghc-options:+    -Wall -fwarn-incomplete-uni-patterns+    -fwarn-incomplete-record-updates -funbox-strict-fields -    other-modules:-          Network.AWS.MachineLearning.Types.Product-        , Network.AWS.MachineLearning.Types.Sum+  exposed-modules:+    Amazonka.MachineLearning+    Amazonka.MachineLearning.AddTags+    Amazonka.MachineLearning.CreateBatchPrediction+    Amazonka.MachineLearning.CreateDataSourceFromRDS+    Amazonka.MachineLearning.CreateDataSourceFromRedshift+    Amazonka.MachineLearning.CreateDataSourceFromS3+    Amazonka.MachineLearning.CreateEvaluation+    Amazonka.MachineLearning.CreateMLModel+    Amazonka.MachineLearning.CreateRealtimeEndpoint+    Amazonka.MachineLearning.DeleteBatchPrediction+    Amazonka.MachineLearning.DeleteDataSource+    Amazonka.MachineLearning.DeleteEvaluation+    Amazonka.MachineLearning.DeleteMLModel+    Amazonka.MachineLearning.DeleteRealtimeEndpoint+    Amazonka.MachineLearning.DeleteTags+    Amazonka.MachineLearning.DescribeBatchPredictions+    Amazonka.MachineLearning.DescribeDataSources+    Amazonka.MachineLearning.DescribeEvaluations+    Amazonka.MachineLearning.DescribeMLModels+    Amazonka.MachineLearning.DescribeTags+    Amazonka.MachineLearning.GetBatchPrediction+    Amazonka.MachineLearning.GetDataSource+    Amazonka.MachineLearning.GetEvaluation+    Amazonka.MachineLearning.GetMLModel+    Amazonka.MachineLearning.Lens+    Amazonka.MachineLearning.Predict+    Amazonka.MachineLearning.Types+    Amazonka.MachineLearning.Types.Algorithm+    Amazonka.MachineLearning.Types.BatchPrediction+    Amazonka.MachineLearning.Types.BatchPredictionFilterVariable+    Amazonka.MachineLearning.Types.DataSource+    Amazonka.MachineLearning.Types.DataSourceFilterVariable+    Amazonka.MachineLearning.Types.DetailsAttributes+    Amazonka.MachineLearning.Types.EntityStatus+    Amazonka.MachineLearning.Types.Evaluation+    Amazonka.MachineLearning.Types.EvaluationFilterVariable+    Amazonka.MachineLearning.Types.MLModel+    Amazonka.MachineLearning.Types.MLModelFilterVariable+    Amazonka.MachineLearning.Types.MLModelType+    Amazonka.MachineLearning.Types.PerformanceMetrics+    Amazonka.MachineLearning.Types.Prediction+    Amazonka.MachineLearning.Types.RDSDatabase+    Amazonka.MachineLearning.Types.RDSDatabaseCredentials+    Amazonka.MachineLearning.Types.RDSDataSpec+    Amazonka.MachineLearning.Types.RDSMetadata+    Amazonka.MachineLearning.Types.RealtimeEndpointInfo+    Amazonka.MachineLearning.Types.RealtimeEndpointStatus+    Amazonka.MachineLearning.Types.RedshiftDatabase+    Amazonka.MachineLearning.Types.RedshiftDatabaseCredentials+    Amazonka.MachineLearning.Types.RedshiftDataSpec+    Amazonka.MachineLearning.Types.RedshiftMetadata+    Amazonka.MachineLearning.Types.S3DataSpec+    Amazonka.MachineLearning.Types.SortOrder+    Amazonka.MachineLearning.Types.Tag+    Amazonka.MachineLearning.Types.TaggableResourceType+    Amazonka.MachineLearning.UpdateBatchPrediction+    Amazonka.MachineLearning.UpdateDataSource+    Amazonka.MachineLearning.UpdateEvaluation+    Amazonka.MachineLearning.UpdateMLModel+    Amazonka.MachineLearning.Waiters -    build-depends:-          amazonka-core == 1.6.1.*-        , base          >= 4.7     && < 5+  build-depends:+    , amazonka-core  >=2.0  && <2.1+    , base           >=4.12 && <5  test-suite amazonka-ml-test-    type:              exitcode-stdio-1.0-    default-language:  Haskell2010-    hs-source-dirs:    test-    main-is:           Main.hs--    ghc-options:       -Wall -threaded+  type:             exitcode-stdio-1.0+  default-language: Haskell2010+  hs-source-dirs:   test+  main-is:          Main.hs+  ghc-options:      -Wall -threaded -    -- This section is encoded by the template and any modules added by-    -- hand outside these namespaces will not correctly be added to the-    -- distribution package.-    other-modules:-          Test.AWS.MachineLearning-        , Test.AWS.Gen.MachineLearning-        , Test.AWS.MachineLearning.Internal+  -- This section is encoded by the template and any modules added by+  -- hand outside these namespaces will not correctly be added to the+  -- distribution package.+  other-modules:+    Test.Amazonka.Gen.MachineLearning+    Test.Amazonka.MachineLearning+    Test.Amazonka.MachineLearning.Internal -    build-depends:-          amazonka-core == 1.6.1.*-        , amazonka-test == 1.6.1.*-        , amazonka-ml-        , base-        , bytestring-        , tasty-        , tasty-hunit-        , text-        , time-        , unordered-containers+  build-depends:+    , amazonka-core         >=2.0 && <2.1+    , amazonka-ml+    , amazonka-test         >=2.0 && <2.1+    , base+    , bytestring+    , case-insensitive+    , tasty+    , tasty-hunit+    , text+    , time+    , unordered-containers

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,10 @@+---+method: POST+headers:+  Authorization:         AWS4-HMAC-SHA256 Credential=access/20091028/us-east-1/machinelearning/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date, Signature=?+  Host:                  machinelearning.us-east-1.amazonaws.com+  Content-Type:          application/x-www-form-urlencoded; charset=utf-8+  X-Amz-Content-SHA256:  abcdef+  X-Amz-Date:            20091028T223200Z+body:+  ''

@@ -0,0 +1,394 @@+{-# OPTIONS_GHC -fno-warn-duplicate-exports #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}++-- |+-- Module      : Amazonka.MachineLearning+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Derived from API version @2014-12-12@ of the AWS service descriptions, licensed under Apache 2.0.+--+-- Definition of the public APIs exposed by Amazon Machine Learning+module Amazonka.MachineLearning+  ( -- * Service Configuration+    defaultService,++    -- * Errors+    -- $errors++    -- ** IdempotentParameterMismatchException+    _IdempotentParameterMismatchException,++    -- ** InternalServerException+    _InternalServerException,++    -- ** InvalidInputException+    _InvalidInputException,++    -- ** InvalidTagException+    _InvalidTagException,++    -- ** LimitExceededException+    _LimitExceededException,++    -- ** PredictorNotMountedException+    _PredictorNotMountedException,++    -- ** ResourceNotFoundException+    _ResourceNotFoundException,++    -- ** TagLimitExceededException+    _TagLimitExceededException,++    -- * Waiters+    -- $waiters++    -- ** BatchPredictionAvailable+    newBatchPredictionAvailable,++    -- ** DataSourceAvailable+    newDataSourceAvailable,++    -- ** EvaluationAvailable+    newEvaluationAvailable,++    -- ** MLModelAvailable+    newMLModelAvailable,++    -- * Operations+    -- $operations++    -- ** AddTags+    AddTags (AddTags'),+    newAddTags,+    AddTagsResponse (AddTagsResponse'),+    newAddTagsResponse,++    -- ** CreateBatchPrediction+    CreateBatchPrediction (CreateBatchPrediction'),+    newCreateBatchPrediction,+    CreateBatchPredictionResponse (CreateBatchPredictionResponse'),+    newCreateBatchPredictionResponse,++    -- ** CreateDataSourceFromRDS+    CreateDataSourceFromRDS (CreateDataSourceFromRDS'),+    newCreateDataSourceFromRDS,+    CreateDataSourceFromRDSResponse (CreateDataSourceFromRDSResponse'),+    newCreateDataSourceFromRDSResponse,++    -- ** CreateDataSourceFromRedshift+    CreateDataSourceFromRedshift (CreateDataSourceFromRedshift'),+    newCreateDataSourceFromRedshift,+    CreateDataSourceFromRedshiftResponse (CreateDataSourceFromRedshiftResponse'),+    newCreateDataSourceFromRedshiftResponse,++    -- ** CreateDataSourceFromS3+    CreateDataSourceFromS3 (CreateDataSourceFromS3'),+    newCreateDataSourceFromS3,+    CreateDataSourceFromS3Response (CreateDataSourceFromS3Response'),+    newCreateDataSourceFromS3Response,++    -- ** CreateEvaluation+    CreateEvaluation (CreateEvaluation'),+    newCreateEvaluation,+    CreateEvaluationResponse (CreateEvaluationResponse'),+    newCreateEvaluationResponse,++    -- ** CreateMLModel+    CreateMLModel (CreateMLModel'),+    newCreateMLModel,+    CreateMLModelResponse (CreateMLModelResponse'),+    newCreateMLModelResponse,++    -- ** CreateRealtimeEndpoint+    CreateRealtimeEndpoint (CreateRealtimeEndpoint'),+    newCreateRealtimeEndpoint,+    CreateRealtimeEndpointResponse (CreateRealtimeEndpointResponse'),+    newCreateRealtimeEndpointResponse,++    -- ** DeleteBatchPrediction+    DeleteBatchPrediction (DeleteBatchPrediction'),+    newDeleteBatchPrediction,+    DeleteBatchPredictionResponse (DeleteBatchPredictionResponse'),+    newDeleteBatchPredictionResponse,++    -- ** DeleteDataSource+    DeleteDataSource (DeleteDataSource'),+    newDeleteDataSource,+    DeleteDataSourceResponse (DeleteDataSourceResponse'),+    newDeleteDataSourceResponse,++    -- ** DeleteEvaluation+    DeleteEvaluation (DeleteEvaluation'),+    newDeleteEvaluation,+    DeleteEvaluationResponse (DeleteEvaluationResponse'),+    newDeleteEvaluationResponse,++    -- ** DeleteMLModel+    DeleteMLModel (DeleteMLModel'),+    newDeleteMLModel,+    DeleteMLModelResponse (DeleteMLModelResponse'),+    newDeleteMLModelResponse,++    -- ** DeleteRealtimeEndpoint+    DeleteRealtimeEndpoint (DeleteRealtimeEndpoint'),+    newDeleteRealtimeEndpoint,+    DeleteRealtimeEndpointResponse (DeleteRealtimeEndpointResponse'),+    newDeleteRealtimeEndpointResponse,++    -- ** DeleteTags+    DeleteTags (DeleteTags'),+    newDeleteTags,+    DeleteTagsResponse (DeleteTagsResponse'),+    newDeleteTagsResponse,++    -- ** DescribeBatchPredictions (Paginated)+    DescribeBatchPredictions (DescribeBatchPredictions'),+    newDescribeBatchPredictions,+    DescribeBatchPredictionsResponse (DescribeBatchPredictionsResponse'),+    newDescribeBatchPredictionsResponse,++    -- ** DescribeDataSources (Paginated)+    DescribeDataSources (DescribeDataSources'),+    newDescribeDataSources,+    DescribeDataSourcesResponse (DescribeDataSourcesResponse'),+    newDescribeDataSourcesResponse,++    -- ** DescribeEvaluations (Paginated)+    DescribeEvaluations (DescribeEvaluations'),+    newDescribeEvaluations,+    DescribeEvaluationsResponse (DescribeEvaluationsResponse'),+    newDescribeEvaluationsResponse,++    -- ** DescribeMLModels (Paginated)+    DescribeMLModels (DescribeMLModels'),+    newDescribeMLModels,+    DescribeMLModelsResponse (DescribeMLModelsResponse'),+    newDescribeMLModelsResponse,++    -- ** DescribeTags+    DescribeTags (DescribeTags'),+    newDescribeTags,+    DescribeTagsResponse (DescribeTagsResponse'),+    newDescribeTagsResponse,++    -- ** GetBatchPrediction+    GetBatchPrediction (GetBatchPrediction'),+    newGetBatchPrediction,+    GetBatchPredictionResponse (GetBatchPredictionResponse'),+    newGetBatchPredictionResponse,++    -- ** GetDataSource+    GetDataSource (GetDataSource'),+    newGetDataSource,+    GetDataSourceResponse (GetDataSourceResponse'),+    newGetDataSourceResponse,++    -- ** GetEvaluation+    GetEvaluation (GetEvaluation'),+    newGetEvaluation,+    GetEvaluationResponse (GetEvaluationResponse'),+    newGetEvaluationResponse,++    -- ** GetMLModel+    GetMLModel (GetMLModel'),+    newGetMLModel,+    GetMLModelResponse (GetMLModelResponse'),+    newGetMLModelResponse,++    -- ** Predict+    Predict (Predict'),+    newPredict,+    PredictResponse (PredictResponse'),+    newPredictResponse,++    -- ** UpdateBatchPrediction+    UpdateBatchPrediction (UpdateBatchPrediction'),+    newUpdateBatchPrediction,+    UpdateBatchPredictionResponse (UpdateBatchPredictionResponse'),+    newUpdateBatchPredictionResponse,++    -- ** UpdateDataSource+    UpdateDataSource (UpdateDataSource'),+    newUpdateDataSource,+    UpdateDataSourceResponse (UpdateDataSourceResponse'),+    newUpdateDataSourceResponse,++    -- ** UpdateEvaluation+    UpdateEvaluation (UpdateEvaluation'),+    newUpdateEvaluation,+    UpdateEvaluationResponse (UpdateEvaluationResponse'),+    newUpdateEvaluationResponse,++    -- ** UpdateMLModel+    UpdateMLModel (UpdateMLModel'),+    newUpdateMLModel,+    UpdateMLModelResponse (UpdateMLModelResponse'),+    newUpdateMLModelResponse,++    -- * Types++    -- ** Algorithm+    Algorithm (..),++    -- ** BatchPredictionFilterVariable+    BatchPredictionFilterVariable (..),++    -- ** DataSourceFilterVariable+    DataSourceFilterVariable (..),++    -- ** DetailsAttributes+    DetailsAttributes (..),++    -- ** EntityStatus+    EntityStatus (..),++    -- ** EvaluationFilterVariable+    EvaluationFilterVariable (..),++    -- ** MLModelFilterVariable+    MLModelFilterVariable (..),++    -- ** MLModelType+    MLModelType (..),++    -- ** RealtimeEndpointStatus+    RealtimeEndpointStatus (..),++    -- ** SortOrder+    SortOrder (..),++    -- ** TaggableResourceType+    TaggableResourceType (..),++    -- ** BatchPrediction+    BatchPrediction (BatchPrediction'),+    newBatchPrediction,++    -- ** DataSource+    DataSource (DataSource'),+    newDataSource,++    -- ** Evaluation+    Evaluation (Evaluation'),+    newEvaluation,++    -- ** MLModel+    MLModel (MLModel'),+    newMLModel,++    -- ** PerformanceMetrics+    PerformanceMetrics (PerformanceMetrics'),+    newPerformanceMetrics,++    -- ** Prediction+    Prediction (Prediction'),+    newPrediction,++    -- ** RDSDataSpec+    RDSDataSpec (RDSDataSpec'),+    newRDSDataSpec,++    -- ** RDSDatabase+    RDSDatabase (RDSDatabase'),+    newRDSDatabase,++    -- ** RDSDatabaseCredentials+    RDSDatabaseCredentials (RDSDatabaseCredentials'),+    newRDSDatabaseCredentials,++    -- ** RDSMetadata+    RDSMetadata (RDSMetadata'),+    newRDSMetadata,++    -- ** RealtimeEndpointInfo+    RealtimeEndpointInfo (RealtimeEndpointInfo'),+    newRealtimeEndpointInfo,++    -- ** RedshiftDataSpec+    RedshiftDataSpec (RedshiftDataSpec'),+    newRedshiftDataSpec,++    -- ** RedshiftDatabase+    