# zexi 0.4.0
emr_RunJobFlow:
  title: Run an &EMR; job flow using an &AWS; SDK
  title_abbrev: Run a job flow
  synopsis: run an &EMR; job flow.
  category:
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide:
          excerpts:
            - description:
              snippet_tags:
                - python.example_code.emr.RunJobFlow
  services:
    emr: {RunJobFlow}
emr_DescribeCluster:
  title: Describe an &EMR; cluster using an &AWS; SDK
  title_abbrev: Describe a cluster
  synopsis: describe an &EMR; cluster.
  category:
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide:
          excerpts:
            - description:
              snippet_tags:
                - python.example_code.emr.DescribeCluster
  services:
    emr: {DescribeCluster}
emr_TerminateJobFlows:
  title: Terminate &EMR; job flows using an &AWS; SDK
  title_abbrev: Terminate job flows
  synopsis: terminate &EMR; job flows.
  category:
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide: 
          excerpts:
            - description:
              snippet_tags:
                - python.example_code.emr.TerminateJobFlows
  services:
    emr: {TerminateJobFlows}
emr_AddJobFlowSteps:
  title: Add steps to an &EMR; job flow using an &AWS; SDK
  title_abbrev: Add steps to a job flow
  synopsis: add steps to an &EMR; job flow.
  category:
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide:
          excerpts:
            - description: Add a Spark step, which is run by the cluster as soon as it is added.
              snippet_tags:
                - python.example_code.emr.AddJobFlowSteps
            - description: Run an &EMR; File System (EMRFS) command as a job step on a cluster.
                This can be used to automate EMRFS commands on a cluster instead of running
                commands manually through an SSH connection.
              snippet_tags:
                - emr.python.addstep.emrfs
  services:
    emr: {AddJobFlowSteps}
emr_ListSteps:
  title: List steps for an &EMR; cluster using an &AWS; SDK
  title_abbrev: List steps for a cluster
  synopsis: list steps for an &EMR; cluster.
  category:
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide:
          excerpts:
            - description:
              snippet_tags:
                - python.example_code.emr.ListSteps
  services:
    emr: {ListSteps}
emr_DescribeStep:
  title: Describe a step on an &EMR; cluster using an &AWS; SDK
  title_abbrev: Describe a step
  synopsis: describe a step on an &EMR; cluster.
  category:
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide:
          excerpts:
            - description:
              snippet_tags:
                - python.example_code.emr.DescribeStep
  services:
    emr: {DescribeStep}
emr_Usage_InstallLibrariesWithSsm:
  title: Run a shell script to install libraries on &EMR; instances using an &AWS; SDK
  title_abbrev: Run a shell script to install libraries
  synopsis: use &SYSlong; to run a shell script on &EMR; instances that installs
    additional libraries. This way, you can automate instance management instead
    of running commands manually through an SSH connection.
  category: Scenarios
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: python/example_code/emr
          sdkguide:
          excerpts:
            - description:
              snippet_tags:
                - emr.python.jupyterhub.installlibraries
  services:
    emr: {ListInstances}
emr_Scenario_ShortLivedEmrCluster:
  title: Create a short-lived &EMR; cluster and run a step using an &AWS; SDK
  title_abbrev: Create a short-lived &EMR; cluster and run a step
  synopsis: create a short-lived &EMR; cluster that runs a step and automatically
    terminates after the step completes.
  category: Scenarios
  languages:
    Python:
      versions:
        - sdk_version: 3
          github: emr_usage_demo.py
          block_content: cross_EmrShortLivedCluster_Python_block.xml
  services:
    emr: {}