我正在学习一些数据科学,我正在尝试发现和理解与之相关的各种工具。
到目前为止,我在Mac OS上安装了Hadoop 2.8.0,现在我也想让Spark 2.1.1正常工作。我知道Spark不一定需要Hadoop环境才能工作,但我也知道让它在YARN上运行对于与其他应用程序共享数据非常有用。
在线阅读了不同的指南和建议之后,这就是我所做的:
在Hadoop配置文件中,我添加了 yarn-site.xml :
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>localhost</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>localhost:8030</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>localhost:8032</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>localhost:8088</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>localhost:8031</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>localhost:8033</value>
</property>
在Spark配置文件中,我添加了 spark-env.sh :
export SPARK_MASTER_IP=localhost
export SPARK_WORKER_CORES=1
export SPARK_WORKER_MEMORY=800m
export SPARK_WORKER_ISTANCES=1
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export SPARK_EXECUTOR_INSTANCES=1
export SPARK_LOCAL_IP=127.0.0.1
现在,在使用$HADOOP_HOME/sbin/start-dfs.sh
和$HADOOP_HOME/sbin/start-yarn.sh
启动Hadoop后,如果我尝试启动:
sudo spark-shell --master yarn
(如果我理解的话,这应该是让Spark运行Yarn的方法),在很长的时间后,我收到以下错误:
17/06/09 14:55:44 ERROR SparkContext: Error initializing SparkContext.
java.net.ConnectException: Call From Alessandro.local/192.168.2.1 to 0.0.0.0:8032 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.GeneratedConstructorAccessor8.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy12.getNewApplication(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationClientProtocolPBClientImpl.getNewApplication(ApplicationClientProtocolPBClientImpl.java:221)
at sun.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy13.getNewApplication(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.getNewApplication(YarnClientImpl.java:219)
at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.createApplication(YarnClientImpl.java:227)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:159)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:56)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:156)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:509)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2320)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:868)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:860)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:860)
at org.apache.spark.repl.Main$.createSparkSession(Main.scala:96)
at $line3.$read$$iw$$iw.<init>(<console>:15)
at $line3.$read$$iw.<init>(<console>:42)
at $line3.$read.<init>(<console>:44)
at $line3.$read$.<init>(<console>:48)
at $line3.$read$.<clinit>(<console>)
at $line3.$eval$.$print$lzycompute(<console>:7)
at $line3.$eval$.$print(<console>:6)
at $line3.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)
at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638)
at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637)
at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)
at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19)
at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681)
at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)
at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:38)
at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214)
at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37)
at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:105)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:920)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
at org.apache.spark.repl.Main$.doMain(Main.scala:69)
at org.apache.spark.repl.Main$.main(Main.scala:52)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:743)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 69 more
17/06/09 14:55:44 WARN YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request executors before the AM has registered!
我做错了什么?也许这是明显的,但我是新手,我需要一些帮助。
答案 0 :(得分:3)
异常中的0.0.0.0地址指出spark-shell未配置为获取YARN资源管理器的地址。 (参考this)
Spark从HADOOP_CONF_DIR或YARN_CONF_DIR中获取YARN ResourceManager的地址。在您的情况下,我怀疑HADOOP_CONF_DIR未正确设置。只是一种预感。希望这有帮助!