编写Spark的WordCount程序并提交到集群运行[含scala和java两个版本]

编写Spark的WordCount程序并提交到集群运行[含scala和java两个版本]

1. 开发环境

Jdk 1.7.0_72
Maven 3.2.1
Scala 2.10.6
Spark 1.6.2
Hadoop 2.6.4
IntelliJ IDEA 2016.1.1

2. 创建项目
1) 新建Maven项目

2) 在pom文件中导入依赖
pom.xml文件内容如下：

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.xuebusi</groupId>
    <artifactId>spark</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>1.7</maven.compiler.source>
        <maven.compiler.target>1.7</maven.compiler.target>
        <encoding>UTF-8</encoding>

        <!-- 这里对jar包版本做集中管理 -->
        <scala.version>2.10.6</scala.version>
        <spark.version>1.6.2</spark.version>
        <hadoop.version>2.6.4</hadoop.version>
    </properties>

    <dependencies>
        <dependency>
            <!-- scala语言核心包 -->
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>
        <dependency>
            <!-- spark核心包 -->
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.10</artifactId>
            <version>${spark.version}</version>
        </dependency>

        <dependency>
            <!-- hadoop的客户端,用于访问HDFS -->
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>${hadoop.version}</version>
        </dependency>
    </dependencies>

    <build>
        <sourceDirectory>src/main/scala</sourceDirectory>
        <testSourceDirectory>src/test/scala</testSourceDirectory>
        <plugins>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.2</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                        <configuration>
                            <args>
                                <arg>-make:transitive</arg>
                                <arg>-dependencyfile</arg>
                                <arg>${project.build.directory}/.scala_dependencies</arg>
                            </args>
                        </configuration>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>2.4.3</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <filters>
                                <filter>
                                    <artifact>*:*</artifact>
                                    <excludes>
                                        <exclude>META-INF/*.SF</exclude>
                                        <exclude>META-INF/*.DSA</exclude>
                                        <exclude>META-INF/*.RSA</exclude>
                                    </excludes>
                                </filter>
                            </filters>
                            <!-- 由于我们的程序可能有很多，所以这里可以不用指定main方法所在的类名，我们可以在提交spark程序的时候手动指定要调用那个main方法 -->
                            <!--
                            <transformers>
                                <transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                    <mainClass>com.xuebusi.spark.WordCount</mainClass>
                                </transformer>
                            </transformers>
                            -->

                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

虽然我们的pom文件中的jar包依赖准备好了，但是在Project的External Libraries缺少Maven依赖：

需要点击右侧的Maven Project侧边栏中的刷新按钮，才会导入Maven依赖，前提是保证电脑能够联网，Maven可能会到中央仓库下载一些依赖：

在左侧的Project侧边栏中的External Libraries下就可以看到新导入的Maven依赖了：

但是在pom.xml文件中还有错误提示，因为src/main/和src/test/这两个目录下面没有scala目录：

分别在main和test目录之上点击鼠标右键选择new->Directory创建scala目录：

由于新创建的scala文件夹前面的图标颜色和java文件夹不一样，我们需要再次点击右侧Maven Project侧边栏中的刷新按钮，其颜色就会发生变化：

在scala目录下面创建WordCount(类型为Object)：

3. 编写WordCount程序
下面是使用scala语言编写的Spark的一个简单的单词计数程序：

package com.xuebusi.spark

import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

/**
  * Created by SYJ on 2017/1/23.
  */
object WordCount {
  def main(args: Array[String]) {
    //创建SparkConf
    val conf: SparkConf = new SparkConf()
    //创建SparkContext
    val sc: SparkContext = new SparkContext(conf)
    //从文件读取数据
    val lines: RDD[String] = sc.textFile(args(0))
    //按空格切分单词
    val words: RDD[String] = lines.flatMap(_.split(" "))
    //单词计数,每个单词每出现一次就计数为1
    val wordAndOne: RDD[(String, Int)] = words.map((_, 1))
    //聚合,统计每个单词总共出现的次数
    val result: RDD[(String, Int)] = wordAndOne.reduceByKey(_+_)
    //排序,根据单词出现的次数排序
    val fianlResult: RDD[(String, Int)] = result.sortBy(_._2, false)
    //将统计结果保存到文件
    fianlResult.saveAsTextFile(args(1))
    //释放资源
    sc.stop()
  }
}

4. 打包
将编写好的WordCount程序使用Maven插件打成jar包，打包的时候也要保证电脑能够联网，因为Maven可能会到中央仓库中下载一些依赖：

在jar包名称上面点击鼠标右键选择“Copy Path”，得到jar包在Windows磁盘上的绝对路径：D:\bigdatacode\xbs-spark\target\spark-1.0-SNAPSHOT.jar，在下面上传jar包时会用到此路径。

5. 上传jar包
使用SecureCRT工具连接Spark集群服务器，将spark-1.0-SNAPSHOT.jar上传到服务器：

6. 同步时间

date -s "2017-01-23 19:19:30"

7. 启动Zookeeper

/root/apps/zookeeper/bin/zkServer.sh start

8. 启动hdfs

/root/apps/hadoop/sbin/start-dfs.sh

HDFS的活跃的NameNode节点：

HDFS的备选NameNode节点：

9. 启动Spark集群

/root/apps/spark/sbin/start-all.sh

启动单个Master进程使用如下命令：

/root/apps/spark/sbin/start-master.sh

Spark活跃的Master节点：

Spark的备选Master节点：

10. 准备输入数据

11. 提交Spark程序

提交Spark的WordCount程序需要两个参数，一个输入目录，一个输出目录，首先确定输出目录不存在，如果存在则删除：

hdfs dfs -rm -r /wordcount/output

使用spark-submit脚本提交spark程序：

/root/apps/spark/bin/spark-submit \
--master spark://hadoop01:7077,hadoop02:7077 \
--executor-memory 512m \
--total-executor-cores 7 \
--class com.xuebusi.spark.WordCount /root/spark-1.0-SNAPSHOT.jar hdfs://hadoop01:9000/wordcount/input hdfs://hadoop01:9000/wordcount/output

