openapi: 3.0.0
info:
  version: '2017-03-31'
  x-release: v4
  title: 'AWS Glue #X Amz Target=AWSGlue.BatchCreatePartition #X Amz Target=AWSGlue.BatchCreatePartition #X Amz Target=AWSGlue.GetMLTransform API'
  description: <fullname>Glue</fullname> <p>Defines the public endpoint for the Glue service.</p>
  x-logo:
    url: https://api.apis.guru/v2/cache/logo/https_twitter.com_awscloud_profile_image.png
    backgroundColor: '#FFFFFF'
  termsOfService: https://aws.amazon.com/service-terms/
  contact:
    name: Mike Ralphson
    email: mike.ralphson@gmail.com
    url: https://github.com/mermade/aws2openapi
    x-twitter: PermittedSoc
  license:
    name: Apache 2.0 License
    url: http://www.apache.org/licenses/
  x-providerName: amazonaws.com
  x-serviceName: glue
  x-origin:
  - contentType: application/json
    url: https://raw.githubusercontent.com/aws/aws-sdk-js/master/apis/glue-2017-03-31.normal.json
    converter:
      url: https://github.com/mermade/aws2openapi
      version: 1.0.0
    x-apisguru-driver: external
  x-apiClientRegistration:
    url: https://portal.aws.amazon.com/gp/aws/developer/registration/index.html?nc2=h_ct
  x-apisguru-categories:
  - cloud
  x-preferred: true
servers:
- url: http://glue.{region}.amazonaws.com
  variables:
    region:
      description: The AWS region
      enum:
      - us-east-1
      - us-east-2
      - us-west-1
      - us-west-2
      - us-gov-west-1
      - us-gov-east-1
      - ca-central-1
      - eu-north-1
      - eu-west-1
      - eu-west-2
      - eu-west-3
      - eu-central-1
      - eu-south-1
      - af-south-1
      - ap-northeast-1
      - ap-northeast-2
      - ap-northeast-3
      - ap-southeast-1
      - ap-southeast-2
      - ap-east-1
      - ap-south-1
      - sa-east-1
      - me-south-1
      default: us-east-1
  description: The AWS Glue multi-region endpoint
- url: https://glue.{region}.amazonaws.com
  variables:
    region:
      description: The AWS region
      enum:
      - us-east-1
      - us-east-2
      - us-west-1
      - us-west-2
      - us-gov-west-1
      - us-gov-east-1
      - ca-central-1
      - eu-north-1
      - eu-west-1
      - eu-west-2
      - eu-west-3
      - eu-central-1
      - eu-south-1
      - af-south-1
      - ap-northeast-1
      - ap-northeast-2
      - ap-northeast-3
      - ap-southeast-1
      - ap-southeast-2
      - ap-east-1
      - ap-south-1
      - sa-east-1
      - me-south-1
      default: us-east-1
  description: The AWS Glue multi-region endpoint
- url: http://glue.{region}.amazonaws.com.cn
  variables:
    region:
      description: The AWS region
      enum:
      - cn-north-1
      - cn-northwest-1
      default: cn-north-1
  description: The AWS Glue endpoint for China (Beijing) and China (Ningxia)
- url: https://glue.{region}.amazonaws.com.cn
  variables:
    region:
      description: The AWS region
      enum:
      - cn-north-1
      - cn-northwest-1
      default: cn-north-1
  description: The AWS Glue endpoint for China (Beijing) and China (Ningxia)
security:
- hmac: []
tags:
- name: '#X Amz Target=AWSGlue.GetMLTransform'
paths:
  /#X-Amz-Target=AWSGlue.GetMLTransform:
    parameters:
    - $ref: '#/components/parameters/X-Amz-Content-Sha256'
    - $ref: '#/components/parameters/X-Amz-Date'
    - $ref: '#/components/parameters/X-Amz-Algorithm'
    - $ref: '#/components/parameters/X-Amz-Credential'
    - $ref: '#/components/parameters/X-Amz-Security-Token'
    - $ref: '#/components/parameters/X-Amz-Signature'
    - $ref: '#/components/parameters/X-Amz-SignedHeaders'
    post:
      operationId: GetMLTransform
      description: Gets an Glue machine learning transform artifact and all its corresponding metadata. Machine learning transforms are a special type of transform that use machine learning to learn the details of the transformation to be performed by learning from examples provided by humans. These transformations are then saved by Glue. You can retrieve their metadata by calling <code>GetMLTransform</code>.