RedshiftDatabase (RedshiftDatabase'),+    newRedshiftDatabase,++    -- ** RedshiftDatabaseCredentials+    RedshiftDatabaseCredentials (RedshiftDatabaseCredentials'),+    newRedshiftDatabaseCredentials,++    -- ** RedshiftMetadata+    RedshiftMetadata (RedshiftMetadata'),+    newRedshiftMetadata,++    -- ** S3DataSpec+    S3DataSpec (S3DataSpec'),+    newS3DataSpec,++    -- ** Tag+    Tag (Tag'),+    newTag,+  )+where++import Amazonka.MachineLearning.AddTags+import Amazonka.MachineLearning.CreateBatchPrediction+import Amazonka.MachineLearning.CreateDataSourceFromRDS+import Amazonka.MachineLearning.CreateDataSourceFromRedshift+import Amazonka.MachineLearning.CreateDataSourceFromS3+import Amazonka.MachineLearning.CreateEvaluation+import Amazonka.MachineLearning.CreateMLModel+import Amazonka.MachineLearning.CreateRealtimeEndpoint+import Amazonka.MachineLearning.DeleteBatchPrediction+import Amazonka.MachineLearning.DeleteDataSource+import Amazonka.MachineLearning.DeleteEvaluation+import Amazonka.MachineLearning.DeleteMLModel+import Amazonka.MachineLearning.DeleteRealtimeEndpoint+import Amazonka.MachineLearning.DeleteTags+import Amazonka.MachineLearning.DescribeBatchPredictions+import Amazonka.MachineLearning.DescribeDataSources+import Amazonka.MachineLearning.DescribeEvaluations+import Amazonka.MachineLearning.DescribeMLModels+import Amazonka.MachineLearning.DescribeTags+import Amazonka.MachineLearning.GetBatchPrediction+import Amazonka.MachineLearning.GetDataSource+import Amazonka.MachineLearning.GetEvaluation+import Amazonka.MachineLearning.GetMLModel+import Amazonka.MachineLearning.Lens+import Amazonka.MachineLearning.Predict+import Amazonka.MachineLearning.Types+import Amazonka.MachineLearning.UpdateBatchPrediction+import Amazonka.MachineLearning.UpdateDataSource+import Amazonka.MachineLearning.UpdateEvaluation+import Amazonka.MachineLearning.UpdateMLModel+import Amazonka.MachineLearning.Waiters++-- $errors+-- Error matchers are designed for use with the functions provided by+-- <http://hackage.haskell.org/package/lens/docs/Control-Exception-Lens.html Control.Exception.Lens>.+-- This allows catching (and rethrowing) service specific errors returned+-- by 'MachineLearning'.++-- $operations+-- Some AWS operations return results that are incomplete and require subsequent+-- requests in order to obtain the entire result set. The process of sending+-- subsequent requests to continue where a previous request left off is called+-- pagination. For example, the 'ListObjects' operation of Amazon S3 returns up to+-- 1000 objects at a time, and you must send subsequent requests with the+-- appropriate Marker in order to retrieve the next page of results.+--+-- Operations that have an 'AWSPager' instance can transparently perform subsequent+-- requests, correctly setting Markers and other request facets to iterate through+-- the entire result set of a truncated API operation. Operations which support+-- this have an additional note in the documentation.+--+-- Many operations have the ability to filter results on the server side. See the+-- individual operation parameters for details.++-- $waiters+-- Waiters poll by repeatedly sending a request until some remote success condition+-- configured by the 'Wait' specification is fulfilled. The 'Wait' specification+-- determines how many attempts should be made, in addition to delay and retry strategies.

@@ -0,0 +1,219 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.AddTags+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Adds one or more tags to an object, up to a limit of 10. Each tag+-- consists of a key and an optional value. If you add a tag using a key+-- that is already associated with the ML object, @AddTags@ updates the+-- tag\'s value.+module Amazonka.MachineLearning.AddTags+  ( -- * Creating a Request+    AddTags (..),+    newAddTags,++    -- * Request Lenses+    addTags_tags,+    addTags_resourceId,+    addTags_resourceType,++    -- * Destructuring the Response+    AddTagsResponse (..),+    newAddTagsResponse,++    -- * Response Lenses+    addTagsResponse_resourceId,+    addTagsResponse_resourceType,+    addTagsResponse_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newAddTags' smart constructor.+data AddTags = AddTags'+  { -- | The key-value pairs to use to create tags. If you specify a key without+    -- specifying a value, Amazon ML creates a tag with the specified key and a+    -- value of null.+    tags :: [Tag],+    -- | The ID of the ML object to tag. For example, @exampleModelId@.+    resourceId :: Prelude.Text,+    -- | The type of the ML object to tag.+    resourceType :: TaggableResourceType+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'AddTags' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'tags', 'addTags_tags' - The key-value pairs to use to create tags. If you specify a key without+-- specifying a value, Amazon ML creates a tag with the specified key and a+-- value of null.+--+-- 'resourceId', 'addTags_resourceId' - The ID of the ML object to tag. For example, @exampleModelId@.+--+-- 'resourceType', 'addTags_resourceType' - The type of the ML object to tag.+newAddTags ::+  -- | 'resourceId'+  Prelude.Text ->+  -- | 'resourceType'+  TaggableResourceType ->+  AddTags+newAddTags pResourceId_ pResourceType_ =+  AddTags'+    { tags = Prelude.mempty,+      resourceId = pResourceId_,+      resourceType = pResourceType_+    }++-- | The key-value pairs to use to create tags. If you specify a key without+-- specifying a value, Amazon ML creates a tag with the specified key and a+-- value of null.+addTags_tags :: Lens.Lens' AddTags [Tag]+addTags_tags = Lens.lens (\AddTags' {tags} -> tags) (\s@AddTags' {} a -> s {tags = a} :: AddTags) Prelude.. Lens.coerced++-- | The ID of the ML object to tag. For example, @exampleModelId@.+addTags_resourceId :: Lens.Lens' AddTags Prelude.Text+addTags_resourceId = Lens.lens (\AddTags' {resourceId} -> resourceId) (\s@AddTags' {} a -> s {resourceId = a} :: AddTags)++-- | The type of the ML object to tag.+addTags_resourceType :: Lens.Lens' AddTags TaggableResourceType+addTags_resourceType = Lens.lens (\AddTags' {resourceType} -> resourceType) (\s@AddTags' {} a -> s {resourceType = a} :: AddTags)++instance Core.AWSRequest AddTags where+  type AWSResponse AddTags = AddTagsResponse+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          AddTagsResponse'+            Prelude.<$> (x Data..?> "ResourceId")+            Prelude.<*> (x Data..?> "ResourceType")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance Prelude.Hashable AddTags where+  hashWithSalt _salt AddTags' {..} =+    _salt+      `Prelude.hashWithSalt` tags+      `Prelude.hashWithSalt` resourceId+      `Prelude.hashWithSalt` resourceType++instance Prelude.NFData AddTags where+  rnf AddTags' {..} =+    Prelude.rnf tags+      `Prelude.seq` Prelude.rnf resourceId+      `Prelude.seq` Prelude.rnf resourceType++instance Data.ToHeaders AddTags where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ("AmazonML_20141212.AddTags" :: Prelude.ByteString),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON AddTags where+  toJSON AddTags' {..} =+    Data.object+      ( Prelude.catMaybes+          [ Prelude.Just ("Tags" Data..= tags),+            Prelude.Just ("ResourceId" Data..= resourceId),+            Prelude.Just ("ResourceType" Data..= resourceType)+          ]+      )++instance Data.ToPath AddTags where+  toPath = Prelude.const "/"++instance Data.ToQuery AddTags where+  toQuery = Prelude.const Prelude.mempty++-- | Amazon ML returns the following elements.+--+-- /See:/ 'newAddTagsResponse' smart constructor.+data AddTagsResponse = AddTagsResponse'+  { -- | The ID of the ML object that was tagged.+    resourceId :: Prelude.Maybe Prelude.Text,+    -- | The type of the ML object that was tagged.+    resourceType :: Prelude.Maybe TaggableResourceType,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'AddTagsResponse' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'resourceId', 'addTagsResponse_resourceId' - The ID of the ML object that was tagged.+--+-- 'resourceType', 'addTagsResponse_resourceType' - The type of the ML object that was tagged.+--+-- 'httpStatus', 'addTagsResponse_httpStatus' - The response's http status code.+newAddTagsResponse ::+  -- | 'httpStatus'+  Prelude.Int ->+  AddTagsResponse+newAddTagsResponse pHttpStatus_ =+  AddTagsResponse'+    { resourceId = Prelude.Nothing,+      resourceType = Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | The ID of the ML object that was tagged.+addTagsResponse_resourceId :: Lens.Lens' AddTagsResponse (Prelude.Maybe Prelude.Text)+addTagsResponse_resourceId = Lens.lens (\AddTagsResponse' {resourceId} -> resourceId) (\s@AddTagsResponse' {} a -> s {resourceId = a} :: AddTagsResponse)++-- | The type of the ML object that was tagged.+addTagsResponse_resourceType :: Lens.Lens' AddTagsResponse (Prelude.Maybe TaggableResourceType)+addTagsResponse_resourceType = Lens.lens (\AddTagsResponse' {resourceType} -> resourceType) (\s@AddTagsResponse' {} a -> s {resourceType = a} :: AddTagsResponse)++-- | The response's http status code.+addTagsResponse_httpStatus :: Lens.Lens' AddTagsResponse Prelude.Int+addTagsResponse_httpStatus = Lens.lens (\AddTagsResponse' {httpStatus} -> httpStatus) (\s@AddTagsResponse' {} a -> s {httpStatus = a} :: AddTagsResponse)++instance Prelude.NFData AddTagsResponse where+  rnf AddTagsResponse' {..} =+    Prelude.rnf resourceId+      `Prelude.seq` Prelude.rnf resourceType+      `Prelude.seq` Prelude.rnf httpStatus

@@ -0,0 +1,299 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.CreateBatchPrediction+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Generates predictions for a group of observations. The observations to+-- process exist in one or more data files referenced by a @DataSource@.+-- This operation creates a new @BatchPrediction@, and uses an @MLModel@+-- and the data files referenced by the @DataSource@ as information+-- sources.+--+-- @CreateBatchPrediction@ is an asynchronous operation. In response to+-- @CreateBatchPrediction@, Amazon Machine Learning (Amazon ML) immediately+-- returns and sets the @BatchPrediction@ status to @PENDING@. After the+-- @BatchPrediction@ completes, Amazon ML sets the status to @COMPLETED@.+--+-- You can poll for status updates by using the GetBatchPrediction+-- operation and checking the @Status@ parameter of the result. After the+-- @COMPLETED@ status appears, the results are available in the location+-- specified by the @OutputUri@ parameter.+module Amazonka.MachineLearning.CreateBatchPrediction+  ( -- * Creating a Request+    CreateBatchPrediction (..),+    newCreateBatchPrediction,++    -- * Request Lenses+    createBatchPrediction_batchPredictionName,+    createBatchPrediction_batchPredictionId,+    createBatchPrediction_mLModelId,+    createBatchPrediction_batchPredictionDataSourceId,+    createBatchPrediction_outputUri,++    -- * Destructuring the Response+    CreateBatchPredictionResponse (..),+    newCreateBatchPredictionResponse,++    -- * Response Lenses+    createBatchPredictionResponse_batchPredictionId,+    createBatchPredictionResponse_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newCreateBatchPrediction' smart constructor.+data CreateBatchPrediction = CreateBatchPrediction'+  { -- | A user-supplied name or description of the @BatchPrediction@.+    -- @BatchPredictionName@ can only use the UTF-8 character set.+    batchPredictionName :: Prelude.Maybe Prelude.Text,+    -- | A user-supplied ID that uniquely identifies the @BatchPrediction@.+    batchPredictionId :: Prelude.Text,+    -- | The ID of the @MLModel@ that will generate predictions for the group of+    -- observations.+    mLModelId :: Prelude.Text,+    -- | The ID of the @DataSource@ that points to the group of observations to+    -- predict.+    batchPredictionDataSourceId :: Prelude.Text,+    -- | The location of an Amazon Simple Storage Service (Amazon S3) bucket or+    -- directory to store the batch prediction results. The following+    -- substrings are not allowed in the @s3 key@ portion of the @outputURI@+    -- field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'.+    --+    -- Amazon ML needs permissions to store and retrieve the logs on your+    -- behalf. For information about how to set permissions, see the+    -- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+    outputUri :: Prelude.Text+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateBatchPrediction' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'batchPredictionName', 'createBatchPrediction_batchPredictionName' - A user-supplied name or description of the @BatchPrediction@.+-- @BatchPredictionName@ can only use the UTF-8 character set.+--+-- 'batchPredictionId', 'createBatchPrediction_batchPredictionId' - A user-supplied ID that uniquely identifies the @BatchPrediction@.+--+-- 'mLModelId', 'createBatchPrediction_mLModelId' - The ID of the @MLModel@ that will generate predictions for the group of+-- observations.+--+-- 'batchPredictionDataSourceId', 'createBatchPrediction_batchPredictionDataSourceId' - The ID of the @DataSource@ that points to the group of observations to+-- predict.+--+-- 'outputUri', 'createBatchPrediction_outputUri' - The location of an Amazon Simple Storage Service (Amazon S3) bucket or+-- directory to store the batch prediction results. The following+-- substrings are not allowed in the @s3 key@ portion of the @outputURI@+-- field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'.