通过Spark的UI界面来观察程序执行过程：

12. 查看结果

附1：程序打包日志

1 D:\java\jdk1.7.0_72\bin\java -Dmaven.home=D:\apache-maven-3.2.1 -Dclassworlds.conf=D:\apache-maven-3.2.1\bin\m2.conf -Didea.launcher.port=7533 "-Didea.launcher.bin.path=D:\java\IntelliJ_IDEA\IntelliJ IDEA Community Edition 2016.1.1\bin" -Dfile.encoding=UTF-8 -classpath "D:\apache-maven-3.2.1\boot\plexus-classworlds-2.5.1.jar;D:\java\IntelliJ_IDEA\IntelliJ IDEA Community Edition 2016.1.1\lib\idea_rt.jar" com.intellij.rt.execution.application.AppMain org.codehaus.classworlds.Launcher -Didea.version=2016.1.1 package
  2 [INFO] Scanning for projects...
  3 [INFO] 
  4 [INFO] Using the builder org.apache.maven.lifecycle.internal.builder.singlethreaded.SingleThreadedBuilder with a thread count of 1
  5 [INFO]                                                                         
  6 [INFO] ------------------------------------------------------------------------
  7 [INFO] Building spark 1.0-SNAPSHOT
  8 [INFO] ------------------------------------------------------------------------
  9 [INFO] 
 10 [INFO] --- maven-resources-plugin:2.6:resources (default-resources) @ spark ---
 11 [INFO] Using 'UTF-8' encoding to copy filtered resources.
 12 [INFO] Copying 0 resource
 13 [INFO] 
 14 [INFO] --- maven-compiler-plugin:2.5.1:compile (default-compile) @ spark ---
 15 [INFO] Nothing to compile - all classes are up to date
 16 [INFO] 
 17 [INFO] --- scala-maven-plugin:3.2.2:compile (default) @ spark ---
 18 [WARNING]  Expected all dependencies to require Scala version: 2.10.6
 19 [WARNING]  com.xuebusi:spark:1.0-SNAPSHOT requires scala version: 2.10.6
 20 [WARNING]  com.twitter:chill_2.10:0.5.0 requires scala version: 2.10.4
 21 [WARNING] Multiple versions of scala libraries detected!
 22 [INFO] Nothing to compile - all classes are up to date
 23 [INFO] 
 24 [INFO] --- maven-resources-plugin:2.6:testResources (default-testResources) @ spark ---
 25 [INFO] Using 'UTF-8' encoding to copy filtered resources.
 26 [INFO] skip non existing resourceDirectory D:\bigdatacode\spark-wordcount\src\test\resources
 27 [INFO] 
 28 [INFO] --- maven-compiler-plugin:2.5.1:testCompile (default-testCompile) @ spark ---
 29 [INFO] Nothing to compile - all classes are up to date
 30 [INFO] 
 31 [INFO] --- scala-maven-plugin:3.2.2:testCompile (default) @ spark ---
 32 [WARNING]  Expected all dependencies to require Scala version: 2.10.6
 33 [WARNING]  com.xuebusi:spark:1.0-SNAPSHOT requires scala version: 2.10.6
 34 [WARNING]  com.twitter:chill_2.10:0.5.0 requires scala version: 2.10.4
 35 [WARNING] Multiple versions of scala libraries detected!
 36 [INFO] No sources to compile
 37 [INFO] 
 38 [INFO] --- maven-surefire-plugin:2.12.4:test (default-test) @ spark ---
 39 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-booter/2.12.4/surefire-booter-2.12.4.pom
 40 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-booter/2.12.4/surefire-booter-2.12.4.pom (3 KB at 1.7 KB/sec)
 41 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-api/2.12.4/surefire-api-2.12.4.pom
 42 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-api/2.12.4/surefire-api-2.12.4.pom (3 KB at 2.4 KB/sec)
 43 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/maven-surefire-common/2.12.4/maven-surefire-common-2.12.4.pom
 44 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/maven-surefire-common/2.12.4/maven-surefire-common-2.12.4.pom (6 KB at 3.2 KB/sec)
 45 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/plugin-tools/maven-plugin-annotations/3.1/maven-plugin-annotations-3.1.pom
 46 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/plugin-tools/maven-plugin-annotations/3.1/maven-plugin-annotations-3.1.pom (2 KB at 1.7 KB/sec)
 47 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/plugin-tools/maven-plugin-tools/3.1/maven-plugin-tools-3.1.pom
 48 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/plugin-tools/maven-plugin-tools/3.1/maven-plugin-tools-3.1.pom (16 KB at 12.0 KB/sec)
 49 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/maven-surefire-common/2.12.4/maven-surefire-common-2.12.4.jar
 50 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-api/2.12.4/surefire-api-2.12.4.jar
 51 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-booter/2.12.4/surefire-booter-2.12.4.jar
 52 Downloading: http://repo.maven.apache.org/maven2/org/apache/maven/plugin-tools/maven-plugin-annotations/3.1/maven-plugin-annotations-3.1.jar
 53 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/plugin-tools/maven-plugin-annotations/3.1/maven-plugin-annotations-3.1.jar (14 KB at 10.6 KB/sec)