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/GetMLTransformResponse'
              examples:
                GetMLTransform200Example:
                  summary: Default GetMLTransform 200 response
                  x-microcks-default: true
                  value:
                    JobRunId: jr_abc123
                    State: SUCCEEDED
        '480':
          description: EntityNotFoundException
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EntityNotFoundException'
              examples:
                GetMLTransform480Example:
                  summary: Default GetMLTransform 480 response
                  x-microcks-default: true
                  value:
                    JobRunId: jr_abc123
                    State: SUCCEEDED
        '481':
          description: InvalidInputException
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/InvalidInputException'
              examples:
                GetMLTransform481Example:
                  summary: Default GetMLTransform 481 response
                  x-microcks-default: true
                  value:
                    JobRunId: jr_abc123
                    State: SUCCEEDED
        '482':
          description: OperationTimeoutException
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/OperationTimeoutException'
              examples:
                GetMLTransform482Example:
                  summary: Default GetMLTransform 482 response
                  x-microcks-default: true
                  value:
                    JobRunId: jr_abc123
                    State: SUCCEEDED
        '483':
          description: InternalServiceException
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/InternalServiceException'
              examples:
                GetMLTransform483Example:
                  summary: Default GetMLTransform 483 response
                  x-microcks-default: true
                  value:
                    JobRunId: jr_abc123
                    State: SUCCEEDED
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/GetMLTransformRequest'
      parameters:
      - name: X-Amz-Target
        in: header
        required: true
        schema:
          type: string
          enum:
          - AWSGlue.GetMLTransform
      summary: Amazon Glue Get M L Transform
      x-microcks-operation:
        delay: 0
        dispatcher: FALLBACK
      tags:
      - '#X Amz Target=AWSGlue.GetMLTransform'
components:
  schemas:
    ColumnNameString:
      type: string
      minLength: 1
      maxLength: 1024
      x-pattern: '[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*'
    TransformSchema:
      type: array
      items:
        $ref: '#/components/schemas/SchemaColumn'
      maxItems: 100
    InternalServiceException: {}
    DescriptionString:
      type: string
      minLength: 0
      maxLength: 2048
      x-pattern: '[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\r\n\t]*'
    ColumnTypeString:
      type: string
      minLength: 0
      maxLength: 131072
      x-pattern: '[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*'
    FindMatchesMetrics:
      type: object
      properties:
        AreaUnderPRCurve:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: <p>The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.</p> <p>For more information, see <a href="https://en.wikipedia.org/wiki/Precision_and_recall">Precision and recall</a> in Wikipedia.</p>
        Precision:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: <p>The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.</p> <p>For more information, see <a href="https://en.wikipedia.org/wiki/Precision_and_recall">Precision and recall</a> in Wikipedia.</p>
        Recall:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: <p>The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.</p> <p>For more information, see <a href="https://en.wikipedia.org/wiki/Precision_and_recall">Precision and recall</a> in Wikipedia.</p>
        F1:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: <p>The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.</p> <p>For more information, see <a href="https://en.wikipedia.org/wiki/F1_score">F1 score</a> in Wikipedia.</p>
        ConfusionMatrix:
          allOf:
          - $ref: '#/components/schemas/ConfusionMatrix'
          - description: <p>The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.</p> <p>For more information, see <a href="https://en.wikipedia.org/wiki/Confusion_matrix">Confusion matrix</a> in Wikipedia.</p>
        ColumnImportances:
          allOf:
          - $ref: '#/components/schemas/ColumnImportanceList'
          - description: A list of <code>ColumnImportance</code> structures containing column importance metrics, sorted in order of descending importance.
      description: The evaluation metrics for the find matches algorithm. The quality of your machine learning transform is measured by getting your transform to predict some matches and comparing the results to known matches from the same dataset. The quality metrics are based on a subset of your data, so they are not precise.
