eclipse开发spark程序配置本地运行

今天简单讲一下在local模式下用eclipse开发一个简单的spark应用程序，并在本地运行测试。
1.下载最新版的scala for eclipse版本，选择windows 64位，下载网址：http://scala-ide.org/download/sdk.html


下载好后解压到D盘，打开并选择工作空间。


然后创建一个测试项目ScalaDev,右击项目选择Properties，在对话框中选择Scala Compiler，在右面页签中勾选Use Project Settings和Scala Installation点击ok，保存配置。



2.添加spark1.6.0的jar文件依赖spark-assembly-1.6.0-hadoop2.6.0.jar，并添加到项目中。
spark-assembly-1.6.0-hadoop2.6.0.jar在spark-1.6.0-bin-hadoop2.6.tgz包中的lib下面。



右击ScalaDev项目选择Build Path->Configure Build Path


注：如果你选择了Scala Installation为Latest2.11 bundle（dynamic）项目会报如下的错误：ScalaDev工程上出现一个红叉，查看Problems下面的原因是scala编译版本和spark的不一致导致。
More than one scala library found in the build path (D:/eclipse/plugins/org.scala-lang.scala-library_2.11.7.v20150622-112736-1fbce4612c.jar, F:/IMF/Big_Data_Software/spark-1.6.0-bin-hadoop2.6/lib/spark-assembly-1.6.0-hadoop2.6.0.jar).At least one has an incompatible version. Please update the project build path so it contains only one compatible scala library.




解决方法：右击Scala Library Container->Properties，在弹出框中选择Latest 2.10 bundle（dynamic），保存即可。



3.在src下创建spark工程包，并创建入口类。
选择项目New -> Package创建com.imf.spark包;



选择com.imf.spark包名，创建Scala Object;



测试程序前，要将spark-1.6.0-bin-hadoop2.6目录中的README.md文件拷贝到D://testspark//目录中，代码如下：

package com.imf.spark

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
/**
 * 用户scala开发本地测试的spark wordcount程序
 */
object WordCount {
   def main(args: Array[String]): Unit = {
     /**
      * 1.创建Spark的配置对象SparkConf，设置Spark程序的运行时的配置信息，
      * 例如：通过setMaster来设置程序要链接的Spark集群的Master的URL,如果设置为local,
      * 则代表Spark程序在本地运行，特别适合于机器配置条件非常差的情况。
      */
     //创建SparkConf对象
     val conf = new SparkConf()
     //设置应用程序名称，在程序运行的监控界面可以看到名称
     conf.setAppName("My First Spark App!")
     //设置local使程序在本地运行，不需要安装Spark集群
     conf.setMaster("local")
     /**
      * 2.创建SparkContext对象
      * SparkContext是spark程序所有功能的唯一入口，无论是采用Scala,java,python,R等都必须有一个SprakContext
      * SparkContext核心作用：初始化spark应用程序运行所需要的核心组件，包括DAGScheduler,TaskScheduler,SchedulerBackend
      * 同时还会负责Spark程序往Master注册程序等；
      * SparkContext是整个应用程序中最为至关重要的一个对象；
      */
     //通过创建SparkContext对象，通过传入SparkConf实例定制Spark运行的具体参数和配置信息
     val sc = new SparkContext(conf)

     /**
      * 3.根据具体数据的来源（HDFS,HBase,Local,FS,DB,S3等）通过SparkContext来创建RDD；
      * RDD的创建基本有三种方式：根据外部的数据来源（例如HDFS）、根据Scala集合、由其他的RDD操作；
      * 数据会被RDD划分成为一系列的Partitions,分配到每个Partition的数据属于一个Task的处理范畴；
      */
     //读取本地文件，并设置一个partition
     val lines = sc.textFile("D://testspark//README.md",1)

     /**
      * 4.对初始的RDD进行Transformation级别的处理，例如map,filter等高阶函数的变成，来进行具体的数据计算
      * 4.1.将每一行的字符串拆分成单个单词
      */
     //对每一行的字符串进行拆分并把所有行的拆分结果通过flat合并成一个大的集合
      val words = lines.flatMap { line => line.split(" ") }
     /**
      * 4.2.在单词拆分的基础上对每个单词实例计数为1，也就是word => (word,1)
      */
     val pairs = words.map{word =>(word,1)}