 54 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-booter/2.12.4/surefire-booter-2.12.4.jar (34 KB at 21.5 KB/sec)
 55 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/maven-surefire-common/2.12.4/maven-surefire-common-2.12.4.jar (257 KB at 161.0 KB/sec)
 56 Downloaded: http://repo.maven.apache.org/maven2/org/apache/maven/surefire/surefire-api/2.12.4/surefire-api-2.12.4.jar (115 KB at 55.1 KB/sec)
 57 [INFO] No tests to run.
 58 [INFO] 
 59 [INFO] --- maven-jar-plugin:2.4:jar (default-jar) @ spark ---
 60 [INFO] Building jar: D:\bigdatacode\spark-wordcount\target\spark-1.0-SNAPSHOT.jar
 61 [INFO] 
 62 [INFO] --- maven-shade-plugin:2.4.3:shade (default) @ spark ---
 63 [INFO] Including org.scala-lang:scala-library:jar:2.10.6 in the shaded jar.
 64 [INFO] Including org.apache.spark:spark-core_2.10:jar:1.6.2 in the shaded jar.
 65 [INFO] Including org.apache.avro:avro-mapred:jar:hadoop2:1.7.7 in the shaded jar.
 66 [INFO] Including org.apache.avro:avro-ipc:jar:1.7.7 in the shaded jar.
 67 [INFO] Including org.apache.avro:avro-ipc:jar:tests:1.7.7 in the shaded jar.
 68 [INFO] Including org.codehaus.jackson:jackson-core-asl:jar:1.9.13 in the shaded jar.
 69 [INFO] Including org.codehaus.jackson:jackson-mapper-asl:jar:1.9.13 in the shaded jar.
 70 [INFO] Including com.twitter:chill_2.10:jar:0.5.0 in the shaded jar.
 71 [INFO] Including com.esotericsoftware.kryo:kryo:jar:2.21 in the shaded jar.
 72 [INFO] Including com.esotericsoftware.reflectasm:reflectasm:jar:shaded:1.07 in the shaded jar.
 73 [INFO] Including com.esotericsoftware.minlog:minlog:jar:1.2 in the shaded jar.
 74 [INFO] Including org.objenesis:objenesis:jar:1.2 in the shaded jar.
 75 [INFO] Including com.twitter:chill-java:jar:0.5.0 in the shaded jar.
 76 [INFO] Including org.apache.xbean:xbean-asm5-shaded:jar:4.4 in the shaded jar.
 77 [INFO] Including org.apache.spark:spark-launcher_2.10:jar:1.6.2 in the shaded jar.
 78 [INFO] Including org.apache.spark:spark-network-common_2.10:jar:1.6.2 in the shaded jar.
 79 [INFO] Including org.apache.spark:spark-network-shuffle_2.10:jar:1.6.2 in the shaded jar.
 80 [INFO] Including org.fusesource.leveldbjni:leveldbjni-all:jar:1.8 in the shaded jar.
 81 [INFO] Including com.fasterxml.jackson.core:jackson-annotations:jar:2.4.4 in the shaded jar.
 82 [INFO] Including org.apache.spark:spark-unsafe_2.10:jar:1.6.2 in the shaded jar.
 83 [INFO] Including net.java.dev.jets3t:jets3t:jar:0.7.1 in the shaded jar.
 84 [INFO] Including commons-codec:commons-codec:jar:1.3 in the shaded jar.
 85 [INFO] Including commons-httpclient:commons-httpclient:jar:3.1 in the shaded jar.
 86 [INFO] Including org.apache.curator:curator-recipes:jar:2.4.0 in the shaded jar.
 87 [INFO] Including org.apache.curator:curator-framework:jar:2.4.0 in the shaded jar.
 88 [INFO] Including org.apache.zookeeper:zookeeper:jar:3.4.5 in the shaded jar.
 89 [INFO] Including jline:jline:jar:0.9.94 in the shaded jar.
 90 [INFO] Including com.google.guava:guava:jar:14.0.1 in the shaded jar.
 91 [INFO] Including org.eclipse.jetty.orbit:javax.servlet:jar:3.0.0.v201112011016 in the shaded jar.
 92 [INFO] Including org.apache.commons:commons-lang3:jar:3.3.2 in the shaded jar.
 93 [INFO] Including org.apache.commons:commons-math3:jar:3.4.1 in the shaded jar.
 94 [INFO] Including com.google.code.findbugs:jsr305:jar:1.3.9 in the shaded jar.
 95 [INFO] Including org.slf4j:slf4j-api:jar:1.7.10 in the shaded jar.
 96 [INFO] Including org.slf4j:jul-to-slf4j:jar:1.7.10 in the shaded jar.
 97 [INFO] Including org.slf4j:jcl-over-slf4j:jar:1.7.10 in the shaded jar.
 98 [INFO] Including log4j:log4j:jar:1.2.17 in the shaded jar.
 99 [INFO] Including org.slf4j:slf4j-log4j12:jar:1.7.10 in the shaded jar.
100 [INFO] Including com.ning:compress-lzf:jar:1.0.3 in the shaded jar.
101 [INFO] Including org.xerial.snappy:snappy-java:jar:1.1.2.1 in the shaded jar.
102 [INFO] Including net.jpountz.lz4:lz4:jar:1.3.0 in the shaded jar.
103 [INFO] Including org.roaringbitmap:RoaringBitmap:jar:0.5.11 in the shaded jar.
104 [INFO] Including commons-net:commons-net:jar:2.2 in the shaded jar.
105 [INFO] Including com.typesafe.akka:akka-remote_2.10:jar:2.3.11 in the shaded jar.
106 [INFO] Including com.typesafe.akka:akka-actor_2.10:jar:2.3.11 in the shaded jar.
107 [INFO] Including com.typesafe:config:jar:1.2.1 in the shaded jar.
108 [INFO] Including io.netty:netty:jar:3.8.0.Final in the shaded jar.
109 [INFO] Including com.google.protobuf:protobuf-java:jar:2.5.0 in the shaded jar.