+--+-- Amazon ML needs permissions to store and retrieve the logs on your+-- behalf. For information about how to set permissions, see the+-- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+newCreateBatchPrediction ::+  -- | 'batchPredictionId'+  Prelude.Text ->+  -- | 'mLModelId'+  Prelude.Text ->+  -- | 'batchPredictionDataSourceId'+  Prelude.Text ->+  -- | 'outputUri'+  Prelude.Text ->+  CreateBatchPrediction+newCreateBatchPrediction+  pBatchPredictionId_+  pMLModelId_+  pBatchPredictionDataSourceId_+  pOutputUri_ =+    CreateBatchPrediction'+      { batchPredictionName =+          Prelude.Nothing,+        batchPredictionId = pBatchPredictionId_,+        mLModelId = pMLModelId_,+        batchPredictionDataSourceId =+          pBatchPredictionDataSourceId_,+        outputUri = pOutputUri_+      }++-- | A user-supplied name or description of the @BatchPrediction@.+-- @BatchPredictionName@ can only use the UTF-8 character set.+createBatchPrediction_batchPredictionName :: Lens.Lens' CreateBatchPrediction (Prelude.Maybe Prelude.Text)+createBatchPrediction_batchPredictionName = Lens.lens (\CreateBatchPrediction' {batchPredictionName} -> batchPredictionName) (\s@CreateBatchPrediction' {} a -> s {batchPredictionName = a} :: CreateBatchPrediction)++-- | A user-supplied ID that uniquely identifies the @BatchPrediction@.+createBatchPrediction_batchPredictionId :: Lens.Lens' CreateBatchPrediction Prelude.Text+createBatchPrediction_batchPredictionId = Lens.lens (\CreateBatchPrediction' {batchPredictionId} -> batchPredictionId) (\s@CreateBatchPrediction' {} a -> s {batchPredictionId = a} :: CreateBatchPrediction)++-- | The ID of the @MLModel@ that will generate predictions for the group of+-- observations.+createBatchPrediction_mLModelId :: Lens.Lens' CreateBatchPrediction Prelude.Text+createBatchPrediction_mLModelId = Lens.lens (\CreateBatchPrediction' {mLModelId} -> mLModelId) (\s@CreateBatchPrediction' {} a -> s {mLModelId = a} :: CreateBatchPrediction)++-- | The ID of the @DataSource@ that points to the group of observations to+-- predict.+createBatchPrediction_batchPredictionDataSourceId :: Lens.Lens' CreateBatchPrediction Prelude.Text+createBatchPrediction_batchPredictionDataSourceId = Lens.lens (\CreateBatchPrediction' {batchPredictionDataSourceId} -> batchPredictionDataSourceId) (\s@CreateBatchPrediction' {} a -> s {batchPredictionDataSourceId = a} :: CreateBatchPrediction)++-- | The location of an Amazon Simple Storage Service (Amazon S3) bucket or+-- directory to store the batch prediction results. The following+-- substrings are not allowed in the @s3 key@ portion of the @outputURI@+-- field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'.+--+-- Amazon ML needs permissions to store and retrieve the logs on your+-- behalf. For information about how to set permissions, see the+-- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+createBatchPrediction_outputUri :: Lens.Lens' CreateBatchPrediction Prelude.Text+createBatchPrediction_outputUri = Lens.lens (\CreateBatchPrediction' {outputUri} -> outputUri) (\s@CreateBatchPrediction' {} a -> s {outputUri = a} :: CreateBatchPrediction)++instance Core.AWSRequest CreateBatchPrediction where+  type+    AWSResponse CreateBatchPrediction =+      CreateBatchPredictionResponse+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          CreateBatchPredictionResponse'+            Prelude.<$> (x Data..?> "BatchPredictionId")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance Prelude.Hashable CreateBatchPrediction where+  hashWithSalt _salt CreateBatchPrediction' {..} =+    _salt+      `Prelude.hashWithSalt` batchPredictionName+      `Prelude.hashWithSalt` batchPredictionId+      `Prelude.hashWithSalt` mLModelId+      `Prelude.hashWithSalt` batchPredictionDataSourceId+      `Prelude.hashWithSalt` outputUri++instance Prelude.NFData CreateBatchPrediction where+  rnf CreateBatchPrediction' {..} =+    Prelude.rnf batchPredictionName+      `Prelude.seq` Prelude.rnf batchPredictionId+      `Prelude.seq` Prelude.rnf mLModelId+      `Prelude.seq` Prelude.rnf batchPredictionDataSourceId+      `Prelude.seq` Prelude.rnf outputUri++instance Data.ToHeaders CreateBatchPrediction where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ( "AmazonML_20141212.CreateBatchPrediction" ::+                          Prelude.ByteString+                      ),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON CreateBatchPrediction where+  toJSON CreateBatchPrediction' {..} =+    Data.object+      ( Prelude.catMaybes+          [ ("BatchPredictionName" Data..=)+              Prelude.<$> batchPredictionName,+            Prelude.Just+              ("BatchPredictionId" Data..= batchPredictionId),+            Prelude.Just ("MLModelId" Data..= mLModelId),+            Prelude.Just+              ( "BatchPredictionDataSourceId"+                  Data..= batchPredictionDataSourceId+              ),+            Prelude.Just ("OutputUri" Data..= outputUri)+          ]+      )++instance Data.ToPath CreateBatchPrediction where+  toPath = Prelude.const "/"++instance Data.ToQuery CreateBatchPrediction where+  toQuery = Prelude.const Prelude.mempty++-- | Represents the output of a @CreateBatchPrediction@ operation, and is an+-- acknowledgement that Amazon ML received the request.+--+-- The @CreateBatchPrediction@ operation is asynchronous. You can poll for+-- status updates by using the @>GetBatchPrediction@ operation and checking+-- the @Status@ parameter of the result.+--+-- /See:/ 'newCreateBatchPredictionResponse' smart constructor.+data CreateBatchPredictionResponse = CreateBatchPredictionResponse'+  { -- | A user-supplied ID that uniquely identifies the @BatchPrediction@. This+    -- value is identical to the value of the @BatchPredictionId@ in the+    -- request.+    batchPredictionId :: Prelude.Maybe Prelude.Text,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateBatchPredictionResponse' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'batchPredictionId', 'createBatchPredictionResponse_batchPredictionId' - A user-supplied ID that uniquely identifies the @BatchPrediction@. This+-- value is identical to the value of the @BatchPredictionId@ in the+-- request.+--+-- 'httpStatus', 'createBatchPredictionResponse_httpStatus' - The response's http status code.+newCreateBatchPredictionResponse ::+  -- | 'httpStatus'+  Prelude.Int ->+  CreateBatchPredictionResponse+newCreateBatchPredictionResponse pHttpStatus_ =+  CreateBatchPredictionResponse'+    { batchPredictionId =+        Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | A user-supplied ID that uniquely identifies the @BatchPrediction@. This+-- value is identical to the value of the @BatchPredictionId@ in the+-- request.+createBatchPredictionResponse_batchPredictionId :: Lens.Lens' CreateBatchPredictionResponse (Prelude.Maybe Prelude.Text)+createBatchPredictionResponse_batchPredictionId = Lens.lens (\CreateBatchPredictionResponse' {batchPredictionId} -> batchPredictionId) (\s@CreateBatchPredictionResponse' {} a -> s {batchPredictionId = a} :: CreateBatchPredictionResponse)++-- | The response's http status code.+createBatchPredictionResponse_httpStatus :: Lens.Lens' CreateBatchPredictionResponse Prelude.Int+createBatchPredictionResponse_httpStatus = Lens.lens (\CreateBatchPredictionResponse' {httpStatus} -> httpStatus) (\s@CreateBatchPredictionResponse' {} a -> s {httpStatus = a} :: CreateBatchPredictionResponse)++instance Prelude.NFData CreateBatchPredictionResponse where+  rnf CreateBatchPredictionResponse' {..} =+    Prelude.rnf batchPredictionId+      `Prelude.seq` Prelude.rnf httpStatus

@@ -0,0 +1,426 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.CreateDataSourceFromRDS+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Creates a @DataSource@ object from an+-- <http://aws.amazon.com/rds/ Amazon Relational Database Service> (Amazon+-- RDS). A @DataSource@ references data that can be used to perform+-- @CreateMLModel@, @CreateEvaluation@, or @CreateBatchPrediction@+-- operations.+--+-- @CreateDataSourceFromRDS@ is an asynchronous operation. In response to+-- @CreateDataSourceFromRDS@, Amazon Machine Learning (Amazon ML)+-- immediately returns and sets the @DataSource@ status to @PENDING@. After+-- the @DataSource@ is created and ready for use, Amazon ML sets the+-- @Status@ parameter to @COMPLETED@. @DataSource@ in the @COMPLETED@ or+-- @PENDING@ state can be used only to perform @>CreateMLModel@>,+-- @CreateEvaluation@, or @CreateBatchPrediction@ operations.+--+-- If Amazon ML cannot accept the input source, it sets the @Status@+-- parameter to @FAILED@ and includes an error message in the @Message@+-- attribute of the @GetDataSource@ operation response.+module Amazonka.MachineLearning.CreateDataSourceFromRDS+  ( -- * Creating a Request+    CreateDataSourceFromRDS (..),+    newCreateDataSourceFromRDS,++    -- * Request Lenses+    createDataSourceFromRDS_computeStatistics,+    createDataSourceFromRDS_dataSourceName,+    createDataSourceFromRDS_dataSourceId,+    createDataSourceFromRDS_rDSData,+    createDataSourceFromRDS_roleARN,++    -- * Destructuring the Response+    CreateDataSourceFromRDSResponse (..),+    newCreateDataSourceFromRDSResponse,++    -- * Response Lenses+    createDataSourceFromRDSResponse_dataSourceId,+    createDataSourceFromRDSResponse_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newCreateDataSourceFromRDS' smart constructor.+data CreateDataSourceFromRDS = CreateDataSourceFromRDS'+  { -- | The compute statistics for a @DataSource@. The statistics are generated+    -- from the observation data referenced by a @DataSource@. Amazon ML uses+    -- the statistics internally during @MLModel@ training. This parameter must+    -- be set to @true@ if the DataSource needs to be used for @MLModel@+    -- training.+    computeStatistics :: Prelude.Maybe Prelude.Bool,+    -- | A user-supplied name or description of the @DataSource@.+    dataSourceName :: Prelude.Maybe Prelude.Text,+    -- | A user-supplied ID that uniquely identifies the @DataSource@. Typically,+    -- an Amazon Resource Number (ARN) becomes the ID for a @DataSource@.+    dataSourceId :: Prelude.Text,+    -- | The data specification of an Amazon RDS @DataSource@:+    --+    -- -   DatabaseInformation -+    --+    --     -   @DatabaseName@ - The name of the Amazon RDS database.+    --+    --     -   @InstanceIdentifier @ - A unique identifier for the Amazon RDS+    --         database instance.+    --+    -- -   DatabaseCredentials - AWS Identity and Access Management (IAM)+    --     credentials that are used to connect to the Amazon RDS database.+    --+    -- -   ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by+    --     an EC2 instance to carry out the copy task from Amazon RDS to Amazon+    --     Simple Storage Service (Amazon S3). For more information, see+    --     <https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>+    --     for data pipelines.+    --+    -- -   ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS+    --     Data Pipeline service to monitor the progress of the copy task from+    --     Amazon RDS to Amazon S3. For more information, see+    --     <https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>+    --     for data pipelines.+    --+    -- -   SecurityInfo - The security information to use to access an RDS DB+    --     instance. You need to set up appropriate ingress rules for the+    --     security entity IDs provided to allow access to the Amazon RDS+    --     instance. Specify a [@SubnetId@, @SecurityGroupIds@] pair for a+    --     VPC-based RDS DB instance.+    --+    -- -   SelectSqlQuery - A query that is used to retrieve the observation+    --     data for the @Datasource@.+    --+    -- -   S3StagingLocation - The Amazon S3 location for staging Amazon RDS+    --     data. The data retrieved from Amazon RDS using @SelectSqlQuery@ is+    --     stored in this location.+    --+    -- -   DataSchemaUri - The Amazon S3 location of the @DataSchema@.+    --+    -- -   DataSchema - A JSON string representing the schema. This is not+    --     required if @DataSchemaUri@ is specified.+    --+    -- -   DataRearrangement - A JSON string that represents the splitting and+    --     rearrangement requirements for the @Datasource@.+    --+    --     Sample -+    --     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+    rDSData :: RDSDataSpec,+    -- | The role that Amazon ML assumes on behalf of the user to create and+    -- activate a data pipeline in the user\'s account and copy data using the+    -- @SelectSqlQuery@ query from Amazon RDS to Amazon S3.+    roleARN :: Prelude.Text+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateDataSourceFromRDS' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'computeStatistics', 'createDataSourceFromRDS_computeStatistics' - The compute statistics for a @DataSource@. The statistics are generated+-- from the observation data referenced by a @DataSource@. Amazon ML uses+-- the statistics internally during @MLModel@ training. This parameter must+-- be set to @true@ if the DataSource needs to be used for @MLModel@+-- training.+--+-- 'dataSourceName', 'createDataSourceFromRDS_dataSourceName' - A user-supplied name or description of the @DataSource@.+--+-- 'dataSourceId', 'createDataSourceFromRDS_dataSourceId' - A user-supplied ID that uniquely identifies the @DataSource@. Typically,+-- an Amazon Resource Number (ARN) becomes the ID for a @DataSource@.+--+-- 'rDSData', 'createDataSourceFromRDS_rDSData' - The data specification of an Amazon RDS @DataSource@:+--+-- -   DatabaseInformation -+--+--     -   @DatabaseName@ - The name of the Amazon RDS database.+--+--     -   @InstanceIdentifier @ - A unique identifier for the Amazon RDS+--         database instance.+--+-- -   DatabaseCredentials - AWS Identity and Access Management (IAM)+--     credentials that are used to connect to the Amazon RDS database.