    LabelCount:
      type: integer
    TransformParameters:
      type: object
      required:
      - TransformType
      properties:
        TransformType:
          allOf:
          - $ref: '#/components/schemas/TransformType'
          - description: <p>The type of machine learning transform.</p> <p>For information about the types of machine learning transforms, see <a href="https://docs.aws.amazon.com/glue/latest/dg/add-job-machine-learning-transform.html">Creating Machine Learning Transforms</a>.</p>
        FindMatchesParameters:
          allOf:
          - $ref: '#/components/schemas/FindMatchesParameters'
          - description: The parameters for the find matches algorithm.
      description: The algorithm-specific parameters that are associated with the machine learning transform.
    NullableInteger:
      type: integer
    RoleString:
      type: string
    EntityNotFoundException: {}
    GetMLTransformRequest:
      type: object
      required:
      - TransformId
      title: GetMLTransformRequest
      properties:
        TransformId:
          allOf:
          - $ref: '#/components/schemas/HashString'
          - description: The unique identifier of the transform, generated at the time that the transform was created.
    NullableBoolean:
      type: boolean
    TransformType:
      type: string
      enum:
      - FIND_MATCHES
    ColumnImportanceList:
      type: array
      items:
        $ref: '#/components/schemas/ColumnImportance'
      minItems: 0
      maxItems: 100
    OperationTimeoutException: {}
    TransformStatusType:
      type: string
      enum:
      - NOT_READY
      - READY
      - DELETING
    GlueTables:
      type: array
      items:
        $ref: '#/components/schemas/GlueTable'
      minItems: 0
      maxItems: 10
    WorkerType:
      type: string
      enum:
      - Standard
      - G.1X
      - G.2X
      - G.025X
    HashString:
      type: string
      minLength: 1
      maxLength: 255
      x-pattern: '[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*'
    Timeout:
      type: integer
      minimum: 1
    ColumnImportance:
      type: object
      properties:
        ColumnName:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: The name of a column.
        Importance:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: The column importance score for the column, as a decimal.
      description: <p>A structure containing the column name and column importance score for a column. </p> <p>Column importance helps you understand how columns contribute to your model, by identifying which columns in your records are more important than others.</p>
    FindMatchesParameters:
      type: object
      properties:
        PrimaryKeyColumnName:
          allOf:
          - $ref: '#/components/schemas/ColumnNameString'
          - description: The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
        PrecisionRecallTradeoff:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: <p>The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.</p> <p>The precision metric indicates how often your model is correct when it predicts a match. </p> <p>The recall metric indicates that for an actual match, how often your model predicts the match.</p>
        AccuracyCostTradeoff:
          allOf:
          - $ref: '#/components/schemas/GenericBoundedDouble'
          - description: <p>The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate <code>FindMatches</code> transform, sometimes with unacceptable accuracy.</p> <p>Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall. </p> <p>Cost measures how many compute resources, and thus money, are consumed to run the transform.</p>
        EnforceProvidedLabels:
          allOf:
          - $ref: '#/components/schemas/NullableBoolean'
          - description: <p>The value to switch on or off to force the output to match the provided labels from users. If the value is <code>True</code>, the <code>find matches</code> transform forces the output to match the provided labels. The results override the normal conflation results. If the value is <code>False</code>, the <code>find matches</code> transform does not ensure all the labels provided are respected, and the results rely on the trained model.</p> <p>Note that setting this value to true may increase the conflation execution time.</p>
      description: The parameters to configure the find matches transform.
    GlueTable:
      type: object
      required:
      - DatabaseName
      - TableName
      properties:
        DatabaseName:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: A database name in the Glue Data Catalog.
        TableName:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: A table name in the Glue Data Catalog.
        CatalogId:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: A unique identifier for the Glue Data Catalog.
        ConnectionName:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: The name of the connection to the Glue Data Catalog.
        AdditionalOptions:
          allOf:
          - $ref: '#/components/schemas/GlueTableAdditionalOptions'
          - description: '<p>Additional options for the table. Currently there are two keys supported:</p> <ul> <li> <p> <code>pushDownPredicate</code>: to filter on partitions without having to list and read all the files in your dataset.</p> </li> <li> <p> <code>catalogPartitionPredicate</code>: to use server-side partition pruning using partition indexes in the Glue Data Catalog.</p> </li> </ul>'
      description: The database and table in the Glue Data Catalog that is used for input or output data.