110 [INFO] Including org.uncommons.maths:uncommons-maths:jar:1.2.2a in the shaded jar.
111 [INFO] Including com.typesafe.akka:akka-slf4j_2.10:jar:2.3.11 in the shaded jar.
112 [INFO] Including org.json4s:json4s-jackson_2.10:jar:3.2.10 in the shaded jar.
113 [INFO] Including org.json4s:json4s-core_2.10:jar:3.2.10 in the shaded jar.
114 [INFO] Including org.json4s:json4s-ast_2.10:jar:3.2.10 in the shaded jar.
115 [INFO] Including org.scala-lang:scalap:jar:2.10.0 in the shaded jar.
116 [INFO] Including org.scala-lang:scala-compiler:jar:2.10.0 in the shaded jar.
117 [INFO] Including com.sun.jersey:jersey-server:jar:1.9 in the shaded jar.
118 [INFO] Including asm:asm:jar:3.1 in the shaded jar.
119 [INFO] Including com.sun.jersey:jersey-core:jar:1.9 in the shaded jar.
120 [INFO] Including org.apache.mesos:mesos:jar:shaded-protobuf:0.21.1 in the shaded jar.
121 [INFO] Including io.netty:netty-all:jar:4.0.29.Final in the shaded jar.
122 [INFO] Including com.clearspring.analytics:stream:jar:2.7.0 in the shaded jar.
123 [INFO] Including io.dropwizard.metrics:metrics-core:jar:3.1.2 in the shaded jar.
124 [INFO] Including io.dropwizard.metrics:metrics-jvm:jar:3.1.2 in the shaded jar.
125 [INFO] Including io.dropwizard.metrics:metrics-json:jar:3.1.2 in the shaded jar.
126 [INFO] Including io.dropwizard.metrics:metrics-graphite:jar:3.1.2 in the shaded jar.
127 [INFO] Including com.fasterxml.jackson.core:jackson-databind:jar:2.4.4 in the shaded jar.
128 [INFO] Including com.fasterxml.jackson.core:jackson-core:jar:2.4.4 in the shaded jar.
129 [INFO] Including com.fasterxml.jackson.module:jackson-module-scala_2.10:jar:2.4.4 in the shaded jar.
130 [INFO] Including org.scala-lang:scala-reflect:jar:2.10.4 in the shaded jar.
131 [INFO] Including com.thoughtworks.paranamer:paranamer:jar:2.6 in the shaded jar.
132 [INFO] Including org.apache.ivy:ivy:jar:2.4.0 in the shaded jar.
133 [INFO] Including oro:oro:jar:2.0.8 in the shaded jar.
134 [INFO] Including org.tachyonproject:tachyon-client:jar:0.8.2 in the shaded jar.
135 [INFO] Including commons-lang:commons-lang:jar:2.4 in the shaded jar.
136 [INFO] Including commons-io:commons-io:jar:2.4 in the shaded jar.
137 [INFO] Including org.tachyonproject:tachyon-underfs-hdfs:jar:0.8.2 in the shaded jar.
138 [INFO] Including org.tachyonproject:tachyon-underfs-s3:jar:0.8.2 in the shaded jar.
139 [INFO] Including org.tachyonproject:tachyon-underfs-local:jar:0.8.2 in the shaded jar.
140 [INFO] Including net.razorvine:pyrolite:jar:4.9 in the shaded jar.
141 [INFO] Including net.sf.py4j:py4j:jar:0.9 in the shaded jar.
142 [INFO] Including org.spark-project.spark:unused:jar:1.0.0 in the shaded jar.
143 [INFO] Including org.apache.hadoop:hadoop-client:jar:2.6.4 in the shaded jar.
144 [INFO] Including org.apache.hadoop:hadoop-common:jar:2.6.4 in the shaded jar.
145 [INFO] Including commons-cli:commons-cli:jar:1.2 in the shaded jar.
146 [INFO] Including xmlenc:xmlenc:jar:0.52 in the shaded jar.
147 [INFO] Including commons-collections:commons-collections:jar:3.2.2 in the shaded jar.
148 [INFO] Including commons-logging:commons-logging:jar:1.1.3 in the shaded jar.
149 [INFO] Including commons-configuration:commons-configuration:jar:1.6 in the shaded jar.
150 [INFO] Including commons-digester:commons-digester:jar:1.8 in the shaded jar.
151 [INFO] Including commons-beanutils:commons-beanutils:jar:1.7.0 in the shaded jar.
152 [INFO] Including commons-beanutils:commons-beanutils-core:jar:1.8.0 in the shaded jar.
153 [INFO] Including org.apache.avro:avro:jar:1.7.4 in the shaded jar.
154 [INFO] Including com.google.code.gson:gson:jar:2.2.4 in the shaded jar.
155 [INFO] Including org.apache.hadoop:hadoop-auth:jar:2.6.4 in the shaded jar.
156 [INFO] Including org.apache.httpcomponents:httpclient:jar:4.2.5 in the shaded jar.
157 [INFO] Including org.apache.httpcomponents:httpcore:jar:4.2.4 in the shaded jar.
158 [INFO] Including org.apache.directory.server:apacheds-kerberos-codec:jar:2.0.0-M15 in the shaded jar.
159 [INFO] Including org.apache.directory.server:apacheds-i18n:jar:2.0.0-M15 in the shaded jar.
160 [INFO] Including org.apache.directory.api:api-asn1-api:jar:1.0.0-M20 in the shaded jar.
161 [INFO] Including org.apache.directory.api:api-util:jar:1.0.0-M20 in the shaded jar.
162 [INFO] Including org.apache.curator:curator-client:jar:2.6.0 in the shaded jar.
163 [INFO] Including org.htrace:htrace-core:jar:3.0.4 in the shaded jar.
164 [INFO] Including org.apache.commons:commons-compress:jar:1.4.1 in the shaded jar.