+--+-- -   ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by+--     an EC2 instance to carry out the copy task from Amazon RDS to Amazon+--     Simple Storage Service (Amazon S3). For more information, see+--     <https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>+--     for data pipelines.+--+-- -   ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS+--     Data Pipeline service to monitor the progress of the copy task from+--     Amazon RDS to Amazon S3. For more information, see+--     <https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>+--     for data pipelines.+--+-- -   SecurityInfo - The security information to use to access an RDS DB+--     instance. You need to set up appropriate ingress rules for the+--     security entity IDs provided to allow access to the Amazon RDS+--     instance. Specify a [@SubnetId@, @SecurityGroupIds@] pair for a+--     VPC-based RDS DB instance.+--+-- -   SelectSqlQuery - A query that is used to retrieve the observation+--     data for the @Datasource@.+--+-- -   S3StagingLocation - The Amazon S3 location for staging Amazon RDS+--     data. The data retrieved from Amazon RDS using @SelectSqlQuery@ is+--     stored in this location.+--+-- -   DataSchemaUri - The Amazon S3 location of the @DataSchema@.+--+-- -   DataSchema - A JSON string representing the schema. This is not+--     required if @DataSchemaUri@ is specified.+--+-- -   DataRearrangement - A JSON string that represents the splitting and+--     rearrangement requirements for the @Datasource@.+--+--     Sample -+--     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+--+-- 'roleARN', 'createDataSourceFromRDS_roleARN' - The role that Amazon ML assumes on behalf of the user to create and+-- activate a data pipeline in the user\'s account and copy data using the+-- @SelectSqlQuery@ query from Amazon RDS to Amazon S3.+newCreateDataSourceFromRDS ::+  -- | 'dataSourceId'+  Prelude.Text ->+  -- | 'rDSData'+  RDSDataSpec ->+  -- | 'roleARN'+  Prelude.Text ->+  CreateDataSourceFromRDS+newCreateDataSourceFromRDS+  pDataSourceId_+  pRDSData_+  pRoleARN_ =+    CreateDataSourceFromRDS'+      { computeStatistics =+          Prelude.Nothing,+        dataSourceName = Prelude.Nothing,+        dataSourceId = pDataSourceId_,+        rDSData = pRDSData_,+        roleARN = pRoleARN_+      }++-- | The compute statistics for a @DataSource@. The statistics are generated+-- from the observation data referenced by a @DataSource@. Amazon ML uses+-- the statistics internally during @MLModel@ training. This parameter must+-- be set to @true@ if the DataSource needs to be used for @MLModel@+-- training.+createDataSourceFromRDS_computeStatistics :: Lens.Lens' CreateDataSourceFromRDS (Prelude.Maybe Prelude.Bool)+createDataSourceFromRDS_computeStatistics = Lens.lens (\CreateDataSourceFromRDS' {computeStatistics} -> computeStatistics) (\s@CreateDataSourceFromRDS' {} a -> s {computeStatistics = a} :: CreateDataSourceFromRDS)++-- | A user-supplied name or description of the @DataSource@.+createDataSourceFromRDS_dataSourceName :: Lens.Lens' CreateDataSourceFromRDS (Prelude.Maybe Prelude.Text)+createDataSourceFromRDS_dataSourceName = Lens.lens (\CreateDataSourceFromRDS' {dataSourceName} -> dataSourceName) (\s@CreateDataSourceFromRDS' {} a -> s {dataSourceName = a} :: CreateDataSourceFromRDS)++-- | A user-supplied ID that uniquely identifies the @DataSource@. Typically,+-- an Amazon Resource Number (ARN) becomes the ID for a @DataSource@.+createDataSourceFromRDS_dataSourceId :: Lens.Lens' CreateDataSourceFromRDS Prelude.Text+createDataSourceFromRDS_dataSourceId = Lens.lens (\CreateDataSourceFromRDS' {dataSourceId} -> dataSourceId) (\s@CreateDataSourceFromRDS' {} a -> s {dataSourceId = a} :: CreateDataSourceFromRDS)++-- | The data specification of an Amazon RDS @DataSource@:+--+-- -   DatabaseInformation -+--+--     -   @DatabaseName@ - The name of the Amazon RDS database.+--+--     -   @InstanceIdentifier @ - A unique identifier for the Amazon RDS+--         database instance.+--+-- -   DatabaseCredentials - AWS Identity and Access Management (IAM)+--     credentials that are used to connect to the Amazon RDS database.+--+-- -   ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by+--     an EC2 instance to carry out the copy task from Amazon RDS to Amazon+--     Simple Storage Service (Amazon S3). For more information, see+--     <https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>+--     for data pipelines.+--+-- -   ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS+--     Data Pipeline service to monitor the progress of the copy task from+--     Amazon RDS to Amazon S3. For more information, see+--     <https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>+--     for data pipelines.+--+-- -   SecurityInfo - The security information to use to access an RDS DB+--     instance. You need to set up appropriate ingress rules for the+--     security entity IDs provided to allow access to the Amazon RDS+--     instance. Specify a [@SubnetId@, @SecurityGroupIds@] pair for a+--     VPC-based RDS DB instance.+--+-- -   SelectSqlQuery - A query that is used to retrieve the observation+--     data for the @Datasource@.+--+-- -   S3StagingLocation - The Amazon S3 location for staging Amazon RDS+--     data. The data retrieved from Amazon RDS using @SelectSqlQuery@ is+--     stored in this location.+--+-- -   DataSchemaUri - The Amazon S3 location of the @DataSchema@.+--+-- -   DataSchema - A JSON string representing the schema. This is not+--     required if @DataSchemaUri@ is specified.+--+-- -   DataRearrangement - A JSON string that represents the splitting and+--     rearrangement requirements for the @Datasource@.+--+--     Sample -+--     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+createDataSourceFromRDS_rDSData :: Lens.Lens' CreateDataSourceFromRDS RDSDataSpec+createDataSourceFromRDS_rDSData = Lens.lens (\CreateDataSourceFromRDS' {rDSData} -> rDSData) (\s@CreateDataSourceFromRDS' {} a -> s {rDSData = a} :: CreateDataSourceFromRDS)++-- | The role that Amazon ML assumes on behalf of the user to create and+-- activate a data pipeline in the user\'s account and copy data using the+-- @SelectSqlQuery@ query from Amazon RDS to Amazon S3.+createDataSourceFromRDS_roleARN :: Lens.Lens' CreateDataSourceFromRDS Prelude.Text+createDataSourceFromRDS_roleARN = Lens.lens (\CreateDataSourceFromRDS' {roleARN} -> roleARN) (\s@CreateDataSourceFromRDS' {} a -> s {roleARN = a} :: CreateDataSourceFromRDS)++instance Core.AWSRequest CreateDataSourceFromRDS where+  type+    AWSResponse CreateDataSourceFromRDS =+      CreateDataSourceFromRDSResponse+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          CreateDataSourceFromRDSResponse'+            Prelude.<$> (x Data..?> "DataSourceId")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance Prelude.Hashable CreateDataSourceFromRDS where+  hashWithSalt _salt CreateDataSourceFromRDS' {..} =+    _salt+      `Prelude.hashWithSalt` computeStatistics+      `Prelude.hashWithSalt` dataSourceName+      `Prelude.hashWithSalt` dataSourceId+      `Prelude.hashWithSalt` rDSData+      `Prelude.hashWithSalt` roleARN++instance Prelude.NFData CreateDataSourceFromRDS where+  rnf CreateDataSourceFromRDS' {..} =+    Prelude.rnf computeStatistics+      `Prelude.seq` Prelude.rnf dataSourceName+      `Prelude.seq` Prelude.rnf dataSourceId+      `Prelude.seq` Prelude.rnf rDSData+      `Prelude.seq` Prelude.rnf roleARN++instance Data.ToHeaders CreateDataSourceFromRDS where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ( "AmazonML_20141212.CreateDataSourceFromRDS" ::+                          Prelude.ByteString+                      ),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON CreateDataSourceFromRDS where+  toJSON CreateDataSourceFromRDS' {..} =+    Data.object+      ( Prelude.catMaybes+          [ ("ComputeStatistics" Data..=)+              Prelude.<$> computeStatistics,+            ("DataSourceName" Data..=)+              Prelude.<$> dataSourceName,+            Prelude.Just ("DataSourceId" Data..= dataSourceId),+            Prelude.Just ("RDSData" Data..= rDSData),+            Prelude.Just ("RoleARN" Data..= roleARN)+          ]+      )++instance Data.ToPath CreateDataSourceFromRDS where+  toPath = Prelude.const "/"++instance Data.ToQuery CreateDataSourceFromRDS where+  toQuery = Prelude.const Prelude.mempty++-- | Represents the output of a @CreateDataSourceFromRDS@ operation, and is+-- an acknowledgement that Amazon ML received the request.+--+-- The @CreateDataSourceFromRDS@> operation is asynchronous. You can poll+-- for updates by using the @GetBatchPrediction@ operation and checking the+-- @Status@ parameter. You can inspect the @Message@ when @Status@ shows up+-- as @FAILED@. You can also check the progress of the copy operation by+-- going to the @DataPipeline@ console and looking up the pipeline using+-- the @pipelineId @ from the describe call.+--+-- /See:/ 'newCreateDataSourceFromRDSResponse' smart constructor.+data CreateDataSourceFromRDSResponse = CreateDataSourceFromRDSResponse'+  { -- | A user-supplied ID that uniquely identifies the datasource. This value+    -- should be identical to the value of the @DataSourceID@ in the request.+    dataSourceId :: Prelude.Maybe Prelude.Text,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateDataSourceFromRDSResponse' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'dataSourceId', 'createDataSourceFromRDSResponse_dataSourceId' - A user-supplied ID that uniquely identifies the datasource. This value+-- should be identical to the value of the @DataSourceID@ in the request.+--+-- 'httpStatus', 'createDataSourceFromRDSResponse_httpStatus' - The response's http status code.+newCreateDataSourceFromRDSResponse ::+  -- | 'httpStatus'+  Prelude.Int ->+  CreateDataSourceFromRDSResponse+newCreateDataSourceFromRDSResponse pHttpStatus_ =+  CreateDataSourceFromRDSResponse'+    { dataSourceId =+        Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | A user-supplied ID that uniquely identifies the datasource. This value+-- should be identical to the value of the @DataSourceID@ in the request.+createDataSourceFromRDSResponse_dataSourceId :: Lens.Lens' CreateDataSourceFromRDSResponse (Prelude.Maybe Prelude.Text)+createDataSourceFromRDSResponse_dataSourceId = Lens.lens (\CreateDataSourceFromRDSResponse' {dataSourceId} -> dataSourceId) (\s@CreateDataSourceFromRDSResponse' {} a -> s {dataSourceId = a} :: CreateDataSourceFromRDSResponse)++-- | The response's http status code.+createDataSourceFromRDSResponse_httpStatus :: Lens.Lens' CreateDataSourceFromRDSResponse Prelude.Int+createDataSourceFromRDSResponse_httpStatus = Lens.lens (\CreateDataSourceFromRDSResponse' {httpStatus} -> httpStatus) (\s@CreateDataSourceFromRDSResponse' {} a -> s {httpStatus = a} :: CreateDataSourceFromRDSResponse)++instance+  Prelude.NFData+    CreateDataSourceFromRDSResponse+  where+  rnf CreateDataSourceFromRDSResponse' {..} =+    Prelude.rnf dataSourceId+      `Prelude.seq` Prelude.rnf httpStatus

@@ -0,0 +1,410 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.CreateDataSourceFromRedshift+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Creates a @DataSource@ from a database hosted on an Amazon Redshift+-- cluster. A @DataSource@ references data that can be used to perform+-- either @CreateMLModel@, @CreateEvaluation@, or @CreateBatchPrediction@+-- operations.+--+-- @CreateDataSourceFromRedshift@ is an asynchronous operation. In response+-- to @CreateDataSourceFromRedshift@, Amazon Machine Learning (Amazon ML)+-- immediately returns and sets the @DataSource@ status to @PENDING@. After+-- the @DataSource@ is created and ready for use, Amazon ML sets the+-- @Status@ parameter to @COMPLETED@. @DataSource@ in @COMPLETED@ or+-- @PENDING@ states can be used to perform only @CreateMLModel@,+-- @CreateEvaluation@, or @CreateBatchPrediction@ operations.+--+-- If Amazon ML can\'t accept the input source, it sets the @Status@+-- parameter to @FAILED@ and includes an error message in the @Message@+-- attribute of the @GetDataSource@ operation response.+--+-- The observations should be contained in the database hosted on an Amazon+-- Redshift cluster and should be specified by a @SelectSqlQuery@ query.+-- Amazon ML executes an @Unload@ command in Amazon Redshift to transfer+-- the result set of the @SelectSqlQuery@ query to @S3StagingLocation@.+--+-- After the @DataSource@ has been created, it\'s ready for use in+-- evaluations and batch predictions. If you plan to use the @DataSource@+-- to train an @MLModel@, the @DataSource@ also requires a recipe. A recipe+-- describes how each input variable will be used in training an @MLModel@.+-- Will the variable be included or excluded from training? Will the+-- variable be manipulated; for example, will it be combined with another+-- variable or will it be split apart into word combinations? The recipe+-- provides answers to these questions.+--+-- You can\'t change an existing datasource, but you can copy and modify+-- the settings from an existing Amazon Redshift datasource to create a new+-- datasource. To do so, call @GetDataSource@ for an existing datasource+-- and copy the values to a @CreateDataSource@ call. Change the settings+-- that you want to change and make sure that all required fields have the+-- appropriate values.