     /**
      * 4.3.在每个单词实例计数为1基础上统计每个单词在文件中出现的总次数
      */
     //对相同的key进行value的累积（包括Local和Reducer级别同时Reduce）
     val wordCounts = pairs.reduceByKey(_+_)
     //打印输出
     wordCounts.foreach(pair => println(pair._1+":"+pair._2))
     sc.stop()
   }
}

运行结果：

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
16/01/26 08:23:37 INFO SparkContext: Running Spark version 1.6.0
16/01/26 08:23:42 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/01/26 08:23:42 ERROR Shell: Failed to locate the winutils binary in the hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
    at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:355)
    at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:370)
    at org.apache.hadoop.util.Shell.<clinit>(Shell.java:363)
    at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:79)
    at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:104)
    at org.apache.hadoop.security.Groups.<init>(Groups.java:86)
    at org.apache.hadoop.security.Groups.<init>(Groups.java:66)
    at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:280)
    at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:271)
    at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:248)
    at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:763)
    at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:748)
    at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:621)
    at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2136)
    at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2136)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2136)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:322)
    at com.dt.spark.WordCount$.main(WordCount.scala:29)
    at com.dt.spark.WordCount.main(WordCount.scala)
16/01/26 08:23:42 INFO SecurityManager: Changing view acls to: vivi
16/01/26 08:23:42 INFO SecurityManager: Changing modify acls to: vivi
16/01/26 08:23:42 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(vivi); users with modify permissions: Set(vivi)
16/01/26 08:23:43 INFO Utils: Successfully started service 'sparkDriver' on port 54663.
16/01/26 08:23:43 INFO Slf4jLogger: Slf4jLogger started
16/01/26 08:23:43 INFO Remoting: Starting remoting
16/01/26 08:23:43 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.100.102:54676]
16/01/26 08:23:43 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 54676.
16/01/26 08:23:43 INFO SparkEnv: Registering MapOutputTracker
16/01/26 08:23:43 INFO SparkEnv: Registering BlockManagerMaster
16/01/26 08:23:43 INFO DiskBlockManager: Created local directory at C:\Users\vivi\AppData\Local\Temp\blockmgr-5f59f3c2-3b87-49c5-a1ae-e21847aac44b
16/01/26 08:23:43 INFO MemoryStore: MemoryStore started with capacity 1813.7 MB
16/01/26 08:23:43 INFO SparkEnv: Registering OutputCommitCoordinator
16/01/26 08:23:43 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/01/26 08:23:43 INFO SparkUI: Started SparkUI at http://192.168.100.102:4040
16/01/26 08:23:43 INFO Executor: Starting executor ID driver on host localhost
16/01/26 08:23:43 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 54683.
16/01/26 08:23:43 INFO NettyBlockTransferService: Server created on 54683
16/01/26 08:23:43 INFO BlockManagerMaster: Trying to register BlockManager
16/01/26 08:23:43 INFO BlockManagerMasterEndpoint: Registering block manager localhost:54683 with 1813.7 MB RAM, BlockManagerId(driver, localhost, 54683)
16/01/26 08:23:43 INFO BlockManagerMaster: Registered BlockManager
16/01/26 08:23:46 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 153.6 KB, free 153.6 KB)
16/01/26 08:23:46 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 13.9 KB, free 167.6 KB)
16/01/26 08:23:46 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on localhost:54683 (size: 13.9 KB, free: 1813.7 MB)
16/01/26 08:23:46 INFO SparkContext: Created broadcast 0 from textFile at WordCount.scala:37
16/01/26 08:23:47 WARN : Your hostname, vivi-PC resolves to a loopback/non-reachable address: fe80:0:0:0:5937:95c4:86da:2f43%30, but we couldn't find any external IP address!
16/01/26 08:23:48 INFO FileInputFormat: Total input paths to process : 1
16/01/26 08:23:48 INFO SparkContext: Starting job: foreach at WordCount.scala:56
16/01/26 08:23:48 INFO DAGScheduler: Registering RDD 3 (map at WordCount.scala:48)
16/01/26 08:23:48 INFO DAGScheduler: Got job 0 (foreach at WordCount.scala:56) with 1 output partitions
16/01/26 08:23:48 INFO DAGScheduler: Final stage: ResultStage 1 (foreach at WordCount.scala:56)
16/01/26 08:23:48 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
16/01/26 08:23:48 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