165 [INFO] Including org.tukaani:xz:jar:1.0 in the shaded jar.
166 [INFO] Including org.apache.hadoop:hadoop-hdfs:jar:2.6.4 in the shaded jar.
167 [INFO] Including org.mortbay.jetty:jetty-util:jar:6.1.26 in the shaded jar.
168 [INFO] Including xerces:xercesImpl:jar:2.9.1 in the shaded jar.
169 [INFO] Including xml-apis:xml-apis:jar:1.3.04 in the shaded jar.
170 [INFO] Including org.apache.hadoop:hadoop-mapreduce-client-app:jar:2.6.4 in the shaded jar.
171 [INFO] Including org.apache.hadoop:hadoop-mapreduce-client-common:jar:2.6.4 in the shaded jar.
172 [INFO] Including org.apache.hadoop:hadoop-yarn-client:jar:2.6.4 in the shaded jar.
173 [INFO] Including org.apache.hadoop:hadoop-yarn-server-common:jar:2.6.4 in the shaded jar.
174 [INFO] Including org.apache.hadoop:hadoop-mapreduce-client-shuffle:jar:2.6.4 in the shaded jar.
175 [INFO] Including org.apache.hadoop:hadoop-yarn-api:jar:2.6.4 in the shaded jar.
176 [INFO] Including org.apache.hadoop:hadoop-mapreduce-client-core:jar:2.6.4 in the shaded jar.
177 [INFO] Including org.apache.hadoop:hadoop-yarn-common:jar:2.6.4 in the shaded jar.
178 [INFO] Including javax.xml.bind:jaxb-api:jar:2.2.2 in the shaded jar.
179 [INFO] Including javax.xml.stream:stax-api:jar:1.0-2 in the shaded jar.
180 [INFO] Including javax.activation:activation:jar:1.1 in the shaded jar.
181 [INFO] Including javax.servlet:servlet-api:jar:2.5 in the shaded jar.
182 [INFO] Including com.sun.jersey:jersey-client:jar:1.9 in the shaded jar.
183 [INFO] Including org.codehaus.jackson:jackson-jaxrs:jar:1.9.13 in the shaded jar.
184 [INFO] Including org.codehaus.jackson:jackson-xc:jar:1.9.13 in the shaded jar.
185 [INFO] Including org.apache.hadoop:hadoop-mapreduce-client-jobclient:jar:2.6.4 in the shaded jar.
186 [INFO] Including org.apache.hadoop:hadoop-annotations:jar:2.6.4 in the shaded jar.
187 [WARNING] commons-logging-1.1.3.jar, jcl-over-slf4j-1.7.10.jar define 6 overlapping classes: 
188 [WARNING]   - org.apache.commons.logging.impl.NoOpLog
189 [WARNING]   - org.apache.commons.logging.impl.SimpleLog
190 [WARNING]   - org.apache.commons.logging.LogFactory
191 [WARNING]   - org.apache.commons.logging.LogConfigurationException
192 [WARNING]   - org.apache.commons.logging.impl.SimpleLog$1
193 [WARNING]   - org.apache.commons.logging.Log
194 [WARNING] commons-beanutils-core-1.8.0.jar, commons-beanutils-1.7.0.jar define 82 overlapping classes: 
195 [WARNING]   - org.apache.commons.beanutils.WrapDynaBean
196 [WARNING]   - org.apache.commons.beanutils.Converter
197 [WARNING]   - org.apache.commons.beanutils.converters.IntegerConverter
198 [WARNING]   - org.apache.commons.beanutils.locale.LocaleBeanUtilsBean
199 [WARNING]   - org.apache.commons.beanutils.locale.converters.DecimalLocaleConverter
200 [WARNING]   - org.apache.commons.beanutils.locale.converters.DoubleLocaleConverter
201 [WARNING]   - org.apache.commons.beanutils.converters.ShortConverter
202 [WARNING]   - org.apache.commons.beanutils.converters.StringArrayConverter
203 [WARNING]   - org.apache.commons.beanutils.locale.LocaleConvertUtilsBean
204 [WARNING]   - org.apache.commons.beanutils.LazyDynaClass
205 [WARNING]   - 72 more...
206 [WARNING] hadoop-yarn-common-2.6.4.jar, hadoop-yarn-api-2.6.4.jar define 3 overlapping classes: 
207 [WARNING]   - org.apache.hadoop.yarn.factories.package-info
208 [WARNING]   - org.apache.hadoop.yarn.util.package-info
209 [WARNING]   - org.apache.hadoop.yarn.factory.providers.package-info
210 [WARNING] commons-beanutils-core-1.8.0.jar, commons-collections-3.2.2.jar, commons-beanutils-1.7.0.jar define 10 overlapping classes: 
211 [WARNING]   - org.apache.commons.collections.FastHashMap$EntrySet
212 [WARNING]   - org.apache.commons.collections.ArrayStack
213 [WARNING]   - org.apache.commons.collections.FastHashMap$1
214 [WARNING]   - org.apache.commons.collections.FastHashMap$KeySet
215 [WARNING]   - org.apache.commons.collections.FastHashMap$CollectionView
216 [WARNING]   - org.apache.commons.collections.BufferUnderflowException
217 [WARNING]   - org.apache.commons.collections.Buffer
218 [WARNING]   - org.apache.commons.collections.FastHashMap$CollectionView$CollectionViewIterator
219 [WARNING]   - org.apache.commons.collections.FastHashMap$Values
220 [WARNING]   - org.apache.commons.collections.FastHashMap
221 [WARNING] kryo-2.21.jar, objenesis-1.2.jar define 32 overlapping classes: 
222 [WARNING]   - org.objenesis.Objenesis
223 [WARNING]   - org.objenesis.strategy.StdInstantiatorStrategy