+module Amazonka.MachineLearning.CreateDataSourceFromRedshift+  ( -- * Creating a Request+    CreateDataSourceFromRedshift (..),+    newCreateDataSourceFromRedshift,++    -- * Request Lenses+    createDataSourceFromRedshift_computeStatistics,+    createDataSourceFromRedshift_dataSourceName,+    createDataSourceFromRedshift_dataSourceId,+    createDataSourceFromRedshift_dataSpec,+    createDataSourceFromRedshift_roleARN,++    -- * Destructuring the Response+    CreateDataSourceFromRedshiftResponse (..),+    newCreateDataSourceFromRedshiftResponse,++    -- * Response Lenses+    createDataSourceFromRedshiftResponse_dataSourceId,+    createDataSourceFromRedshiftResponse_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newCreateDataSourceFromRedshift' smart constructor.+data CreateDataSourceFromRedshift = CreateDataSourceFromRedshift'+  { -- | The compute statistics for a @DataSource@. The statistics are generated+    -- from the observation data referenced by a @DataSource@. Amazon ML uses+    -- the statistics internally during @MLModel@ training. This parameter must+    -- be set to @true@ if the @DataSource@ needs to be used for @MLModel@+    -- training.+    computeStatistics :: Prelude.Maybe Prelude.Bool,+    -- | A user-supplied name or description of the @DataSource@.+    dataSourceName :: Prelude.Maybe Prelude.Text,+    -- | A user-supplied ID that uniquely identifies the @DataSource@.+    dataSourceId :: Prelude.Text,+    -- | The data specification of an Amazon Redshift @DataSource@:+    --+    -- -   DatabaseInformation -+    --+    --     -   @DatabaseName@ - The name of the Amazon Redshift database.+    --+    --     -   @ ClusterIdentifier@ - The unique ID for the Amazon Redshift+    --         cluster.+    --+    -- -   DatabaseCredentials - The AWS Identity and Access Management (IAM)+    --     credentials that are used to connect to the Amazon Redshift+    --     database.+    --+    -- -   SelectSqlQuery - The query that is used to retrieve the observation+    --     data for the @Datasource@.+    --+    -- -   S3StagingLocation - The Amazon Simple Storage Service (Amazon S3)+    --     location for staging Amazon Redshift data. The data retrieved from+    --     Amazon Redshift using the @SelectSqlQuery@ query is stored in this+    --     location.+    --+    -- -   DataSchemaUri - The Amazon S3 location of the @DataSchema@.+    --+    -- -   DataSchema - A JSON string representing the schema. This is not+    --     required if @DataSchemaUri@ is specified.+    --+    -- -   DataRearrangement - A JSON string that represents the splitting and+    --     rearrangement requirements for the @DataSource@.+    --+    --     Sample -+    --     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+    dataSpec :: RedshiftDataSpec,+    -- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the+    -- role on behalf of the user to create the following:+    --+    -- -   A security group to allow Amazon ML to execute the @SelectSqlQuery@+    --     query on an Amazon Redshift cluster+    --+    -- -   An Amazon S3 bucket policy to grant Amazon ML read\/write+    --     permissions on the @S3StagingLocation@+    roleARN :: Prelude.Text+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateDataSourceFromRedshift' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'computeStatistics', 'createDataSourceFromRedshift_computeStatistics' - The compute statistics for a @DataSource@. The statistics are generated+-- from the observation data referenced by a @DataSource@. Amazon ML uses+-- the statistics internally during @MLModel@ training. This parameter must+-- be set to @true@ if the @DataSource@ needs to be used for @MLModel@+-- training.+--+-- 'dataSourceName', 'createDataSourceFromRedshift_dataSourceName' - A user-supplied name or description of the @DataSource@.+--+-- 'dataSourceId', 'createDataSourceFromRedshift_dataSourceId' - A user-supplied ID that uniquely identifies the @DataSource@.+--+-- 'dataSpec', 'createDataSourceFromRedshift_dataSpec' - The data specification of an Amazon Redshift @DataSource@:+--+-- -   DatabaseInformation -+--+--     -   @DatabaseName@ - The name of the Amazon Redshift database.+--+--     -   @ ClusterIdentifier@ - The unique ID for the Amazon Redshift+--         cluster.+--+-- -   DatabaseCredentials - The AWS Identity and Access Management (IAM)+--     credentials that are used to connect to the Amazon Redshift+--     database.+--+-- -   SelectSqlQuery - The query that is used to retrieve the observation+--     data for the @Datasource@.+--+-- -   S3StagingLocation - The Amazon Simple Storage Service (Amazon S3)+--     location for staging Amazon Redshift data. The data retrieved from+--     Amazon Redshift using the @SelectSqlQuery@ query is stored in this+--     location.+--+-- -   DataSchemaUri - The Amazon S3 location of the @DataSchema@.+--+-- -   DataSchema - A JSON string representing the schema. This is not+--     required if @DataSchemaUri@ is specified.+--+-- -   DataRearrangement - A JSON string that represents the splitting and+--     rearrangement requirements for the @DataSource@.+--+--     Sample -+--     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+--+-- 'roleARN', 'createDataSourceFromRedshift_roleARN' - A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the+-- role on behalf of the user to create the following:+--+-- -   A security group to allow Amazon ML to execute the @SelectSqlQuery@+--     query on an Amazon Redshift cluster+--+-- -   An Amazon S3 bucket policy to grant Amazon ML read\/write+--     permissions on the @S3StagingLocation@+newCreateDataSourceFromRedshift ::+  -- | 'dataSourceId'+  Prelude.Text ->+  -- | 'dataSpec'+  RedshiftDataSpec ->+  -- | 'roleARN'+  Prelude.Text ->+  CreateDataSourceFromRedshift+newCreateDataSourceFromRedshift+  pDataSourceId_+  pDataSpec_+  pRoleARN_ =+    CreateDataSourceFromRedshift'+      { computeStatistics =+          Prelude.Nothing,+        dataSourceName = Prelude.Nothing,+        dataSourceId = pDataSourceId_,+        dataSpec = pDataSpec_,+        roleARN = pRoleARN_+      }++-- | The compute statistics for a @DataSource@. The statistics are generated+-- from the observation data referenced by a @DataSource@. Amazon ML uses+-- the statistics internally during @MLModel@ training. This parameter must+-- be set to @true@ if the @DataSource@ needs to be used for @MLModel@+-- training.+createDataSourceFromRedshift_computeStatistics :: Lens.Lens' CreateDataSourceFromRedshift (Prelude.Maybe Prelude.Bool)+createDataSourceFromRedshift_computeStatistics = Lens.lens (\CreateDataSourceFromRedshift' {computeStatistics} -> computeStatistics) (\s@CreateDataSourceFromRedshift' {} a -> s {computeStatistics = a} :: CreateDataSourceFromRedshift)++-- | A user-supplied name or description of the @DataSource@.+createDataSourceFromRedshift_dataSourceName :: Lens.Lens' CreateDataSourceFromRedshift (Prelude.Maybe Prelude.Text)+createDataSourceFromRedshift_dataSourceName = Lens.lens (\CreateDataSourceFromRedshift' {dataSourceName} -> dataSourceName) (\s@CreateDataSourceFromRedshift' {} a -> s {dataSourceName = a} :: CreateDataSourceFromRedshift)++-- | A user-supplied ID that uniquely identifies the @DataSource@.+createDataSourceFromRedshift_dataSourceId :: Lens.Lens' CreateDataSourceFromRedshift Prelude.Text+createDataSourceFromRedshift_dataSourceId = Lens.lens (\CreateDataSourceFromRedshift' {dataSourceId} -> dataSourceId) (\s@CreateDataSourceFromRedshift' {} a -> s {dataSourceId = a} :: CreateDataSourceFromRedshift)++-- | The data specification of an Amazon Redshift @DataSource@:+--+-- -   DatabaseInformation -+--+--     -   @DatabaseName@ - The name of the Amazon Redshift database.+--+--     -   @ ClusterIdentifier@ - The unique ID for the Amazon Redshift+--         cluster.+--+-- -   DatabaseCredentials - The AWS Identity and Access Management (IAM)+--     credentials that are used to connect to the Amazon Redshift+--     database.+--+-- -   SelectSqlQuery - The query that is used to retrieve the observation+--     data for the @Datasource@.+--+-- -   S3StagingLocation - The Amazon Simple Storage Service (Amazon S3)+--     location for staging Amazon Redshift data. The data retrieved from+--     Amazon Redshift using the @SelectSqlQuery@ query is stored in this+--     location.+--+-- -   DataSchemaUri - The Amazon S3 location of the @DataSchema@.+--+-- -   DataSchema - A JSON string representing the schema. This is not+--     required if @DataSchemaUri@ is specified.+--+-- -   DataRearrangement - A JSON string that represents the splitting and+--     rearrangement requirements for the @DataSource@.+--+--     Sample -+--     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+createDataSourceFromRedshift_dataSpec :: Lens.Lens' CreateDataSourceFromRedshift RedshiftDataSpec+createDataSourceFromRedshift_dataSpec = Lens.lens (\CreateDataSourceFromRedshift' {dataSpec} -> dataSpec) (\s@CreateDataSourceFromRedshift' {} a -> s {dataSpec = a} :: CreateDataSourceFromRedshift)++-- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the+-- role on behalf of the user to create the following:+--+-- -   A security group to allow Amazon ML to execute the @SelectSqlQuery@+--     query on an Amazon Redshift cluster+--+-- -   An Amazon S3 bucket policy to grant Amazon ML read\/write+--     permissions on the @S3StagingLocation@+createDataSourceFromRedshift_roleARN :: Lens.Lens' CreateDataSourceFromRedshift Prelude.Text+createDataSourceFromRedshift_roleARN = Lens.lens (\CreateDataSourceFromRedshift' {roleARN} -> roleARN) (\s@CreateDataSourceFromRedshift' {} a -> s {roleARN = a} :: CreateDataSourceFromRedshift)++instance Core.AWSRequest CreateDataSourceFromRedshift where+  type+    AWSResponse CreateDataSourceFromRedshift =+      CreateDataSourceFromRedshiftResponse+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          CreateDataSourceFromRedshiftResponse'+            Prelude.<$> (x Data..?> "DataSourceId")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance+  Prelude.Hashable+    CreateDataSourceFromRedshift+  where+  hashWithSalt _salt CreateDataSourceFromRedshift' {..} =+    _salt+      `Prelude.hashWithSalt` computeStatistics+      `Prelude.hashWithSalt` dataSourceName+      `Prelude.hashWithSalt` dataSourceId+      `Prelude.hashWithSalt` dataSpec+      `Prelude.hashWithSalt` roleARN++instance Prelude.NFData CreateDataSourceFromRedshift where+  rnf CreateDataSourceFromRedshift' {..} =+    Prelude.rnf computeStatistics+      `Prelude.seq` Prelude.rnf dataSourceName+      `Prelude.seq` Prelude.rnf dataSourceId+      `Prelude.seq` Prelude.rnf dataSpec+      `Prelude.seq` Prelude.rnf roleARN++instance Data.ToHeaders CreateDataSourceFromRedshift where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ( "AmazonML_20141212.CreateDataSourceFromRedshift" ::+                          Prelude.ByteString+                      ),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON CreateDataSourceFromRedshift where+  toJSON CreateDataSourceFromRedshift' {..} =+    Data.object+      ( Prelude.catMaybes+          [ ("ComputeStatistics" Data..=)+              Prelude.<$> computeStatistics,+            ("DataSourceName" Data..=)+              Prelude.<$> dataSourceName,+            Prelude.Just ("DataSourceId" Data..= dataSourceId),+            Prelude.Just ("DataSpec" Data..= dataSpec),+            Prelude.Just ("RoleARN" Data..= roleARN)+          ]+      )++instance Data.ToPath CreateDataSourceFromRedshift where+  toPath = Prelude.const "/"++instance Data.ToQuery CreateDataSourceFromRedshift where+  toQuery = Prelude.const Prelude.mempty++-- | Represents the output of a @CreateDataSourceFromRedshift@ operation, and+-- is an acknowledgement that Amazon ML received the request.+--+-- The @CreateDataSourceFromRedshift@ operation is asynchronous. You can+-- poll for updates by using the @GetBatchPrediction@ operation and+-- checking the @Status@ parameter.+--+-- /See:/ 'newCreateDataSourceFromRedshiftResponse' smart constructor.+data CreateDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse'+  { -- | A user-supplied ID that uniquely identifies the datasource. This value+    -- should be identical to the value of the @DataSourceID@ in the request.+    dataSourceId :: Prelude.Maybe Prelude.Text,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateDataSourceFromRedshiftResponse' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'dataSourceId', 'createDataSourceFromRedshiftResponse_dataSourceId' - A user-supplied ID that uniquely identifies the datasource. This value+-- should be identical to the value of the @DataSourceID@ in the request.+--+-- 'httpStatus', 'createDataSourceFromRedshiftResponse_httpStatus' - The response's http status code.+newCreateDataSourceFromRedshiftResponse ::+  -- | 'httpStatus'+  Prelude.Int ->+  CreateDataSourceFromRedshiftResponse+newCreateDataSourceFromRedshiftResponse pHttpStatus_ =+  CreateDataSourceFromRedshiftResponse'+    { dataSourceId =+        Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | A user-supplied ID that uniquely identifies the datasource. This value+-- should be identical to the value of the @DataSourceID@ in the request.+createDataSourceFromRedshiftResponse_dataSourceId :: Lens.Lens' CreateDataSourceFromRedshiftResponse (Prelude.Maybe Prelude.Text)+createDataSourceFromRedshiftResponse_dataSourceId = Lens.lens (\CreateDataSourceFromRedshiftResponse' {dataSourceId} -> dataSourceId) (\s@CreateDataSourceFromRedshiftResponse' {} a -> s {dataSourceId = a} :: CreateDataSourceFromRedshiftResponse)++-- | The response's http status code.+createDataSourceFromRedshiftResponse_httpStatus :: Lens.Lens' CreateDataSourceFromRedshiftResponse Prelude.Int+createDataSourceFromRedshiftResponse_httpStatus = Lens.lens (\CreateDataSourceFromRedshiftResponse' {httpStatus} -> httpStatus) (\s@CreateDataSourceFromRedshiftResponse' {} a -> s {httpStatus = a} :: CreateDataSourceFromRedshiftResponse)++instance+  Prelude.NFData+    CreateDataSourceFromRedshiftResponse+  where+  rnf CreateDataSourceFromRedshiftResponse' {..} =+    Prelude.rnf dataSourceId+      `Prelude.seq` Prelude.rnf httpStatus

