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Spark standalone集群安装

时间：2015-11-11 16:48:52      阅读：787      评论：0      收藏：0      [点我收藏+]

标签：spark

本文不会搞什么Yarn混搭Spark，只想建立一个纯粹的Spark环境，太多层东西搅和在一起，不靠谱。

创建spark服务运行帐号

# useradd smile

smile帐号就是spark服务的运行帐号。


下载安装包并测试

在root帐号下，下载最新安装包，注意不是source，而是bin安装包，支持hadoop2.6以后的

wget http://mirrors.cnnic.cn/apache/spark/spark-1.5.1/spark-1.5.1-bin-hadoop2.6.tgz

解压到下面的目录，并将owner和group设置成smile帐号，再建立链接。

wget http://mirrors.cnnic.cn/apache/spark/spark-1.5.1/spark-1.5.1-bin-hadoop2.6.tgz
tar zxvf spark-1.5.1-bin-hadoop2.6.tgz
chown -R smile:smile spark-1.5.1-bin-hadoop2.6
ln -s spark-1.5.1-bin-hadoop2.6 spark
chown -R smile:smile spark

进入目录

cd /data/slot0/spark/
./sbin/start-master.sh
starting org.apache.spark.deploy.master.Master, logging to /data/slot0/spark-1.5.1-bin-hadoop2.6/sbin/../logs/spark-smile-org.apache.spark.deploy.master.Master-1-10-149-11-157.out

启动成功。查看web界面 http://your-host:8080

技术分享


测试成功。关闭命令也很简单

$ sbin/stop-master.sh
stopping org.apache.spark.deploy.master.Master


基于zookeeper建立高可用集群

将第一个节点作为master

现在打算用3台服务器建立集群，使用zookeeper进行选举，确保总有一个可用的master，其他两个总是slave

在第一台服务器上，进入spark/conf目录，复制spark-env.sh.template为spark-env.sh文件

然后添加如下设置

SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER"
SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.zookeeper.url=host1:2181,host2:2181,host3:2181"
SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.zookeeper.dir=/vehicle_spark"
export SPARK_DAEMON_JAVA_OPTS

启动服务为master

./sbin/start-master.sh


将后续节点作为slave启动

在另外2台spark 服务器上启动slave

./sbin/start-slave.sh spark://master-ip:7077


这样，另外两台slave的web站点无法访问，只能访问第一台的web站点

站点会显示

alive works: 2

同样的方法可以不断增加，除了master之外，所有slave都是worker，可以执行计算任务。


用shell测试连接master

./bin/spark-shell --master spark://your-master:7077
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Using Spark‘s repl log4j profile: org/apache/spark/log4j-defaults-repl.properties
To adjust logging level use sc.setLogLevel("INFO")
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  ‘_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.5.1
      /_/

Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_45)
Type in expressions to have them evaluated.
Type :help for more information.
15/11/10 13:41:06 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
Spark context available as sc.
15/11/10 13:41:07 WARN General: Plugin (Bundle) "org.datanucleus" is already registered. Ensure you dont have multiple JAR versions of the same plugin in the classpath. The URL "file:/data/slot0/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-core-3.2.10.jar" is already registered, and you are trying to register an identical plugin located at URL "file:/data/slot0/spark/lib/datanucleus-core-3.2.10.jar."
15/11/10 13:41:07 WARN General: Plugin (Bundle) "org.datanucleus.api.jdo" is already registered. Ensure you dont have multiple JAR versions of the same plugin in the classpath. The URL "file:/data/slot0/spark/lib/datanucleus-api-jdo-3.2.6.jar" is already registered, and you are trying to register an identical plugin located at URL "file:/data/slot0/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-api-jdo-3.2.6.jar."
15/11/10 13:41:07 WARN General: Plugin (Bundle) "org.datanucleus.store.rdbms" is already registered. Ensure you dont have multiple JAR versions of the same plugin in the classpath. The URL "file:/data/slot0/spark/lib/datanucleus-rdbms-3.2.9.jar" is already registered, and you are trying to register an identical plugin located at URL "file:/data/slot0/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-rdbms-3.2.9.jar."
15/11/10 13:41:07 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
15/11/10 13:41:08 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
15/11/10 13:41:10 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
15/11/10 13:41:10 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
15/11/10 13:41:11 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/11/10 13:41:11 WARN General: Plugin (Bundle) "org.datanucleus" is already registered. Ensure you dont have multiple JAR versions of the same plugin in the classpath. The URL "file:/data/slot0/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-core-3.2.10.jar" is already registered, and you are trying to register an identical plugin located at URL "file:/data/slot0/spark/lib/datanucleus-core-3.2.10.jar."
15/11/10 13:41:11 WARN General: Plugin (Bundle) "org.datanucleus.api.jdo" is already registered. Ensure you dont have multiple JAR versions of the same plugin in the classpath. The URL "file:/data/slot0/spark/lib/datanucleus-api-jdo-3.2.6.jar" is already registered, and you are trying to register an identical plugin located at URL "file:/data/slot0/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-api-jdo-3.2.6.jar."
15/11/10 13:41:11 WARN General: Plugin (Bundle) "org.datanucleus.store.rdbms" is already registered. Ensure you dont have multiple JAR versions of the same plugin in the classpath. The URL "file:/data/slot0/spark/lib/datanucleus-rdbms-3.2.9.jar" is already registered, and you are trying to register an identical plugin located at URL "file:/data/slot0/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-rdbms-3.2.9.jar."
15/11/10 13:41:11 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
15/11/10 13:41:11 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
15/11/10 13:41:13 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
15/11/10 13:41:13 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
SQL context available as sqlContext.