224 [WARNING]   - org.objenesis.instantiator.basic.ObjectStreamClassInstantiator
225 [WARNING]   - org.objenesis.instantiator.sun.SunReflectionFactorySerializationInstantiator
226 [WARNING]   - org.objenesis.instantiator.perc.PercSerializationInstantiator
227 [WARNING]   - org.objenesis.instantiator.NullInstantiator
228 [WARNING]   - org.objenesis.instantiator.jrockit.JRockitLegacyInstantiator
229 [WARNING]   - org.objenesis.instantiator.gcj.GCJInstantiatorBase
230 [WARNING]   - org.objenesis.ObjenesisException
231 [WARNING]   - org.objenesis.instantiator.basic.ObjectInputStreamInstantiator$MockStream
232 [WARNING]   - 22 more...
233 [WARNING] kryo-2.21.jar, reflectasm-1.07-shaded.jar define 23 overlapping classes: 
234 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Opcodes
235 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Frame
236 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Label
237 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.FieldWriter
238 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.AnnotationVisitor
239 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.FieldVisitor
240 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Item
241 [WARNING]   - com.esotericsoftware.reflectasm.AccessClassLoader
242 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Edge
243 [WARNING]   - com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.ClassVisitor
244 [WARNING]   - 13 more...
245 [WARNING] minlog-1.2.jar, kryo-2.21.jar define 2 overlapping classes: 
246 [WARNING]   - com.esotericsoftware.minlog.Log$Logger
247 [WARNING]   - com.esotericsoftware.minlog.Log
248 [WARNING] servlet-api-2.5.jar, javax.servlet-3.0.0.v201112011016.jar define 42 overlapping classes: 
249 [WARNING]   - javax.servlet.ServletRequestWrapper
250 [WARNING]   - javax.servlet.FilterChain
251 [WARNING]   - javax.servlet.SingleThreadModel
252 [WARNING]   - javax.servlet.http.HttpServletResponse
253 [WARNING]   - javax.servlet.http.HttpUtils
254 [WARNING]   - javax.servlet.ServletContextAttributeEvent
255 [WARNING]   - javax.servlet.ServletContextAttributeListener
256 [WARNING]   - javax.servlet.http.HttpServlet
257 [WARNING]   - javax.servlet.http.HttpSessionAttributeListener
258 [WARNING]   - javax.servlet.http.HttpServletRequest
259 [WARNING]   - 32 more...
260 [WARNING] guava-14.0.1.jar, spark-network-common_2.10-1.6.2.jar define 7 overlapping classes: 
261 [WARNING]   - com.google.common.base.Optional$1$1
262 [WARNING]   - com.google.common.base.Supplier
263 [WARNING]   - com.google.common.base.Function
264 [WARNING]   - com.google.common.base.Optional
265 [WARNING]   - com.google.common.base.Optional$1
266 [WARNING]   - com.google.common.base.Absent
267 [WARNING]   - com.google.common.base.Present
268 [WARNING] hadoop-yarn-common-2.6.4.jar, hadoop-yarn-client-2.6.4.jar define 2 overlapping classes: 
269 [WARNING]   - org.apache.hadoop.yarn.client.api.impl.package-info
270 [WARNING]   - org.apache.hadoop.yarn.client.api.package-info
271 [WARNING] unused-1.0.0.jar, spark-core_2.10-1.6.2.jar, spark-network-shuffle_2.10-1.6.2.jar, spark-launcher_2.10-1.6.2.jar, spark-unsafe_2.10-1.6.2.jar, spark-network-common_2.10-1.6.2.jar define 1 overlapping classes: 
272 [WARNING]   - org.apache.spark.unused.UnusedStubClass
273 [WARNING] maven-shade-plugin has detected that some class files are
274 [WARNING] present in two or more JARs. When this happens, only one
275 [WARNING] single version of the class is copied to the uber jar.
276 [WARNING] Usually this is not harmful and you can skip these warnings,
277 [WARNING] otherwise try to manually exclude artifacts based on
278 [WARNING] mvn dependency:tree -Ddetail=true and the above output.
279 [WARNING] See http://maven.apache.org/plugins/maven-shade-plugin/
280 [INFO] Replacing original artifact with shaded artifact.
281 [INFO] Replacing D:\bigdatacode\spark-wordcount\target\spark-1.0-SNAPSHOT.jar with D:\bigdatacode\spark-wordcount\target\spark-1.0-SNAPSHOT-shaded.jar
282 [INFO] Dependency-reduced POM written at: D:\bigdatacode\spark-wordcount\dependency-reduced-pom.xml
283 [INFO] ------------------------------------------------------------------------
284 [INFO] BUILD SUCCESS
285 [INFO] ------------------------------------------------------------------------
286 [INFO] Total time: 01:02 min
287 [INFO] Finished at: 2017-01-23T12:44:03+08:00
288 [INFO] Final Memory: 18M/115M
289 [INFO] ------------------------------------------------------------------------
290 
291 Process finished with exit code 0