@@ -0,0 +1,312 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.CreateDataSourceFromS3+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Creates a @DataSource@ object. A @DataSource@ references data that can+-- be used to perform @CreateMLModel@, @CreateEvaluation@, or+-- @CreateBatchPrediction@ operations.+--+-- @CreateDataSourceFromS3@ is an asynchronous operation. In response to+-- @CreateDataSourceFromS3@, Amazon Machine Learning (Amazon ML)+-- immediately returns and sets the @DataSource@ status to @PENDING@. After+-- the @DataSource@ has been created and is ready for use, Amazon ML sets+-- the @Status@ parameter to @COMPLETED@. @DataSource@ in the @COMPLETED@+-- or @PENDING@ state can be used to perform only @CreateMLModel@,+-- @CreateEvaluation@ or @CreateBatchPrediction@ operations.+--+-- If Amazon ML can\'t accept the input source, it sets the @Status@+-- parameter to @FAILED@ and includes an error message in the @Message@+-- attribute of the @GetDataSource@ operation response.+--+-- The observation data used in a @DataSource@ should be ready to use; that+-- is, it should have a consistent structure, and missing data values+-- should be kept to a minimum. The observation data must reside in one or+-- more .csv files in an Amazon Simple Storage Service (Amazon S3)+-- location, along with a schema that describes the data items by name and+-- type. The same schema must be used for all of the data files referenced+-- by the @DataSource@.+--+-- After the @DataSource@ has been created, it\'s ready to use in+-- evaluations and batch predictions. If you plan to use the @DataSource@+-- to train an @MLModel@, the @DataSource@ also needs a recipe. A recipe+-- describes how each input variable will be used in training an @MLModel@.+-- Will the variable be included or excluded from training? Will the+-- variable be manipulated; for example, will it be combined with another+-- variable or will it be split apart into word combinations? The recipe+-- provides answers to these questions.+module Amazonka.MachineLearning.CreateDataSourceFromS3+  ( -- * Creating a Request+    CreateDataSourceFromS3 (..),+    newCreateDataSourceFromS3,++    -- * Request Lenses+    createDataSourceFromS3_computeStatistics,+    createDataSourceFromS3_dataSourceName,+    createDataSourceFromS3_dataSourceId,+    createDataSourceFromS3_dataSpec,++    -- * Destructuring the Response+    CreateDataSourceFromS3Response (..),+    newCreateDataSourceFromS3Response,++    -- * Response Lenses+    createDataSourceFromS3Response_dataSourceId,+    createDataSourceFromS3Response_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newCreateDataSourceFromS3' smart constructor.+data CreateDataSourceFromS3 = CreateDataSourceFromS3'+  { -- | The compute statistics for a @DataSource@. The statistics are generated+    -- from the observation data referenced by a @DataSource@. Amazon ML uses+    -- the statistics internally during @MLModel@ training. This parameter must+    -- be set to @true@ if the DataSource needs to be used for @MLModel@+    -- training.+    computeStatistics :: Prelude.Maybe Prelude.Bool,+    -- | A user-supplied name or description of the @DataSource@.+    dataSourceName :: Prelude.Maybe Prelude.Text,+    -- | A user-supplied identifier that uniquely identifies the @DataSource@.+    dataSourceId :: Prelude.Text,+    -- | The data specification of a @DataSource@:+    --+    -- -   DataLocationS3 - The Amazon S3 location of the observation data.+    --+    -- -   DataSchemaLocationS3 - The Amazon S3 location of the @DataSchema@.+    --+    -- -   DataSchema - A JSON string representing the schema. This is not+    --     required if @DataSchemaUri@ is specified.+    --+    -- -   DataRearrangement - A JSON string that represents the splitting and+    --     rearrangement requirements for the @Datasource@.+    --+    --     Sample -+    --     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+    dataSpec :: S3DataSpec+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateDataSourceFromS3' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'computeStatistics', 'createDataSourceFromS3_computeStatistics' - The compute statistics for a @DataSource@. The statistics are generated+-- from the observation data referenced by a @DataSource@. Amazon ML uses+-- the statistics internally during @MLModel@ training. This parameter must+-- be set to @true@ if the DataSource needs to be used for @MLModel@+-- training.+--+-- 'dataSourceName', 'createDataSourceFromS3_dataSourceName' - A user-supplied name or description of the @DataSource@.+--+-- 'dataSourceId', 'createDataSourceFromS3_dataSourceId' - A user-supplied identifier that uniquely identifies the @DataSource@.+--+-- 'dataSpec', 'createDataSourceFromS3_dataSpec' - The data specification of a @DataSource@:+--+-- -   DataLocationS3 - The Amazon S3 location of the observation data.+--+-- -   DataSchemaLocationS3 - The Amazon S3 location of the @DataSchema@.+--+-- -   DataSchema - A JSON string representing the schema. This is not+--     required if @DataSchemaUri@ is specified.+--+-- -   DataRearrangement - A JSON string that represents the splitting and+--     rearrangement requirements for the @Datasource@.+--+--     Sample -+--     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+newCreateDataSourceFromS3 ::+  -- | 'dataSourceId'+  Prelude.Text ->+  -- | 'dataSpec'+  S3DataSpec ->+  CreateDataSourceFromS3+newCreateDataSourceFromS3 pDataSourceId_ pDataSpec_ =+  CreateDataSourceFromS3'+    { computeStatistics =+        Prelude.Nothing,+      dataSourceName = Prelude.Nothing,+      dataSourceId = pDataSourceId_,+      dataSpec = pDataSpec_+    }++-- | The compute statistics for a @DataSource@. The statistics are generated+-- from the observation data referenced by a @DataSource@. Amazon ML uses+-- the statistics internally during @MLModel@ training. This parameter must+-- be set to @true@ if the DataSource needs to be used for @MLModel@+-- training.+createDataSourceFromS3_computeStatistics :: Lens.Lens' CreateDataSourceFromS3 (Prelude.Maybe Prelude.Bool)+createDataSourceFromS3_computeStatistics = Lens.lens (\CreateDataSourceFromS3' {computeStatistics} -> computeStatistics) (\s@CreateDataSourceFromS3' {} a -> s {computeStatistics = a} :: CreateDataSourceFromS3)++-- | A user-supplied name or description of the @DataSource@.+createDataSourceFromS3_dataSourceName :: Lens.Lens' CreateDataSourceFromS3 (Prelude.Maybe Prelude.Text)+createDataSourceFromS3_dataSourceName = Lens.lens (\CreateDataSourceFromS3' {dataSourceName} -> dataSourceName) (\s@CreateDataSourceFromS3' {} a -> s {dataSourceName = a} :: CreateDataSourceFromS3)++-- | A user-supplied identifier that uniquely identifies the @DataSource@.+createDataSourceFromS3_dataSourceId :: Lens.Lens' CreateDataSourceFromS3 Prelude.Text+createDataSourceFromS3_dataSourceId = Lens.lens (\CreateDataSourceFromS3' {dataSourceId} -> dataSourceId) (\s@CreateDataSourceFromS3' {} a -> s {dataSourceId = a} :: CreateDataSourceFromS3)++-- | The data specification of a @DataSource@:+--+-- -   DataLocationS3 - The Amazon S3 location of the observation data.+--+-- -   DataSchemaLocationS3 - The Amazon S3 location of the @DataSchema@.+--+-- -   DataSchema - A JSON string representing the schema. This is not+--     required if @DataSchemaUri@ is specified.+--+-- -   DataRearrangement - A JSON string that represents the splitting and+--     rearrangement requirements for the @Datasource@.+--+--     Sample -+--     @ \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"@+createDataSourceFromS3_dataSpec :: Lens.Lens' CreateDataSourceFromS3 S3DataSpec+createDataSourceFromS3_dataSpec = Lens.lens (\CreateDataSourceFromS3' {dataSpec} -> dataSpec) (\s@CreateDataSourceFromS3' {} a -> s {dataSpec = a} :: CreateDataSourceFromS3)++instance Core.AWSRequest CreateDataSourceFromS3 where+  type+    AWSResponse CreateDataSourceFromS3 =+      CreateDataSourceFromS3Response+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          CreateDataSourceFromS3Response'+            Prelude.<$> (x Data..?> "DataSourceId")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance Prelude.Hashable CreateDataSourceFromS3 where+  hashWithSalt _salt CreateDataSourceFromS3' {..} =+    _salt+      `Prelude.hashWithSalt` computeStatistics+      `Prelude.hashWithSalt` dataSourceName+      `Prelude.hashWithSalt` dataSourceId+      `Prelude.hashWithSalt` dataSpec++instance Prelude.NFData CreateDataSourceFromS3 where+  rnf CreateDataSourceFromS3' {..} =+    Prelude.rnf computeStatistics+      `Prelude.seq` Prelude.rnf dataSourceName+      `Prelude.seq` Prelude.rnf dataSourceId+      `Prelude.seq` Prelude.rnf dataSpec++instance Data.ToHeaders CreateDataSourceFromS3 where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ( "AmazonML_20141212.CreateDataSourceFromS3" ::+                          Prelude.ByteString+                      ),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON CreateDataSourceFromS3 where+  toJSON CreateDataSourceFromS3' {..} =+    Data.object+      ( Prelude.catMaybes+          [ ("ComputeStatistics" Data..=)+              Prelude.<$> computeStatistics,+            ("DataSourceName" Data..=)+              Prelude.<$> dataSourceName,+            Prelude.Just ("DataSourceId" Data..= dataSourceId),+            Prelude.Just ("DataSpec" Data..= dataSpec)+          ]+      )++instance Data.ToPath CreateDataSourceFromS3 where+  toPath = Prelude.const "/"++instance Data.ToQuery CreateDataSourceFromS3 where+  toQuery = Prelude.const Prelude.mempty++-- | Represents the output of a @CreateDataSourceFromS3@ operation, and is an+-- acknowledgement that Amazon ML received the request.+--+-- The @CreateDataSourceFromS3@ operation is asynchronous. You can poll for+-- updates by using the @GetBatchPrediction@ operation and checking the+-- @Status@ parameter.+--+-- /See:/ 'newCreateDataSourceFromS3Response' smart constructor.+data CreateDataSourceFromS3Response = CreateDataSourceFromS3Response'+  { -- | A user-supplied ID that uniquely identifies the @DataSource@. This value+    -- should be identical to the value of the @DataSourceID@ in the request.+    dataSourceId :: Prelude.Maybe Prelude.Text,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateDataSourceFromS3Response' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'dataSourceId', 'createDataSourceFromS3Response_dataSourceId' - A user-supplied ID that uniquely identifies the @DataSource@. This value+-- should be identical to the value of the @DataSourceID@ in the request.+--+-- 'httpStatus', 'createDataSourceFromS3Response_httpStatus' - The response's http status code.+newCreateDataSourceFromS3Response ::+  -- | 'httpStatus'+  Prelude.Int ->+  CreateDataSourceFromS3Response+newCreateDataSourceFromS3Response pHttpStatus_ =+  CreateDataSourceFromS3Response'+    { dataSourceId =+        Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | A user-supplied ID that uniquely identifies the @DataSource@. This value+-- should be identical to the value of the @DataSourceID@ in the request.+createDataSourceFromS3Response_dataSourceId :: Lens.Lens' CreateDataSourceFromS3Response (Prelude.Maybe Prelude.Text)+createDataSourceFromS3Response_dataSourceId = Lens.lens (\CreateDataSourceFromS3Response' {dataSourceId} -> dataSourceId) (\s@CreateDataSourceFromS3Response' {} a -> s {dataSourceId = a} :: CreateDataSourceFromS3Response)++-- | The response's http status code.+createDataSourceFromS3Response_httpStatus :: Lens.Lens' CreateDataSourceFromS3Response Prelude.Int+createDataSourceFromS3Response_httpStatus = Lens.lens (\CreateDataSourceFromS3Response' {httpStatus} -> httpStatus) (\s@CreateDataSourceFromS3Response' {} a -> s {httpStatus = a} :: CreateDataSourceFromS3Response)++instance+  Prelude.NFData+    CreateDataSourceFromS3Response+  where+  rnf CreateDataSourceFromS3Response' {..} =+    Prelude.rnf dataSourceId+      `Prelude.seq` Prelude.rnf httpStatus