    GlueVersionString:
      type: string
      pattern: ^\w+\.\w+$
      minLength: 1
      maxLength: 255
    NullableDouble:
      type: number
      format: double
    SchemaColumn:
      type: object
      properties:
        Name:
          allOf:
          - $ref: '#/components/schemas/ColumnNameString'
          - description: The name of the column.
        DataType:
          allOf:
          - $ref: '#/components/schemas/ColumnTypeString'
          - description: The type of data in the column.
      description: A key-value pair representing a column and data type that this transform can run against. The <code>Schema</code> parameter of the <code>MLTransform</code> may contain up to 100 of these structures.
    ConfusionMatrix:
      type: object
      properties:
        NumTruePositives:
          allOf:
          - $ref: '#/components/schemas/RecordsCount'
          - description: The number of matches in the data that the transform correctly found, in the confusion matrix for your transform.
        NumFalsePositives:
          allOf:
          - $ref: '#/components/schemas/RecordsCount'
          - description: The number of nonmatches in the data that the transform incorrectly classified as a match, in the confusion matrix for your transform.
        NumTrueNegatives:
          allOf:
          - $ref: '#/components/schemas/RecordsCount'
          - description: The number of nonmatches in the data that the transform correctly rejected, in the confusion matrix for your transform.
        NumFalseNegatives:
          allOf:
          - $ref: '#/components/schemas/RecordsCount'
          - description: The number of matches in the data that the transform didn't find, in the confusion matrix for your transform.
      description: <p>The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.</p> <p>For more information, see <a href="https://en.wikipedia.org/wiki/Confusion_matrix">Confusion matrix</a> in Wikipedia.</p>
    TransformEncryption:
      type: object
      properties:
        MlUserDataEncryption:
          allOf:
          - $ref: '#/components/schemas/MLUserDataEncryption'
          - description: An <code>MLUserDataEncryption</code> object containing the encryption mode and customer-provided KMS key ID.
        TaskRunSecurityConfigurationName:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: The name of the security configuration.
      description: <p>The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.</p> <p>Additionally, imported labels and trained transforms can now be encrypted using a customer provided KMS key.</p>
    RecordsCount:
      type: integer
    GlueTableAdditionalOptions:
      type: object
      minProperties: 1
      maxProperties: 10
      additionalProperties:
        $ref: '#/components/schemas/DescriptionString'
    NameString:
      type: string
      minLength: 1
      maxLength: 255
      x-pattern: '[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*'
    Timestamp:
      type: string
      format: date-time
    MLUserDataEncryption:
      type: object
      required:
      - MlUserDataEncryptionMode
      properties:
        MlUserDataEncryptionMode:
          allOf:
          - $ref: '#/components/schemas/MLUserDataEncryptionModeString'
          - description: '<p>The encryption mode applied to user data. Valid values are:</p> <ul> <li> <p>DISABLED: encryption is disabled</p> </li> <li> <p>SSEKMS: use of server-side encryption with Key Management Service (SSE-KMS) for user data stored in Amazon S3.</p> </li> </ul>'
        KmsKeyId:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: The ID for the customer-provided KMS key.
      description: The encryption-at-rest settings of the transform that apply to accessing user data.
    InvalidInputException: {}
    MLUserDataEncryptionModeString:
      type: string
      enum:
      - DISABLED
      - SSE-KMS
    GenericBoundedDouble:
      type: number
      format: double
      minimum: 0
      maximum: 1
    EvaluationMetrics:
      type: object
      required:
      - TransformType
      properties:
        TransformType:
          allOf:
          - $ref: '#/components/schemas/TransformType'
          - description: The type of machine learning transform.
        FindMatchesMetrics:
          allOf:
          - $ref: '#/components/schemas/FindMatchesMetrics'
          - description: The evaluation metrics for the find matches algorithm.
      description: Evaluation metrics provide an estimate of the quality of your machine learning transform.
    GetMLTransformResponse:
      type: object
      properties:
        TransformId:
          allOf:
          - $ref: '#/components/schemas/HashString'
          - description: The unique identifier of the transform, generated at the time that the transform was created.
        Name:
          allOf:
          - $ref: '#/components/schemas/NameString'
          - description: The unique name given to the transform when it was created.
        Description:
          allOf:
          - $ref: '#/components/schemas/DescriptionString'
          - description: A description of the transform.
        Status:
          allOf:
          - $ref: '#/components/schemas/TransformStatusType'
          - description: The last known status of the transform (to indicate whether it can be used or not). One of "NOT_READY", "READY", or "DELETING".