View Code

附2：程序执行过程日志

1 Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
  2 17/01/23 19:35:52 INFO SparkContext: Running Spark version 1.6.2
  3 17/01/23 19:35:55 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
  4 17/01/23 19:35:57 INFO SecurityManager: Changing view acls to: root
  5 17/01/23 19:35:57 INFO SecurityManager: Changing modify acls to: root
  6 17/01/23 19:35:57 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
  7 17/01/23 19:36:00 INFO Utils: Successfully started service 'sparkDriver' on port 38885.
  8 17/01/23 19:36:04 INFO Slf4jLogger: Slf4jLogger started
  9 17/01/23 19:36:04 INFO Remoting: Starting remoting
 10 17/01/23 19:36:06 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.71.11:50102]
 11 17/01/23 19:36:06 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 50102.
 12 17/01/23 19:36:07 INFO SparkEnv: Registering MapOutputTracker
 13 17/01/23 19:36:07 INFO SparkEnv: Registering BlockManagerMaster
 14 17/01/23 19:36:08 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-677f9442-f73a-4925-b629-297dc3409fa8
 15 17/01/23 19:36:08 INFO MemoryStore: MemoryStore started with capacity 517.4 MB
 16 17/01/23 19:36:08 INFO SparkEnv: Registering OutputCommitCoordinator
 17 17/01/23 19:36:15 INFO Utils: Successfully started service 'SparkUI' on port 4040.
 18 17/01/23 19:36:15 INFO SparkUI: Started SparkUI at http://192.168.71.11:4040
 19 17/01/23 19:36:15 INFO HttpFileServer: HTTP File server directory is /tmp/spark-1be891d5-88d1-4e02-970b-023ff1e8c618/httpd-b73f26ff-5d13-4abd-953b-164a3f2d18e7
 20 17/01/23 19:36:15 INFO HttpServer: Starting HTTP Server
 21 17/01/23 19:36:15 INFO Utils: Successfully started service 'HTTP file server' on port 38719.
 22 17/01/23 19:36:22 INFO SparkContext: Added JAR file:/root/spark-1.0-SNAPSHOT.jar at http://192.168.71.11:38719/jars/spark-1.0-SNAPSHOT.jar with timestamp 1485228982685
 23 17/01/23 19:36:23 INFO AppClient$ClientEndpoint: Connecting to master spark://hadoop01:7077...
 24 17/01/23 19:36:23 INFO AppClient$ClientEndpoint: Connecting to master spark://hadoop02:7077...
 25 17/01/23 19:36:26 INFO SparkDeploySchedulerBackend: Connected to Spark cluster with app ID app-20170123193626-0000
 26 17/01/23 19:36:26 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 59402.
 27 17/01/23 19:36:26 INFO NettyBlockTransferService: Server created on 59402
 28 17/01/23 19:36:26 INFO BlockManagerMaster: Trying to register BlockManager
 29 17/01/23 19:36:26 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.71.11:59402 with 517.4 MB RAM, BlockManagerId(driver, 192.168.71.11, 59402)
 30 17/01/23 19:36:27 INFO BlockManagerMaster: Registered BlockManager
 31 17/01/23 19:36:27 INFO AppClient$ClientEndpoint: Executor added: app-20170123193626-0000/0 on worker-20170123192703-192.168.71.12-41229 (192.168.71.12:41229) with 1 cores
 32 17/01/23 19:36:27 INFO SparkDeploySchedulerBackend: Granted executor ID app-20170123193626-0000/0 on hostPort 192.168.71.12:41229 with 1 cores, 512.0 MB RAM
 33 17/01/23 19:36:27 INFO AppClient$ClientEndpoint: Executor added: app-20170123193626-0000/1 on worker-20170123192703-192.168.71.13-49628 (192.168.71.13:49628) with 1 cores
 34 17/01/23 19:36:27 INFO SparkDeploySchedulerBackend: Granted executor ID app-20170123193626-0000/1 on hostPort 192.168.71.13:49628 with 1 cores, 512.0 MB RAM
 35 17/01/23 19:36:28 INFO AppClient$ClientEndpoint: Executor updated: app-20170123193626-0000/1 is now RUNNING
 36 17/01/23 19:36:28 INFO AppClient$ClientEndpoint: Executor updated: app-20170123193626-0000/0 is now RUNNING
 37 17/01/23 19:36:30 INFO SparkDeploySchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0
 38 17/01/23 19:36:33 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 153.6 KB, free 153.6 KB)
 39 17/01/23 19:36:33 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 13.9 KB, free 167.5 KB)
 40 17/01/23 19:36:33 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.71.11:59402 (size: 13.9 KB, free: 517.4 MB)
 41 17/01/23 19:36:33 INFO SparkContext: Created broadcast 0 from textFile at WordCount.scala:16
 42 17/01/23 19:36:45 INFO FileInputFormat: Total input paths to process : 1
 43 17/01/23 19:36:45 INFO SparkContext: Starting job: sortBy at WordCount.scala:24
 44 17/01/23 19:36:46 INFO DAGScheduler: Registering RDD 3 (map at WordCount.scala:20)
 45 17/01/23 19:36:46 INFO DAGScheduler: Got job 0 (sortBy at WordCount.scala:24) with 2 output partitions
 46 17/01/23 19:36:46 INFO DAGScheduler: Final stage: ResultStage 1 (sortBy at WordCount.scala:24)
 47 17/01/23 19:36:46 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
 48 17/01/23 19:36:46 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
 49 17/01/23 19:36:46 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:20), which has no missing parents
 50 17/01/23 19:36:46 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 4.1 KB, free 171.6 KB)
 51 17/01/23 19:36:46 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.3 KB, free 173.9 KB)
 52 17/01/23 19:36:46 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 192.168.71.11:59402 (size: 2.3 KB, free: 517.4 MB)
 53 17/01/23 19:36:46 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006
 54 17/01/23 19:36:46 INFO DAGScheduler: Submitting 2 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:20)
 55 17/01/23 19:36:46 INFO TaskSchedulerImpl: Adding task set 0.0 with 2 tasks
 56 17/01/23 19:36:53 INFO SparkDeploySchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hadoop02:59859) with ID 0
 57 17/01/23 19:36:53 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, hadoop02, partition 0,NODE_LOCAL, 2201 bytes)
 58 17/01/23 19:36:54 INFO BlockManagerMasterEndpoint: Registering block manager hadoop02:37066 with 146.2 MB RAM, BlockManagerId(0, hadoop02, 37066)
 59 17/01/23 19:37:09 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on hadoop02:37066 (size: 2.3 KB, free: 146.2 MB)
 60 17/01/23 19:37:10 INFO SparkDeploySchedulerBackend: Registered executor NettyRpcEndpointRef(null) (hadoop03:43916) with ID 1
 61 17/01/23 19:37:10 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, hadoop03, partition 1,NODE_LOCAL, 2201 bytes)