16/01/26 08:23:48 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:48), which has no missing parents
16/01/26 08:23:48 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 4.0 KB, free 171.6 KB)
16/01/26 08:23:48 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.3 KB, free 173.9 KB)
16/01/26 08:23:48 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on localhost:54683 (size: 2.3 KB, free: 1813.7 MB)
16/01/26 08:23:48 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006
16/01/26 08:23:48 INFO DAGScheduler: Submitting 1 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:48)
16/01/26 08:23:48 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
16/01/26 08:23:48 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, partition 0,PROCESS_LOCAL, 2119 bytes)
16/01/26 08:23:48 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
16/01/26 08:23:48 INFO HadoopRDD: Input split: file:/D:/testspark/README.md:0+3359
16/01/26 08:23:48 INFO deprecation: mapred.tip.id is deprecated. Instead, use mapreduce.task.id
16/01/26 08:23:48 INFO deprecation: mapred.task.id is deprecated. Instead, use mapreduce.task.attempt.id
16/01/26 08:23:48 INFO deprecation: mapred.task.is.map is deprecated. Instead, use mapreduce.task.ismap
16/01/26 08:23:48 INFO deprecation: mapred.task.partition is deprecated. Instead, use mapreduce.task.partition
16/01/26 08:23:48 INFO deprecation: mapred.job.id is deprecated. Instead, use mapreduce.job.id
16/01/26 08:23:48 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 2253 bytes result sent to driver
16/01/26 08:23:48 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 177 ms on localhost (1/1)
16/01/26 08:23:48 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
16/01/26 08:23:48 INFO DAGScheduler: ShuffleMapStage 0 (map at WordCount.scala:48) finished in 0.186 s
16/01/26 08:23:48 INFO DAGScheduler: looking for newly runnable stages
16/01/26 08:23:48 INFO DAGScheduler: running: Set()
16/01/26 08:23:48 INFO DAGScheduler: waiting: Set(ResultStage 1)
16/01/26 08:23:48 INFO DAGScheduler: failed: Set()
16/01/26 08:23:48 INFO DAGScheduler: Submitting ResultStage 1 (ShuffledRDD[4] at reduceByKey at WordCount.scala:54), which has no missing parents
16/01/26 08:23:48 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 2.5 KB, free 176.4 KB)
16/01/26 08:23:48 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 1581.0 B, free 177.9 KB)
16/01/26 08:23:48 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on localhost:54683 (size: 1581.0 B, free: 1813.7 MB)
16/01/26 08:23:48 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1006
16/01/26 08:23:48 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (ShuffledRDD[4] at reduceByKey at WordCount.scala:54)
16/01/26 08:23:48 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks
16/01/26 08:23:48 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1, localhost, partition 0,NODE_LOCAL, 1894 bytes)
16/01/26 08:23:48 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)
16/01/26 08:23:48 INFO ShuffleBlockFetcherIterator: Getting 1 non-empty blocks out of 1 blocks
16/01/26 08:23:48 INFO ShuffleBlockFetcherIterator: Started 0 remote fetches in 2 ms
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16/01/26 08:23:48 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 1165 bytes result sent to driver
16/01/26 08:23:48 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 61 ms on localhost (1/1)
16/01/26 08:23:48 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool 
16/01/26 08:23:48 INFO DAGScheduler: ResultStage 1 (foreach at WordCount.scala:56) finished in 0.061 s
16/01/26 08:23:48 INFO DAGScheduler: Job 0 finished: foreach at WordCount.scala:56, took 0.328012 s
16/01/26 08:23:48 INFO SparkUI: Stopped Spark web UI at http://192.168.100.102:4040
16/01/26 08:23:48 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
16/01/26 08:23:48 INFO MemoryStore: MemoryStore cleared
16/01/26 08:23:48 INFO BlockManager: BlockManager stopped
16/01/26 08:23:48 INFO BlockManagerMaster: BlockManagerMaster stopped
16/01/26 08:23:48 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
16/01/26 08:23:48 INFO SparkContext: Successfully stopped SparkContext
16/01/26 08:23:48 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
16/01/26 08:23:48 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
16/01/26 08:23:48 INFO ShutdownHookManager: Shutdown hook called
16/01/26 08:23:48 INFO ShutdownHookManager: Deleting directory C:\Users\vivi\AppData\Local\Temp\spark-56f9ed0a-5671-449a-955a-041c63569ff2

说明：上面程序运行错误，是加载hadoop的配置，因为运行在本地，是找不到的，但不影响测试。

评论

1 楼 bo_hai 2016-06-12  

target jvm版本也要选择正确。不能选择太高。2.10对应是JVM1.7