scala>

看来需要学习scala语言了。：）

spark有点不靠谱，有时候连接会报错，退出再来就好了。spark-sql也遇到相同的问题。

$ bin/spark-shell --master spark://master-host:7077
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Using Spark‘s repl log4j profile: org/apache/spark/log4j-defaults-repl.properties
To adjust logging level use sc.setLogLevel("INFO")
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  ‘_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.5.1
      /_/

Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_45)
Type in expressions to have them evaluated.
Type :help for more information.
15/11/10 22:12:36 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
15/11/10 22:12:37 ERROR SparkDeploySchedulerBackend: Application has been killed. Reason: Master removed our application: FAILED
15/11/10 22:12:37 WARN QueuedThreadPool: 8 threads could not be stopped
15/11/10 22:12:37 ERROR SparkContext: Error initializing SparkContext.
java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext
	at org.apache.spark.SparkContext.org$apache$spark$SparkContext$$assertNotStopped(SparkContext.scala:104)
	at org.apache.spark.SparkContext.getSchedulingMode(SparkContext.scala:1575)
	at org.apache.spark.SparkContext.postEnvironmentUpdate(SparkContext.scala:2154)
	at org.apache.spark.SparkContext.<init>(SparkContext.scala:571)
	at org.apache.spark.repl.SparkILoop.createSparkContext(SparkILoop.scala:1017)
	at $line3.$read$$iwC$$iwC.<init>(<console>:9)
	at $line3.$read$$iwC.<init>(<console>:18)
	at $line3.$read.<init>(<console>:20)
	at $line3.$read$.<init>(<console>:24)
	at $line3.$read$.<clinit>(<console>)
	at $line3.$eval$.<init>(<console>:7)
	at $line3.$eval$.<clinit>(<console>)
	at $line3.$eval.$print(<console>)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
	at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340)
	at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
	at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
	at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
	at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
	at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:125)
	at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
	at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
	at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
	at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
	at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
	at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:108)
	at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
	at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
	at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
	at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
	at org.apache.spark.repl.Main$.main(Main.scala:31)
	at org.apache.spark.repl.Main.main(Main.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext
	at org.apache.spark.SparkContext.org$apache$spark$SparkContext$$assertNotStopped(SparkContext.scala:104)
	at org.apache.spark.SparkContext.getSchedulingMode(SparkContext.scala:1575)
	at org.apache.spark.SparkContext.postEnvironmentUpdate(SparkContext.scala:2154)
	at org.apache.spark.SparkContext.<init>(SparkContext.scala:571)
	at org.apache.spark.repl.SparkILoop.createSparkContext(SparkILoop.scala:1017)
	at $iwC$$iwC.<init>(<console>:9)
	at $iwC.<init>(<console>:18)
	at <init>(<console>:20)
	at .<init>(<console>:24)
	at .<clinit>(<console>)
	at .<init>(<console>:7)
	at .<clinit>(<console>)
	at $print(<console>)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
	at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340)
	at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
	at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
	at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
	at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
	at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:125)
	at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
	at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
	at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
	at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
	at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
	at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:108)
	at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
	at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
	at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
	at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
	at org.apache.spark.repl.Main$.main(Main.scala:31)
	at org.apache.spark.repl.Main.main(Main.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

java.lang.NullPointerException
	at org.apache.spark.sql.execution.ui.SQLListener.<init>(SQLListener.scala:34)
	at org.apache.spark.sql.SQLContext.<init>(SQLContext.scala:77)
	at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:72)
	at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
	at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
	at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
	at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
	at org.apache.spark.repl.SparkILoop.createSQLContext(SparkILoop.scala:1028)
	at $iwC$$iwC.<init>(<console>:9)
	at $iwC.<init>(<console>:18)
	at <init>(<console>:20)
	at .<init>(<console>:24)
	at .<clinit>(<console>)
	at .<init>(<console>:7)
	at .<clinit>(<console>)
	at $print(<console>)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
	at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340)
	at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
	at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
	at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
	at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
	at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:132)
	at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply(SparkILoopInit.scala:124)
	at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
	at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoopInit.scala:124)
	at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
	at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.scala:159)
	at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkILoopInit.scala:108)
	at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:64)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
	at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
	at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
	at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
	at org.apache.spark.repl.Main$.main(Main.scala:31)
	at org.apache.spark.repl.Main.main(Main.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

<console>:10: error: not found: value sqlContext
       import sqlContext.implicits._
              ^
<console>:10: error: not found: value sqlContext
       import sqlContext.sql
              ^

scala> exit


版权声明：本文为博主原创文章，未经博主允许不得转载。

Spark standalone集群安装

标签：spark

原文地址：http://blog.csdn.net/csfreebird/article/details/49721235
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