使用任务提交者分类 - Amazon EMR
概述示例

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使用任务提交者分类

概述

Amazon EMR on EKS StartJobRun reques t 会创建一个任务提交者窗格（也称为作业运行器窗格）来生成 Spark 驱动程序。您可以使用emr-job-submitter分类为作业提交者窗格配置节点选择器，也可以为作业提交者窗格的日志容器设置图像和内存。CPU

该emr-job-submitter分类下有以下设置可用：

jobsubmitter.node.selector.[labelKey]

添加到任务提交者 Pod 的节点选择器中，以键 labelKey 和值作为配置的配置值。例如，您可以将 jobsubmitter.node.selector.identifier 设置为 myIdentifier，任务提交者 Pod 会有一个键标识符值为 myIdentifier 的节点选择器。这可以用来指定任务提交者窗格可以放在哪些节点上。要添加多个节点选择器键，可使用此前缀设置多个配置。

jobsubmitter.logging.image

设置用于作业提交者窗格上的日志容器的自定义镜像。

jobsubmitter.logging.request.cores

为作业提交者窗格上的日志容器的CPUs数量设置自定义值（以CPU单位为单位）。默认情况下，此值设置为 100 米。

jobsubmitter.logging.request.memory

为作业提交者窗格上的日志容器设置一个自定义的内存量（以字节为单位）。默认情况下，此值设置为 200Mi。兆字节是一种类似于兆字节的度量单位。

我们建议将任务提交者窗格放在按需实例上。如果运行作业提交者容器的实例受到竞价型实例中断，则在竞价型实例上放置作业提交者容器可能会导致任务失败。您也可以将任务提交者 Pod 放在单个可用区中，也可以使用应用于节点的任何 Kubernetes 标签。

任务提交者分类示例

StartJobRun 为任务提交者 Pod 请求按需型节点放置

cat >spark-python-in-s3-nodeselector-job-submitter.json << EOF
{
  "name": "spark-python-in-s3-nodeselector", 
  "virtualClusterId": "virtual-cluster-id", 
  "executionRoleArn": "execution-role-arn", 
  "releaseLabel": "emr-6.11.0-latest", 
  "jobDriver": {
    "sparkSubmitJobDriver": {
      "entryPoint": "s3://S3-prefix/trip-count.py", 
       "sparkSubmitParameters": "--conf spark.driver.cores=5  --conf spark.executor.memory=20G --conf spark.driver.memory=15G --conf spark.executor.cores=6"
    }
  }, 
  "configurationOverrides": {
    "applicationConfiguration": [
      {
        "classification": "spark-defaults", 
        "properties": {
          "spark.dynamicAllocation.enabled":"false"
         }
      },
      {
        "classification": "emr-job-submitter",
        "properties": {
            "jobsubmitter.node.selector.eks.amazonaws.com/capacityType": "ON_DEMAND"
        }
      }
    ], 
    "monitoringConfiguration": {
      "cloudWatchMonitoringConfiguration": {
        "logGroupName": "/emr-containers/jobs", 
        "logStreamNamePrefix": "demo"
      }, 
      "s3MonitoringConfiguration": {
        "logUri": "s3://joblogs"
      }
    }
  }
}
EOF
aws emr-containers start-job-run --cli-input-json file:///spark-python-in-s3-nodeselector-job-submitter.json

StartJobRun 为任务提交者 Pod 请求单可用区型节点放置

cat >spark-python-in-s3-nodeselector-job-submitter-az.json << EOF
{
  "name": "spark-python-in-s3-nodeselector", 
  "virtualClusterId": "virtual-cluster-id", 
  "executionRoleArn": "execution-role-arn", 
  "releaseLabel": "emr-6.11.0-latest", 
  "jobDriver": {
    "sparkSubmitJobDriver": {
      "entryPoint": "s3://S3-prefix/trip-count.py", 
       "sparkSubmitParameters": "--conf spark.driver.cores=5  --conf spark.executor.memory=20G --conf spark.driver.memory=15G --conf spark.executor.cores=6"
    }
  }, 
  "configurationOverrides": {
    "applicationConfiguration": [
      {
        "classification": "spark-defaults", 
        "properties": {
          "spark.dynamicAllocation.enabled":"false"
         }
      },
      {
        "classification": "emr-job-submitter",
        "properties": {
            "jobsubmitter.node.selector.topology.kubernetes.io/zone": "Availability Zone"
        }
      }
    ], 
    "monitoringConfiguration": {
      "cloudWatchMonitoringConfiguration": {
        "logGroupName": "/emr-containers/jobs", 
        "logStreamNamePrefix": "demo"
      }, 
      "s3MonitoringConfiguration": {
        "logUri": "s3://joblogs"
      }
    }
  }
}
EOF
aws emr-containers start-job-run --cli-input-json file:///spark-python-in-s3-nodeselector-job-submitter-az.json

StartJobRun使用单可用区和 Amazon EC2 实例类型放置来请求任务提交者 pod

{
  "name": "spark-python-in-s3-nodeselector", 
  "virtualClusterId": "virtual-cluster-id", 
  "executionRoleArn": "execution-role-arn", 
  "releaseLabel": "emr-6.11.0-latest", 
  "jobDriver": {
    "sparkSubmitJobDriver": {
      "entryPoint": "s3://S3-prefix/trip-count.py", 
       "sparkSubmitParameters": "--conf spark.driver.cores=5  --conf spark.kubernetes.pyspark.pythonVersion=3 --conf spark.executor.memory=20G --conf spark.driver.memory=15G --conf spark.executor.cores=6 --conf spark.sql.shuffle.partitions=1000"
    }
  }, 
  "configurationOverrides": {
    "applicationConfiguration": [
      {
        "classification": "spark-defaults", 
        "properties": {
          "spark.dynamicAllocation.enabled":"false",
         }
      },
      {
        "classification": "emr-job-submitter",
        "properties": {
            "jobsubmitter.node.selector.topology.kubernetes.io/zone": "Availability Zone",
            "jobsubmitter.node.selector.node.kubernetes.io/instance-type":"m5.4xlarge"
        }
      }
    ], 
    "monitoringConfiguration": {
      "cloudWatchMonitoringConfiguration": {
        "logGroupName": "/emr-containers/jobs", 
        "logStreamNamePrefix": "demo"
      }, 
      "s3MonitoringConfiguration": {
        "logUri": "s3://joblogs"
      }
    }
  }
}

StartJobRun使用自定义日志记录容器镜像和内存进行请求 CPU

{
  "name": "spark-python", 
  "virtualClusterId": "virtual-cluster-id", 
  "executionRoleArn": "execution-role-arn", 
  "releaseLabel": "emr-6.11.0-latest", 
  "jobDriver": {
    "sparkSubmitJobDriver": {
      "entryPoint": "s3://S3-prefix/trip-count.py"
    }
  }, 
  "configurationOverrides": {
    "applicationConfiguration": [
      {
        "classification": "emr-job-submitter",
        "properties": {
            "jobsubmitter.logging.image": "YOUR_ECR_IMAGE_URL",
            "jobsubmitter.logging.request.memory": "200Mi",
            "jobsubmitter.logging.request.cores": "0.5"
        }
      }
    ], 
    "monitoringConfiguration": {
      "cloudWatchMonitoringConfiguration": {
        "logGroupName": "/emr-containers/jobs", 
        "logStreamNamePrefix": "demo"
      }, 
      "s3MonitoringConfiguration": {
        "logUri": "s3://joblogs"
      }
    }
  }
}