运行 shell 脚本以使用在 Amazon EMR 实例上安装库 AWS SDK - AWS SDK代码示例

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运行 shell 脚本以使用在 Amazon EMR 实例上安装库 AWS SDK

以下代码示例展示了 AWS Systems Manager 如何使用在安装其他库的 Amazon EMR 实例上运行 shell 脚本。这样,您就可以自动管理实例,而不必通过SSH连接手动运行命令。

Python
SDK适用于 Python (Boto3)
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

import argparse import time import boto3 def install_libraries_on_core_nodes(cluster_id, script_path, emr_client, ssm_client): """ Copies and runs a shell script on the core nodes in the cluster. :param cluster_id: The ID of the cluster. :param script_path: The path to the script, typically an Amazon S3 object URL. :param emr_client: The Boto3 Amazon EMR client. :param ssm_client: The Boto3 AWS Systems Manager client. """ core_nodes = emr_client.list_instances( ClusterId=cluster_id, InstanceGroupTypes=["CORE"] )["Instances"] core_instance_ids = [node["Ec2InstanceId"] for node in core_nodes] print(f"Found core instances: {core_instance_ids}.") commands = [ # Copy the shell script from Amazon S3 to each node instance. f"aws s3 cp {script_path} /home/hadoop", # Run the shell script to install libraries on each node instance. "bash /home/hadoop/install_libraries.sh", ] for command in commands: print(f"Sending '{command}' to core instances...") command_id = ssm_client.send_command( InstanceIds=core_instance_ids, DocumentName="AWS-RunShellScript", Parameters={"commands": [command]}, TimeoutSeconds=3600, )["Command"]["CommandId"] while True: # Verify the previous step succeeded before running the next step. cmd_result = ssm_client.list_commands(CommandId=command_id)["Commands"][0] if cmd_result["StatusDetails"] == "Success": print(f"Command succeeded.") break elif cmd_result["StatusDetails"] in ["Pending", "InProgress"]: print(f"Command status is {cmd_result['StatusDetails']}, waiting...") time.sleep(10) else: print(f"Command status is {cmd_result['StatusDetails']}, quitting.") raise RuntimeError( f"Command {command} failed to run. " f"Details: {cmd_result['StatusDetails']}" ) def main(): parser = argparse.ArgumentParser() parser.add_argument("cluster_id", help="The ID of the cluster.") parser.add_argument("script_path", help="The path to the script in Amazon S3.") args = parser.parse_args() emr_client = boto3.client("emr") ssm_client = boto3.client("ssm") install_libraries_on_core_nodes( args.cluster_id, args.script_path, emr_client, ssm_client ) if __name__ == "__main__": main()
  • 有关API详细信息,请参阅ListInstances中的 AWS SDKPython (Boto3) API 参考。