        CreatedOn:
          allOf:
          - $ref: '#/components/schemas/Timestamp'
          - description: The date and time when the transform was created.
        LastModifiedOn:
          allOf:
          - $ref: '#/components/schemas/Timestamp'
          - description: The date and time when the transform was last modified.
        InputRecordTables:
          allOf:
          - $ref: '#/components/schemas/GlueTables'
          - description: A list of Glue table definitions used by the transform.
        Parameters:
          allOf:
          - $ref: '#/components/schemas/TransformParameters'
          - description: The configuration parameters that are specific to the algorithm used.
        EvaluationMetrics:
          allOf:
          - $ref: '#/components/schemas/EvaluationMetrics'
          - description: The latest evaluation metrics.
        LabelCount:
          allOf:
          - $ref: '#/components/schemas/LabelCount'
          - description: The number of labels available for this transform.
        Schema:
          allOf:
          - $ref: '#/components/schemas/TransformSchema'
          - description: The <code>Map&lt;Column, Type&gt;</code> object that represents the schema that this transform accepts. Has an upper bound of 100 columns.
        Role:
          allOf:
          - $ref: '#/components/schemas/RoleString'
          - description: The name or Amazon Resource Name (ARN) of the IAM role with the required permissions.
        GlueVersion:
          allOf:
          - $ref: '#/components/schemas/GlueVersionString'
          - description: This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see <a href="https://docs.aws.amazon.com/glue/latest/dg/release-notes.html#release-notes-versions">Glue Versions</a> in the developer guide.
        MaxCapacity:
          allOf:
          - $ref: '#/components/schemas/NullableDouble'
          - description: <p>The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the <a href="https://aws.amazon.com/glue/pricing/">Glue pricing page</a>. </p> <p>When the <code>WorkerType</code> field is set to a value other than <code>Standard</code>, the <code>MaxCapacity</code> field is set automatically and becomes read-only.</p>
        WorkerType:
          allOf:
          - $ref: '#/components/schemas/WorkerType'
          - description: <p>The type of predefined worker that is allocated when this task runs. Accepts a value of Standard, G.1X, or G.2X.</p> <ul> <li> <p>For the <code>Standard</code> worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.</p> </li> <li> <p>For the <code>G.1X</code> worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.</p> </li> <li> <p>For the <code>G.2X</code> worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.</p> </li> </ul>
        NumberOfWorkers:
          allOf:
          - $ref: '#/components/schemas/NullableInteger'
          - description: The number of workers of a defined <code>workerType</code> that are allocated when this task runs.
        Timeout:
          allOf:
          - $ref: '#/components/schemas/Timeout'
          - description: The timeout for a task run for this transform in minutes. This is the maximum time that a task run for this transform can consume resources before it is terminated and enters <code>TIMEOUT</code> status. The default is 2,880 minutes (48 hours).
        MaxRetries:
          allOf:
          - $ref: '#/components/schemas/NullableInteger'
          - description: The maximum number of times to retry a task for this transform after a task run fails.
        TransformEncryption:
          allOf:
          - $ref: '#/components/schemas/TransformEncryption'
          - description: The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
  parameters:
    X-Amz-SignedHeaders:
      name: X-Amz-SignedHeaders
      in: header
      schema:
        type: string
      required: false
    X-Amz-Signature:
      name: X-Amz-Signature
      in: header
      schema:
        type: string
      required: false
    X-Amz-Security-Token:
      name: X-Amz-Security-Token
      in: header
      schema:
        type: string
      required: false
    X-Amz-Content-Sha256:
      name: X-Amz-Content-Sha256
      in: header
      schema:
        type: string
      required: false
    X-Amz-Date:
      name: X-Amz-Date
      in: header
      schema:
        type: string
      required: false
    X-Amz-Credential:
      name: X-Amz-Credential
      in: header
      schema:
        type: string
      required: false
    X-Amz-Algorithm:
      name: X-Amz-Algorithm
      in: header
      schema:
        type: string
      required: false
  securitySchemes:
    hmac:
      type: apiKey
      name: Authorization
      in: header
      description: Amazon Signature authorization v4
      x-amazon-apigateway-authtype: awsSigv4
externalDocs:
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