@@ -0,0 +1,265 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.CreateEvaluation+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Creates a new @Evaluation@ of an @MLModel@. An @MLModel@ is evaluated on+-- a set of observations associated to a @DataSource@. Like a @DataSource@+-- for an @MLModel@, the @DataSource@ for an @Evaluation@ contains values+-- for the @Target Variable@. The @Evaluation@ compares the predicted+-- result for each observation to the actual outcome and provides a summary+-- so that you know how effective the @MLModel@ functions on the test data.+-- Evaluation generates a relevant performance metric, such as BinaryAUC,+-- RegressionRMSE or MulticlassAvgFScore based on the corresponding+-- @MLModelType@: @BINARY@, @REGRESSION@ or @MULTICLASS@.+--+-- @CreateEvaluation@ is an asynchronous operation. In response to+-- @CreateEvaluation@, Amazon Machine Learning (Amazon ML) immediately+-- returns and sets the evaluation status to @PENDING@. After the+-- @Evaluation@ is created and ready for use, Amazon ML sets the status to+-- @COMPLETED@.+--+-- You can use the @GetEvaluation@ operation to check progress of the+-- evaluation during the creation operation.+module Amazonka.MachineLearning.CreateEvaluation+  ( -- * Creating a Request+    CreateEvaluation (..),+    newCreateEvaluation,++    -- * Request Lenses+    createEvaluation_evaluationName,+    createEvaluation_evaluationId,+    createEvaluation_mLModelId,+    createEvaluation_evaluationDataSourceId,++    -- * Destructuring the Response+    CreateEvaluationResponse (..),+    newCreateEvaluationResponse,++    -- * Response Lenses+    createEvaluationResponse_evaluationId,+    createEvaluationResponse_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newCreateEvaluation' smart constructor.+data CreateEvaluation = CreateEvaluation'+  { -- | A user-supplied name or description of the @Evaluation@.+    evaluationName :: Prelude.Maybe Prelude.Text,+    -- | A user-supplied ID that uniquely identifies the @Evaluation@.+    evaluationId :: Prelude.Text,+    -- | The ID of the @MLModel@ to evaluate.+    --+    -- The schema used in creating the @MLModel@ must match the schema of the+    -- @DataSource@ used in the @Evaluation@.+    mLModelId :: Prelude.Text,+    -- | The ID of the @DataSource@ for the evaluation. The schema of the+    -- @DataSource@ must match the schema used to create the @MLModel@.+    evaluationDataSourceId :: Prelude.Text+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateEvaluation' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'evaluationName', 'createEvaluation_evaluationName' - A user-supplied name or description of the @Evaluation@.+--+-- 'evaluationId', 'createEvaluation_evaluationId' - A user-supplied ID that uniquely identifies the @Evaluation@.+--+-- 'mLModelId', 'createEvaluation_mLModelId' - The ID of the @MLModel@ to evaluate.+--+-- The schema used in creating the @MLModel@ must match the schema of the+-- @DataSource@ used in the @Evaluation@.+--+-- 'evaluationDataSourceId', 'createEvaluation_evaluationDataSourceId' - The ID of the @DataSource@ for the evaluation. The schema of the+-- @DataSource@ must match the schema used to create the @MLModel@.+newCreateEvaluation ::+  -- | 'evaluationId'+  Prelude.Text ->+  -- | 'mLModelId'+  Prelude.Text ->+  -- | 'evaluationDataSourceId'+  Prelude.Text ->+  CreateEvaluation+newCreateEvaluation+  pEvaluationId_+  pMLModelId_+  pEvaluationDataSourceId_ =+    CreateEvaluation'+      { evaluationName = Prelude.Nothing,+        evaluationId = pEvaluationId_,+        mLModelId = pMLModelId_,+        evaluationDataSourceId = pEvaluationDataSourceId_+      }++-- | A user-supplied name or description of the @Evaluation@.+createEvaluation_evaluationName :: Lens.Lens' CreateEvaluation (Prelude.Maybe Prelude.Text)+createEvaluation_evaluationName = Lens.lens (\CreateEvaluation' {evaluationName} -> evaluationName) (\s@CreateEvaluation' {} a -> s {evaluationName = a} :: CreateEvaluation)++-- | A user-supplied ID that uniquely identifies the @Evaluation@.+createEvaluation_evaluationId :: Lens.Lens' CreateEvaluation Prelude.Text+createEvaluation_evaluationId = Lens.lens (\CreateEvaluation' {evaluationId} -> evaluationId) (\s@CreateEvaluation' {} a -> s {evaluationId = a} :: CreateEvaluation)++-- | The ID of the @MLModel@ to evaluate.+--+-- The schema used in creating the @MLModel@ must match the schema of the+-- @DataSource@ used in the @Evaluation@.+createEvaluation_mLModelId :: Lens.Lens' CreateEvaluation Prelude.Text+createEvaluation_mLModelId = Lens.lens (\CreateEvaluation' {mLModelId} -> mLModelId) (\s@CreateEvaluation' {} a -> s {mLModelId = a} :: CreateEvaluation)++-- | The ID of the @DataSource@ for the evaluation. The schema of the+-- @DataSource@ must match the schema used to create the @MLModel@.+createEvaluation_evaluationDataSourceId :: Lens.Lens' CreateEvaluation Prelude.Text+createEvaluation_evaluationDataSourceId = Lens.lens (\CreateEvaluation' {evaluationDataSourceId} -> evaluationDataSourceId) (\s@CreateEvaluation' {} a -> s {evaluationDataSourceId = a} :: CreateEvaluation)++instance Core.AWSRequest CreateEvaluation where+  type+    AWSResponse CreateEvaluation =+      CreateEvaluationResponse+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          CreateEvaluationResponse'+            Prelude.<$> (x Data..?> "EvaluationId")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance Prelude.Hashable CreateEvaluation where+  hashWithSalt _salt CreateEvaluation' {..} =+    _salt+      `Prelude.hashWithSalt` evaluationName+      `Prelude.hashWithSalt` evaluationId+      `Prelude.hashWithSalt` mLModelId+      `Prelude.hashWithSalt` evaluationDataSourceId++instance Prelude.NFData CreateEvaluation where+  rnf CreateEvaluation' {..} =+    Prelude.rnf evaluationName+      `Prelude.seq` Prelude.rnf evaluationId+      `Prelude.seq` Prelude.rnf mLModelId+      `Prelude.seq` Prelude.rnf evaluationDataSourceId++instance Data.ToHeaders CreateEvaluation where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ( "AmazonML_20141212.CreateEvaluation" ::+                          Prelude.ByteString+                      ),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON CreateEvaluation where+  toJSON CreateEvaluation' {..} =+    Data.object+      ( Prelude.catMaybes+          [ ("EvaluationName" Data..=)+              Prelude.<$> evaluationName,+            Prelude.Just ("EvaluationId" Data..= evaluationId),+            Prelude.Just ("MLModelId" Data..= mLModelId),+            Prelude.Just+              ( "EvaluationDataSourceId"+                  Data..= evaluationDataSourceId+              )+          ]+      )++instance Data.ToPath CreateEvaluation where+  toPath = Prelude.const "/"++instance Data.ToQuery CreateEvaluation where+  toQuery = Prelude.const Prelude.mempty++-- | Represents the output of a @CreateEvaluation@ operation, and is an+-- acknowledgement that Amazon ML received the request.+--+-- @CreateEvaluation@ operation is asynchronous. You can poll for status+-- updates by using the @GetEvcaluation@ operation and checking the+-- @Status@ parameter.+--+-- /See:/ 'newCreateEvaluationResponse' smart constructor.+data CreateEvaluationResponse = CreateEvaluationResponse'+  { -- | The user-supplied ID that uniquely identifies the @Evaluation@. This+    -- value should be identical to the value of the @EvaluationId@ in the+    -- request.+    evaluationId :: Prelude.Maybe Prelude.Text,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateEvaluationResponse' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'evaluationId', 'createEvaluationResponse_evaluationId' - The user-supplied ID that uniquely identifies the @Evaluation@. This+-- value should be identical to the value of the @EvaluationId@ in the+-- request.+--+-- 'httpStatus', 'createEvaluationResponse_httpStatus' - The response's http status code.+newCreateEvaluationResponse ::+  -- | 'httpStatus'+  Prelude.Int ->+  CreateEvaluationResponse+newCreateEvaluationResponse pHttpStatus_ =+  CreateEvaluationResponse'+    { evaluationId =+        Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | The user-supplied ID that uniquely identifies the @Evaluation@. This+-- value should be identical to the value of the @EvaluationId@ in the+-- request.+createEvaluationResponse_evaluationId :: Lens.Lens' CreateEvaluationResponse (Prelude.Maybe Prelude.Text)+createEvaluationResponse_evaluationId = Lens.lens (\CreateEvaluationResponse' {evaluationId} -> evaluationId) (\s@CreateEvaluationResponse' {} a -> s {evaluationId = a} :: CreateEvaluationResponse)++-- | The response's http status code.+createEvaluationResponse_httpStatus :: Lens.Lens' CreateEvaluationResponse Prelude.Int+createEvaluationResponse_httpStatus = Lens.lens (\CreateEvaluationResponse' {httpStatus} -> httpStatus) (\s@CreateEvaluationResponse' {} a -> s {httpStatus = a} :: CreateEvaluationResponse)++instance Prelude.NFData CreateEvaluationResponse where+  rnf CreateEvaluationResponse' {..} =+    Prelude.rnf evaluationId+      `Prelude.seq` Prelude.rnf httpStatus

@@ -0,0 +1,459 @@+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE DuplicateRecordFields #-}+{-# LANGUAGE NamedFieldPuns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE RecordWildCards #-}+{-# LANGUAGE StrictData #-}+{-# LANGUAGE TypeFamilies #-}+{-# LANGUAGE NoImplicitPrelude #-}+{-# OPTIONS_GHC -fno-warn-unused-binds #-}+{-# OPTIONS_GHC -fno-warn-unused-imports #-}+{-# OPTIONS_GHC -fno-warn-unused-matches #-}++-- Derived from AWS service descriptions, licensed under Apache 2.0.++-- |+-- Module      : Amazonka.MachineLearning.CreateMLModel+-- Copyright   : (c) 2013-2023 Brendan Hay+-- License     : Mozilla Public License, v. 2.0.+-- Maintainer  : Brendan Hay+-- Stability   : auto-generated+-- Portability : non-portable (GHC extensions)+--+-- Creates a new @MLModel@ using the @DataSource@ and the recipe as+-- information sources.+--+-- An @MLModel@ is nearly immutable. Users can update only the+-- @MLModelName@ and the @ScoreThreshold@ in an @MLModel@ without creating+-- a new @MLModel@.+--+-- @CreateMLModel@ is an asynchronous operation. In response to+-- @CreateMLModel@, Amazon Machine Learning (Amazon ML) immediately returns+-- and sets the @MLModel@ status to @PENDING@. After the @MLModel@ has been+-- created and ready is for use, Amazon ML sets the status to @COMPLETED@.+--+-- You can use the @GetMLModel@ operation to check the progress of the+-- @MLModel@ during the creation operation.+--+-- @CreateMLModel@ requires a @DataSource@ with computed statistics, which+-- can be created by setting @ComputeStatistics@ to @true@ in+-- @CreateDataSourceFromRDS@, @CreateDataSourceFromS3@, or+-- @CreateDataSourceFromRedshift@ operations.+module Amazonka.MachineLearning.CreateMLModel+  ( -- * Creating a Request+    CreateMLModel (..),+    newCreateMLModel,++    -- * Request Lenses+    createMLModel_mLModelName,+    createMLModel_parameters,+    createMLModel_recipe,+    createMLModel_recipeUri,+    createMLModel_mLModelId,+    createMLModel_mLModelType,+    createMLModel_trainingDataSourceId,++    -- * Destructuring the Response+    CreateMLModelResponse (..),+    newCreateMLModelResponse,++    -- * Response Lenses+    createMLModelResponse_mLModelId,+    createMLModelResponse_httpStatus,+  )+where++import qualified Amazonka.Core as Core+import qualified Amazonka.Core.Lens.Internal as Lens+import qualified Amazonka.Data as Data+import Amazonka.MachineLearning.Types+import qualified Amazonka.Prelude as Prelude+import qualified Amazonka.Request as Request+import qualified Amazonka.Response as Response++-- | /See:/ 'newCreateMLModel' smart constructor.+data CreateMLModel = CreateMLModel'+  { -- | A user-supplied name or description of the @MLModel@.+    mLModelName :: Prelude.Maybe Prelude.Text,+    -- | A list of the training parameters in the @MLModel@. The list is+    -- implemented as a map of key-value pairs.+    --+    -- The following is the current set of training parameters:+    --+    -- -   @sgd.maxMLModelSizeInBytes@ - The maximum allowed size of the model.+    --     Depending on the input data, the size of the model might affect its+    --     performance.+    --+    --     The value is an integer that ranges from @100000@ to @2147483648@.+    --     The default value is @33554432@.+    --+    -- -   @sgd.maxPasses@ - The number of times that the training process+    --     traverses the observations to build the @MLModel@. The value is an+    --     integer that ranges from @1@ to @10000@. The default value is @10@.+    --+    -- -   @sgd.shuffleType@ - Whether Amazon ML shuffles the training data.+    --     Shuffling the data improves a model\'s ability to find the optimal+    --     solution for a variety of data types. The valid values are @auto@+    --     and @none@. The default value is @none@. We strongly recommend that+    --     you shuffle your data.+    --+    -- -   @sgd.l1RegularizationAmount@ - The coefficient regularization L1+    --     norm. It controls overfitting the data by penalizing large+    --     coefficients. This tends to drive coefficients to zero, resulting in+    --     a sparse feature set. If you use this parameter, start by specifying+    --     a small value, such as @1.0E-08@.+    --+    --     The value is a double that ranges from @0@ to @MAX_DOUBLE@. The+    --     default is to not use L1 normalization. This parameter can\'t be+    --     used when @L2@ is specified. Use this parameter sparingly.+    --+    -- -   @sgd.l2RegularizationAmount@ - The coefficient regularization L2+    --     norm. It controls overfitting the data by penalizing large+    --     coefficients. This tends to drive coefficients to small, nonzero+    --     values. If you use this parameter, start by specifying a small+    --     value, such as @1.0E-08@.+    --+    --     The value is a double that ranges from @0@ to @MAX_DOUBLE@. The+    --     default is to not use L2 normalization. This parameter can\'t be+    --     used when @L1@ is specified. Use this parameter sparingly.+    parameters :: Prelude.Maybe (Prelude.HashMap Prelude.Text Prelude.Text),+    -- | The data recipe for creating the @MLModel@. You must specify either the+    -- recipe or its URI. If you don\'t specify a recipe or its URI, Amazon ML+    -- creates a default.+    recipe :: Prelude.Maybe Prelude.Text,+    -- | The Amazon Simple Storage Service (Amazon S3) location and file name+    -- that contains the @MLModel@ recipe. You must specify either the recipe+    -- or its URI. If you don\'t specify a recipe or its URI, Amazon ML creates+    -- a default.+    recipeUri :: Prelude.Maybe Prelude.Text,+    -- | A user-supplied ID that uniquely identifies the @MLModel@.+    mLModelId :: Prelude.Text,+    -- | The category of supervised learning that this @MLModel@ will address.+    -- Choose from the following types:+    --+    -- -   Choose @REGRESSION@ if the @MLModel@ will be used to predict a+    --     numeric value.+    --+    -- -   Choose @BINARY@ if the @MLModel@ result has two possible values.+    --+    -- -   Choose @MULTICLASS@ if the @MLModel@ result has a limited number of+    --     values.+    --+    -- For more information, see the+    -- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+    mLModelType :: MLModelType,+    -- | The @DataSource@ that points to the training data.