我是Spark的新手。现在我遇到了一个问题：当我在命令行中启动独立spark集群中的程序时：
./spark-submit --class scratch.Pi --deploy-mode cluster --executor-memory 5g --name pi --driver-memory 5g --driver-java-options "-XX:MaxPermSize=1024m" --master spark://bx-42-68:7077 hdfs://bx-42-68:9000/jars/pi.jar
会抛出以下错误：
15/01/28 19:48:51 INFO Slf4jLogger: Slf4jLogger started
15/01/28 19:48:51 INFO Utils: Successfully started service 'driverClient' on port 59290.
Sending launch command to spark://bx-42-68:7077
Driver successfully submitted as driver-20150128194852-0003
... waiting before polling master for driver state
... polling master for driver state
State of driver-20150128194852-0003 is FAILED
日志后的集群输出主管：
15/01/28 19:48:52 INFO Master: Driver submitted org.apache.spark.deploy.worker.DriverWrapper
15/01/28 19:48:52 INFO Master: Launching driver driver-20150128194852-0003 on worker worker-20150126133948-bx-42-151-26286
15/01/28 19:48:55 INFO Master: Removing driver: driver-20150128194852-0003
15/01/28 19:48:57 INFO Master: akka.tcp://driverClient@bx-42-68:59290 got disassociated, removing it.
15/01/28 19:48:57 INFO Master: akka.tcp://driverClient@bx-42-68:59290 got disassociated, removing it.
15/01/28 19:48:57 WARN ReliableDeliverySupervisor: Association with remote system [akka.tcp://driverClient@bx-42-68:59290] has failed, address is now gated for [5000] ms. Reason is: [Disassociated].
15/01/28 19:48:57 INFO LocalActorRef: Message [akka.remote.transport.ActorTransportAdapter$DisassociateUnderlying] from Actor[akka://sparkMaster/deadLetters] to Actor[akka://sparkMaster/system/transports/akkaprotocolmanager.tcp0/akkaProtocol-tcp%3A%2F%2FsparkMaster%4010.16.42.68%3A48091-16#-1393479428] was not delivered. [9] dead letters encountered. This logging can be turned off or adjusted with configuration settings 'akka.log-dead-letters' and 'akka.log-dead-letters-during-shutdown'.
用于启动驱动程序输出的相应工作人员：
15/01/28 19:48:52 INFO Worker: Asked to launch driver driver-20150128194852-0003
15/01/28 19:48:52 INFO DriverRunner: Copying user jar hdfs://bx-42-68:9000/jars/pi.jar to /data11/spark-1.2.0-bin-hadoop2.4/work/driver-20150128194852-0003/pi.jar
Spark assembly has been built with Hive, including Datanucleus jars on classpath
15/01/28 19:48:55 INFO DriverRunner: Launch Command: "/opt/apps/jdk-1.7.0_60/bin/java" "-cp" "/data11/spark-1.2.0-bin-hadoop2.4/work/driver-20150128194852-0003/pi.jar:::/data11/spark-1.2.0-bin-hadoop2.4/sbin/../conf:/data11/spark-1.2.0-bin-hadoop2.4/lib/spark-assembly-1.2.0-hadoop2.4.0.jar:/data11/spark-1.2.0-bin-hadoop2.4/lib/datanucleus-api-jdo-3.2.6.jar:/data11/spark-1.2.0-bin-hadoop2.4/lib/datanucleus-core-3.2.10.jar:/data11/spark-1.2.0-bin-hadoop2.4/lib/datanucleus-rdbms-3.2.9.jar" "-XX:MaxPermSize=128m" "-Dspark.executor.memory=5g" "-Dspark.akka.askTimeout=10" "-Dspark.rdd.compress=true" "-Dspark.executor.extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps" "-Dspark.serializer=org.apache.spark.serializer.KryoSerializer" "-Dspark.app.name=YANL" "-Dspark.driver.extraJavaOptions=-XX:MaxPermSize=1024m" "-Dspark.jars=hdfs://bx-42-68:9000/jars/pi.jar" "-Dspark.master=spark://bx-42-68:7077" "-Dspark.storage.memoryFraction=0.6" "-Dakka.loglevel=WARNING" "-XX:MaxPermSize=1024m" "-Xms5120M" "-Xmx5120M" "org.apache.spark.deploy.worker.DriverWrapper" "akka.tcp://sparkWorker@bx-42-151:26286/user/Worker" "scratch.Pi"
15/01/28 19:48:55 WARN Worker: Driver driver-20150128194852-0003 exited with failure
我的spark-env.sh是：
export SCALA_HOME=/opt/apps/scala-2.11.5
export JAVA_HOME=/opt/apps/jdk-1.7.0_60
export SPARK_HOME=/data11/spark-1.2.0-bin-hadoop2.4
export PATH=$JAVA_HOME/bin:$PATH
export SPARK_MASTER_IP=`hostname -f`
export SPARK_LOCAL_IP=`hostname -f`
export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=10.16.42.68:2181,10.16.42.134:2181,10.16.42.151:2181,10.16.42.150:2181,10.16.42.125:2181 -Dspark.deploy.zookeeper.dir=/spark"
SPARK_WORKER_MEMORY=43g
SPARK_WORKER_CORES=22
我的spark-defaults.conf是：
spark.executor.extraJavaOptions -XX:+PrintGCDetails -XX:+PrintGCTimeStamps
spark.executor.memory 20g
spark.rdd.compress true
spark.storage.memoryFraction 0.6
spark.serializer org.apache.spark.serializer.KryoSerializer
然而，当我使用以下命令使用 client 模式启动程序时，它可以正常工作。
./spark-submit --class scratch.Pi --deploy-mode client --executor-memory 5g --name pi --driver-memory 5g --driver-java-options "-XX:MaxPermSize=1024m" --master spark://bx-42-68:7077 /data11/pi.jar
答案 0 :(得分：0)
它在“客户端”模式下而不是在“集群”模式下工作的原因是因为在独立集群中不支持“集群”模式。（在spark文档中提到）。
Alternatively, if your application is submitted from a machine far from the worker machines (e.g. locally on your laptop), it is common to use cluster mode to minimize network latency between the drivers and the executors.
请注意，独立版目前不支持群集模式 集群，Mesos集群或python应用程序。
如果您查看spark文档中的“提交应用程序”部分，则会清楚地提到群集模式的支持在独立群集中不可用。
参考链接：http://spark.apache.org/docs/1.2.0/submitting-applications.html
转到上面的链接，查看“使用spark-submit启动应用程序”部分。
认为它会有所帮助。感谢。