如何激发提交作业到其他集群上的纱线?

问题描述 投票:0回答:1

我有一个安装了spark的docker容器,我正在尝试使用marathon将作业提交到其他集群上的yarn。 docker容器具有yarn和hadoop conf dir的导出值,yarn文件还包含emr master ip的正确地址,但我不确定它作为localhost的位置?

ENV YARN_CONF_DIR="/opt/yarn-site.xml"
ENV HADOOP_CONF_DIR="/opt/spark-2.2.0-bin-hadoop2.6"

Yarn.xml

<property>
    <name>yarn.resourcemanager.hostname</name>
    <value>xx.xxx.x.xx</value>
  </property>

命令:

  "cmd": "/opt/spark-2.2.0-bin-hadoop2.6/bin/spark-submit --verbose \\\n --name emr_external_mpv_streaming \\\n --deploy-mode client \\\n --master yarn\\\n --conf spark.executor.instances=4 \\\n --conf spark.executor.cores=1 \\\n --conf spark.executor.memory=1g \\\n --conf spark.driver.memory=1g \\\n --conf spark.cores.max=4 \\\n --conf spark.executorEnv.EXT_WH_HOST=$EXT_WH_HOST \\\n --conf spark.executorEnv.EXT_WH_PASSWORD=$EXT_WH_PASSWORD \\\n --conf spark.executorEnv.KAFKA_BROKER_LIST=$_KAFKA_BROKER_LIST \\\n --conf spark.executorEnv.SCHEMA_REGISTRY_URL=$SCHEMA_REGISTRY_URL \\\n --conf spark.executorEnv.AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \\\n --conf spark.executorEnv.AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \\\n --conf spark.executorEnv.STAGING_S3_BUCKET=$STAGING_S3_BUCKET \\\n --conf spark.executorEnv.KAFKA_GROUP_ID=$KAFKA_GROUP_ID \\\n --conf spark.executorEnv.MAX_RATE=$MAX_RATE \\\n --conf spark.executorEnv.KAFKA_MAX_POLL_MS=$KAFKA_MAX_POLL_MS \\\n --conf spark.executorEnv.KAFKA_MAX_POLL_RECORDS=$KAFKA_MAX_POLL_RECORDS \\\n --class com.ticketnetwork.edwstream.external.MapPageView \\\n /opt/edw-stream-external-mpv_2.11-2-SNAPSHOT.jar",

我尝试指定--deploy-mode cluster \\ n --master yarn \\ n - 同样的错误

错误:

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
18/09/10 20:41:24 INFO SparkContext: Running Spark version 2.2.0
18/09/10 20:41:25 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/09/10 20:41:25 INFO SparkContext: Submitted application: edw-stream-ext-mpv-emr-prod
18/09/10 20:41:25 INFO SecurityManager: Changing view acls to: root
18/09/10 20:41:25 INFO SecurityManager: Changing modify acls to: root
18/09/10 20:41:25 INFO SecurityManager: Changing view acls groups to: 
18/09/10 20:41:25 INFO SecurityManager: Changing modify acls groups to: 
18/09/10 20:41:25 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(root); groups with view permissions: Set(); users  with modify permissions: Set(root); groups with modify permissions: Set()
18/09/10 20:41:25 INFO Utils: Successfully started service 'sparkDriver' on port 35868.
18/09/10 20:41:25 INFO SparkEnv: Registering MapOutputTracker
18/09/10 20:41:25 INFO SparkEnv: Registering BlockManagerMaster
18/09/10 20:41:25 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
18/09/10 20:41:25 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
18/09/10 20:41:25 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-5526b967-2be9-44bf-a86f-79ef72f2ac0f
18/09/10 20:41:25 INFO MemoryStore: MemoryStore started with capacity 366.3 MB
18/09/10 20:41:26 INFO SparkEnv: Registering OutputCommitCoordinator
18/09/10 20:41:26 INFO Utils: Successfully started service 'SparkUI' on port 4040.
18/09/10 20:41:26 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://10.150.4.45:4040
18/09/10 20:41:26 INFO SparkContext: Added JAR file:/opt/edw-stream-external-mpv_2.11-2-SNAPSHOT.jar at spark://10.150.4.45:35868/jars/edw-stream-external-mpv_2.11-2-SNAPSHOT.jar with timestamp 1536612086416
18/09/10 20:41:26 INFO RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
18/09/10 20:41:27 INFO Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8032. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
18/09/10 20:41:28 INFO Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8032. Already tried 1 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
18/09/10 20:41:29 INFO Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8032. Already tried 2 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
apache-spark hadoop yarn amazon-emr
1个回答
3
投票

0.0.0.0是默认的主机名属性,8032是默认的端口号。

您获得默认值的一个原因是Hadoop环境变量都没有正确设置。你的HADOOP_CONF_DIR需要是Spark的(或Hadoop的)conf文件夹,而不是Spark提取的基本文件夹。如果使用HiveContext,该目录必须包含core-site.xmlyarn-site.xmlhdfs-site.xmlhive-site.xml

然后,如果yarn-site.xml位于上述位置,则不需要YARN_CONF_DIR,但如果设置它,则需要是实际目录,而不是直接到文件。

此外,您可能需要设置多个主机名。例如,生产级YARN集群将具有两个用于容错的ResourceManagers。此外,如果启用了Kerberos键盘和主体,则可能需要设置一些Kerberos键盘和主体。

如果你已经有Mesos / Marathon,我不确定你为什么要使用YARN

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