+    trainingDataSourceId :: Prelude.Text+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateMLModel' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'mLModelName', 'createMLModel_mLModelName' - A user-supplied name or description of the @MLModel@.+--+-- 'parameters', 'createMLModel_parameters' - A list of the training parameters in the @MLModel@. The list is+-- implemented as a map of key-value pairs.+--+-- The following is the current set of training parameters:+--+-- -   @sgd.maxMLModelSizeInBytes@ - The maximum allowed size of the model.+--     Depending on the input data, the size of the model might affect its+--     performance.+--+--     The value is an integer that ranges from @100000@ to @2147483648@.+--     The default value is @33554432@.+--+-- -   @sgd.maxPasses@ - The number of times that the training process+--     traverses the observations to build the @MLModel@. The value is an+--     integer that ranges from @1@ to @10000@. The default value is @10@.+--+-- -   @sgd.shuffleType@ - Whether Amazon ML shuffles the training data.+--     Shuffling the data improves a model\'s ability to find the optimal+--     solution for a variety of data types. The valid values are @auto@+--     and @none@. The default value is @none@. We strongly recommend that+--     you shuffle your data.+--+-- -   @sgd.l1RegularizationAmount@ - The coefficient regularization L1+--     norm. It controls overfitting the data by penalizing large+--     coefficients. This tends to drive coefficients to zero, resulting in+--     a sparse feature set. If you use this parameter, start by specifying+--     a small value, such as @1.0E-08@.+--+--     The value is a double that ranges from @0@ to @MAX_DOUBLE@. The+--     default is to not use L1 normalization. This parameter can\'t be+--     used when @L2@ is specified. Use this parameter sparingly.+--+-- -   @sgd.l2RegularizationAmount@ - The coefficient regularization L2+--     norm. It controls overfitting the data by penalizing large+--     coefficients. This tends to drive coefficients to small, nonzero+--     values. If you use this parameter, start by specifying a small+--     value, such as @1.0E-08@.+--+--     The value is a double that ranges from @0@ to @MAX_DOUBLE@. The+--     default is to not use L2 normalization. This parameter can\'t be+--     used when @L1@ is specified. Use this parameter sparingly.+--+-- 'recipe', 'createMLModel_recipe' - The data recipe for creating the @MLModel@. You must specify either the+-- recipe or its URI. If you don\'t specify a recipe or its URI, Amazon ML+-- creates a default.+--+-- 'recipeUri', 'createMLModel_recipeUri' - The Amazon Simple Storage Service (Amazon S3) location and file name+-- that contains the @MLModel@ recipe. You must specify either the recipe+-- or its URI. If you don\'t specify a recipe or its URI, Amazon ML creates+-- a default.+--+-- 'mLModelId', 'createMLModel_mLModelId' - A user-supplied ID that uniquely identifies the @MLModel@.+--+-- 'mLModelType', 'createMLModel_mLModelType' - The category of supervised learning that this @MLModel@ will address.+-- Choose from the following types:+--+-- -   Choose @REGRESSION@ if the @MLModel@ will be used to predict a+--     numeric value.+--+-- -   Choose @BINARY@ if the @MLModel@ result has two possible values.+--+-- -   Choose @MULTICLASS@ if the @MLModel@ result has a limited number of+--     values.+--+-- For more information, see the+-- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+--+-- 'trainingDataSourceId', 'createMLModel_trainingDataSourceId' - The @DataSource@ that points to the training data.+newCreateMLModel ::+  -- | 'mLModelId'+  Prelude.Text ->+  -- | 'mLModelType'+  MLModelType ->+  -- | 'trainingDataSourceId'+  Prelude.Text ->+  CreateMLModel+newCreateMLModel+  pMLModelId_+  pMLModelType_+  pTrainingDataSourceId_ =+    CreateMLModel'+      { mLModelName = Prelude.Nothing,+        parameters = Prelude.Nothing,+        recipe = Prelude.Nothing,+        recipeUri = Prelude.Nothing,+        mLModelId = pMLModelId_,+        mLModelType = pMLModelType_,+        trainingDataSourceId = pTrainingDataSourceId_+      }++-- | A user-supplied name or description of the @MLModel@.+createMLModel_mLModelName :: Lens.Lens' CreateMLModel (Prelude.Maybe Prelude.Text)+createMLModel_mLModelName = Lens.lens (\CreateMLModel' {mLModelName} -> mLModelName) (\s@CreateMLModel' {} a -> s {mLModelName = a} :: CreateMLModel)++-- | A list of the training parameters in the @MLModel@. The list is+-- implemented as a map of key-value pairs.+--+-- The following is the current set of training parameters:+--+-- -   @sgd.maxMLModelSizeInBytes@ - The maximum allowed size of the model.+--     Depending on the input data, the size of the model might affect its+--     performance.+--+--     The value is an integer that ranges from @100000@ to @2147483648@.+--     The default value is @33554432@.+--+-- -   @sgd.maxPasses@ - The number of times that the training process+--     traverses the observations to build the @MLModel@. The value is an+--     integer that ranges from @1@ to @10000@. The default value is @10@.+--+-- -   @sgd.shuffleType@ - Whether Amazon ML shuffles the training data.+--     Shuffling the data improves a model\'s ability to find the optimal+--     solution for a variety of data types. The valid values are @auto@+--     and @none@. The default value is @none@. We strongly recommend that+--     you shuffle your data.+--+-- -   @sgd.l1RegularizationAmount@ - The coefficient regularization L1+--     norm. It controls overfitting the data by penalizing large+--     coefficients. This tends to drive coefficients to zero, resulting in+--     a sparse feature set. If you use this parameter, start by specifying+--     a small value, such as @1.0E-08@.+--+--     The value is a double that ranges from @0@ to @MAX_DOUBLE@. The+--     default is to not use L1 normalization. This parameter can\'t be+--     used when @L2@ is specified. Use this parameter sparingly.+--+-- -   @sgd.l2RegularizationAmount@ - The coefficient regularization L2+--     norm. It controls overfitting the data by penalizing large+--     coefficients. This tends to drive coefficients to small, nonzero+--     values. If you use this parameter, start by specifying a small+--     value, such as @1.0E-08@.+--+--     The value is a double that ranges from @0@ to @MAX_DOUBLE@. The+--     default is to not use L2 normalization. This parameter can\'t be+--     used when @L1@ is specified. Use this parameter sparingly.+createMLModel_parameters :: Lens.Lens' CreateMLModel (Prelude.Maybe (Prelude.HashMap Prelude.Text Prelude.Text))+createMLModel_parameters = Lens.lens (\CreateMLModel' {parameters} -> parameters) (\s@CreateMLModel' {} a -> s {parameters = a} :: CreateMLModel) Prelude.. Lens.mapping Lens.coerced++-- | The data recipe for creating the @MLModel@. You must specify either the+-- recipe or its URI. If you don\'t specify a recipe or its URI, Amazon ML+-- creates a default.+createMLModel_recipe :: Lens.Lens' CreateMLModel (Prelude.Maybe Prelude.Text)+createMLModel_recipe = Lens.lens (\CreateMLModel' {recipe} -> recipe) (\s@CreateMLModel' {} a -> s {recipe = a} :: CreateMLModel)++-- | The Amazon Simple Storage Service (Amazon S3) location and file name+-- that contains the @MLModel@ recipe. You must specify either the recipe+-- or its URI. If you don\'t specify a recipe or its URI, Amazon ML creates+-- a default.+createMLModel_recipeUri :: Lens.Lens' CreateMLModel (Prelude.Maybe Prelude.Text)+createMLModel_recipeUri = Lens.lens (\CreateMLModel' {recipeUri} -> recipeUri) (\s@CreateMLModel' {} a -> s {recipeUri = a} :: CreateMLModel)++-- | A user-supplied ID that uniquely identifies the @MLModel@.+createMLModel_mLModelId :: Lens.Lens' CreateMLModel Prelude.Text+createMLModel_mLModelId = Lens.lens (\CreateMLModel' {mLModelId} -> mLModelId) (\s@CreateMLModel' {} a -> s {mLModelId = a} :: CreateMLModel)++-- | The category of supervised learning that this @MLModel@ will address.+-- Choose from the following types:+--+-- -   Choose @REGRESSION@ if the @MLModel@ will be used to predict a+--     numeric value.+--+-- -   Choose @BINARY@ if the @MLModel@ result has two possible values.+--+-- -   Choose @MULTICLASS@ if the @MLModel@ result has a limited number of+--     values.+--+-- For more information, see the+-- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+createMLModel_mLModelType :: Lens.Lens' CreateMLModel MLModelType+createMLModel_mLModelType = Lens.lens (\CreateMLModel' {mLModelType} -> mLModelType) (\s@CreateMLModel' {} a -> s {mLModelType = a} :: CreateMLModel)++-- | The @DataSource@ that points to the training data.+createMLModel_trainingDataSourceId :: Lens.Lens' CreateMLModel Prelude.Text+createMLModel_trainingDataSourceId = Lens.lens (\CreateMLModel' {trainingDataSourceId} -> trainingDataSourceId) (\s@CreateMLModel' {} a -> s {trainingDataSourceId = a} :: CreateMLModel)++instance Core.AWSRequest CreateMLModel where+  type+    AWSResponse CreateMLModel =+      CreateMLModelResponse+  request overrides =+    Request.postJSON (overrides defaultService)+  response =+    Response.receiveJSON+      ( \s h x ->+          CreateMLModelResponse'+            Prelude.<$> (x Data..?> "MLModelId")+            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))+      )++instance Prelude.Hashable CreateMLModel where+  hashWithSalt _salt CreateMLModel' {..} =+    _salt+      `Prelude.hashWithSalt` mLModelName+      `Prelude.hashWithSalt` parameters+      `Prelude.hashWithSalt` recipe+      `Prelude.hashWithSalt` recipeUri+      `Prelude.hashWithSalt` mLModelId+      `Prelude.hashWithSalt` mLModelType+      `Prelude.hashWithSalt` trainingDataSourceId++instance Prelude.NFData CreateMLModel where+  rnf CreateMLModel' {..} =+    Prelude.rnf mLModelName+      `Prelude.seq` Prelude.rnf parameters+      `Prelude.seq` Prelude.rnf recipe+      `Prelude.seq` Prelude.rnf recipeUri+      `Prelude.seq` Prelude.rnf mLModelId+      `Prelude.seq` Prelude.rnf mLModelType+      `Prelude.seq` Prelude.rnf trainingDataSourceId++instance Data.ToHeaders CreateMLModel where+  toHeaders =+    Prelude.const+      ( Prelude.mconcat+          [ "X-Amz-Target"+              Data.=# ( "AmazonML_20141212.CreateMLModel" ::+                          Prelude.ByteString+                      ),+            "Content-Type"+              Data.=# ( "application/x-amz-json-1.1" ::+                          Prelude.ByteString+                      )+          ]+      )++instance Data.ToJSON CreateMLModel where+  toJSON CreateMLModel' {..} =+    Data.object+      ( Prelude.catMaybes+          [ ("MLModelName" Data..=) Prelude.<$> mLModelName,+            ("Parameters" Data..=) Prelude.<$> parameters,+            ("Recipe" Data..=) Prelude.<$> recipe,+            ("RecipeUri" Data..=) Prelude.<$> recipeUri,+            Prelude.Just ("MLModelId" Data..= mLModelId),+            Prelude.Just ("MLModelType" Data..= mLModelType),+            Prelude.Just+              ( "TrainingDataSourceId"+                  Data..= trainingDataSourceId+              )+          ]+      )++instance Data.ToPath CreateMLModel where+  toPath = Prelude.const "/"++instance Data.ToQuery CreateMLModel where+  toQuery = Prelude.const Prelude.mempty++-- | Represents the output of a @CreateMLModel@ operation, and is an+-- acknowledgement that Amazon ML received the request.+--+-- The @CreateMLModel@ operation is asynchronous. You can poll for status+-- updates by using the @GetMLModel@ operation and checking the @Status@+-- parameter.+--+-- /See:/ 'newCreateMLModelResponse' smart constructor.+data CreateMLModelResponse = CreateMLModelResponse'+  { -- | A user-supplied ID that uniquely identifies the @MLModel@. This value+    -- should be identical to the value of the @MLModelId@ in the request.+    mLModelId :: Prelude.Maybe Prelude.Text,+    -- | The response's http status code.+    httpStatus :: Prelude.Int+  }+  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)++-- |+-- Create a value of 'CreateMLModelResponse' with all optional fields omitted.+--+-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.+--+-- The following record fields are available, with the corresponding lenses provided+-- for backwards compatibility:+--+-- 'mLModelId', 'createMLModelResponse_mLModelId' - A user-supplied ID that uniquely identifies the @MLModel@. This value+-- should be identical to the value of the @MLModelId@ in the request.+--+-- 'httpStatus', 'createMLModelResponse_httpStatus' - The response's http status code.+newCreateMLModelResponse ::+  -- | 'httpStatus'+  Prelude.Int ->+  CreateMLModelResponse+newCreateMLModelResponse pHttpStatus_ =+  CreateMLModelResponse'+    { mLModelId = Prelude.Nothing,+      httpStatus = pHttpStatus_+    }++-- | A user-supplied ID that uniquely identifies the @MLModel@. This value+-- should be identical to the value of the @MLModelId@ in the request.+createMLModelResponse_mLModelId :: Lens.Lens' CreateMLModelResponse (Prelude.Maybe Prelude.Text)+createMLModelResponse_mLModelId = Lens.lens (\CreateMLModelResponse' {mLModelId} -> mLModelId) (\s@CreateMLModelResponse' {} a -> s {mLModelId = a} :: CreateMLModelResponse)++-- | The response's http status code.+createMLModelResponse_httpStatus :: Lens.Lens' CreateMLModelResponse Prelude.Int+createMLModelResponse_httpStatus = Lens.lens (\CreateMLModelResponse' {httpStatus} -> httpStatus) (\s@CreateMLModelResponse' {} a -> s {httpStatus = a} :: CreateMLModelResponse)++instance Prelude.NFData CreateMLModelResponse where+  rnf CreateMLModelResponse' {..} =+    Prelude.rnf mLModelId+      `Prelude.seq` Prelude.rnf httpStatus