气流火花提交操作符

如何解决气流火花提交操作符

我将 spark2 的命令提交为：

    value = Varibale.get('value')
    cmd = """
                    spark2-submit --master yarn --deploy-mode cluster 
                    --driver-memory=10G 
                    --conf spark.dynamicAllocation.minexecutors=5
                    --conf spark.dynamicAllocation.maxExecutors=10 
                    --queue test 
                    --executor-memory=10G
                    --executor-cores=2
                    --conf spark.yarn.driver.memoryOverhead=5120
                    --conf spark.driver.maxResultSize=2G 
                    --conf spark.yarn.executor.memoryOverhead=5120 
                    --conf spark.kryoserializer.buffer.max=1000m 
                    --conf spark.executor.extrajavaoptions=-XX:+UseG1GC 
                    --conf spark.network.timeout=15000s
                    --conf spark.executor.heartbeatInterval=1500s 
                    --conf spark.task.maxDirectResultSize=8G 
                    --principal test-host@test
                    --keytab /home/test-host.keytab 
                    --conf spark.ui.view.acls="*" 
                    /home/test/test.py {0}
                    """.format(value)

    test = SSHOperator(task_id='TEST',ssh_conn_id='test-conn',command=cmd
                   )

我希望将其转换为 SparkSubmitOperator。另外，我需要 spark2 提交。

如何将上面的转换为 SparkSubmitOperator？ 到目前为止，我已经尝试过：

          
                                      
SparkSubmitOperator(task_id='TEST',conn_id='test-conn',application=f'/home/test/test.py {0}'.format(value),executor_cores=2,executor_memory='10g',)

解决方法

Airflow 中的 SparkSubmitOperator 需要的选项可以在字典中发送。请记住，字典中的键应该与函数的参数名称相同。

创建以下两个字典：

base_config = {
    "task_id":"TEST","conn_id":"test-conn","application": "/home/test/test.py"
    "executor-memory":"10G","driver-memory":"10G","executor-cores":2,"principal":"test-host@test","keytab":"/home/test-host.keytab","env_vars":{"SPARK_MAJOR_VERSION":2}
    }

spark_config = {
    "spark.master": "yarn","spark.submit.deployMode": "client","spark.yarn.queue":"test","spark.dynamicAllocation.minExecutors":5,"spark.dynamicAllocation.maxExecutors":10,"spark.yarn.driver.memoryOverhead":5120,"spark.driver.maxResultSize":"2G","spark.yarn.executor.memoryOverhead":5120,"spark.kryoserializer.buffer.max":"1000m","spark.executor.extraJavaOptions":"-XX:+UseG1GC","spark.network.timeout":"15000s","spark.executor.heartbeatInterval":"1500s","spark.task.maxDirectResultSize":"8G","spark.ui.view.acls":"*"
}

SparkSubmitOperator(**base_config,conf=spark_config)

这应该会驱动您的流程配置。