 62 17/01/23 19:37:10 INFO BlockManagerMasterEndpoint: Registering block manager hadoop03:52009 with 146.2 MB RAM, BlockManagerId(1, hadoop03, 52009)
 63 17/01/23 19:37:11 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hadoop02:37066 (size: 13.9 KB, free: 146.2 MB)
 64 17/01/23 19:37:19 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 25906 ms on hadoop02 (1/2)
 65 17/01/23 19:37:43 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on hadoop03:52009 (size: 2.3 KB, free: 146.2 MB)
 66 17/01/23 19:37:46 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hadoop03:52009 (size: 13.9 KB, free: 146.2 MB)
 67 17/01/23 19:37:55 INFO TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 45040 ms on hadoop03 (2/2)
 68 17/01/23 19:37:55 INFO DAGScheduler: ShuffleMapStage 0 (map at WordCount.scala:20) finished in 68.357 s
 69 17/01/23 19:37:55 INFO DAGScheduler: looking for newly runnable stages
 70 17/01/23 19:37:55 INFO DAGScheduler: running: Set()
 71 17/01/23 19:37:55 INFO DAGScheduler: waiting: Set(ResultStage 1)
 72 17/01/23 19:37:55 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
 73 17/01/23 19:37:55 INFO DAGScheduler: failed: Set()
 74 17/01/23 19:37:55 INFO DAGScheduler: Submitting ResultStage 1 (MapPartitionsRDD[7] at sortBy at WordCount.scala:24), which has no missing parents
 75 17/01/23 19:37:55 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 3.6 KB, free 177.5 KB)
 76 17/01/23 19:37:55 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 2.0 KB, free 179.5 KB)
 77 17/01/23 19:37:55 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 192.168.71.11:59402 (size: 2.0 KB, free: 517.4 MB)
 78 17/01/23 19:37:55 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1006
 79 17/01/23 19:37:55 INFO DAGScheduler: Submitting 2 missing tasks from ResultStage 1 (MapPartitionsRDD[7] at sortBy at WordCount.scala:24)
 80 17/01/23 19:37:55 INFO TaskSchedulerImpl: Adding task set 1.0 with 2 tasks
 81 17/01/23 19:37:55 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 2, hadoop03, partition 0,NODE_LOCAL, 1958 bytes)
 82 17/01/23 19:37:55 INFO TaskSetManager: Starting task 1.0 in stage 1.0 (TID 3, hadoop02, partition 1,NODE_LOCAL, 1958 bytes)
 83 17/01/23 19:37:55 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on hadoop03:52009 (size: 2.0 KB, free: 146.2 MB)
 84 17/01/23 19:37:56 INFO MapOutputTrackerMasterEndpoint: Asked to send map output locations for shuffle 0 to hadoop03:43916
 85 17/01/23 19:37:56 INFO MapOutputTrackerMaster: Size of output statuses for shuffle 0 is 157 bytes
 86 17/01/23 19:37:56 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on hadoop02:37066 (size: 2.0 KB, free: 146.2 MB)
 87 17/01/23 19:37:56 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 2) in 1152 ms on hadoop03 (1/2)
 88 17/01/23 19:37:57 INFO MapOutputTrackerMasterEndpoint: Asked to send map output locations for shuffle 0 to hadoop02:59859
 89 17/01/23 19:37:57 INFO DAGScheduler: ResultStage 1 (sortBy at WordCount.scala:24) finished in 1.615 s
 90 17/01/23 19:37:57 INFO TaskSetManager: Finished task 1.0 in stage 1.0 (TID 3) in 1605 ms on hadoop02 (2/2)
 91 17/01/23 19:37:57 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool 
 92 17/01/23 19:37:57 INFO DAGScheduler: Job 0 finished: sortBy at WordCount.scala:24, took 71.451062 s
 93 17/01/23 19:37:57 INFO deprecation: mapred.tip.id is deprecated. Instead, use mapreduce.task.id
 94 17/01/23 19:37:57 INFO deprecation: mapred.task.id is deprecated. Instead, use mapreduce.task.attempt.id
 95 17/01/23 19:37:57 INFO deprecation: mapred.task.is.map is deprecated. Instead, use mapreduce.task.ismap
 96 17/01/23 19:37:57 INFO deprecation: mapred.task.partition is deprecated. Instead, use mapreduce.task.partition
 97 17/01/23 19:37:57 INFO deprecation: mapred.job.id is deprecated. Instead, use mapreduce.job.id
 98 17/01/23 19:37:58 INFO SparkContext: Starting job: saveAsTextFile at WordCount.scala:26
 99 17/01/23 19:37:58 INFO DAGScheduler: Registering RDD 5 (sortBy at WordCount.scala:24)
100 17/01/23 19:37:58 INFO DAGScheduler: Got job 1 (saveAsTextFile at WordCount.scala:26) with 2 output partitions
101 17/01/23 19:37:58 INFO DAGScheduler: Final stage: ResultStage 4 (saveAsTextFile at WordCount.scala:26)
102 17/01/23 19:37:58 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 3)
103 17/01/23 19:37:58 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 3)
104 17/01/23 19:37:58 INFO DAGScheduler: Submitting ShuffleMapStage 3 (MapPartitionsRDD[5] at sortBy at WordCount.scala:24), which has no missing parents
105 17/01/23 19:37:58 INFO MemoryStore: Block broadcast_3 stored as values in memory (estimated size 3.5 KB, free 183.1 KB)
106 17/01/23 19:37:59 INFO MemoryStore: Block broadcast_3_piece0 stored as bytes in memory (estimated size 2.0 KB, free 185.1 KB)
107 17/01/23 19:37:59 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on 192.168.71.11:59402 (size: 2.0 KB, free: 517.4 MB)
108 17/01/23 19:37:59 INFO SparkContext: Created broadcast 3 from broadcast at DAGScheduler.scala:1006
109 17/01/23 19:37:59 INFO DAGScheduler: Submitting 2 missing tasks from ShuffleMapStage 3 (MapPartitionsRDD[5] at sortBy at WordCount.scala:24)
110 17/01/23 19:37:59 INFO TaskSchedulerImpl: Adding task set 3.0 with 2 tasks
111 17/01/23 19:37:59 INFO TaskSetManager: Starting task 0.0 in stage 3.0 (TID 4, hadoop02, partition 0,NODE_LOCAL, 1947 bytes)
112 17/01/23 19:37:59 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on hadoop02:37066 (size: 2.0 KB, free: 146.2 MB)
113 17/01/23 19:37:59 INFO TaskSetManager: Starting task 1.0 in stage 3.0 (TID 5, hadoop02, partition 1,NODE_LOCAL, 1947 bytes)
114 17/01/23 19:37:59 INFO TaskSetManager: Finished task 0.0 in stage 3.0 (TID 4) in 531 ms on hadoop02 (1/2)
115 17/01/23 19:37:59 INFO DAGScheduler: ShuffleMapStage 3 (sortBy at WordCount.scala:24) finished in 0.643 s
116 17/01/23 19:37:59 INFO DAGScheduler: looking for newly runnable stages
117 17/01/23 19:37:59 INFO DAGScheduler: running: Set()
118 17/01/23 19:37:59 INFO DAGScheduler: waiting: Set(ResultStage 4)
119 17/01/23 19:37:59 INFO DAGScheduler: failed: Set()
120 17/01/23 19:37:59 INFO DAGScheduler: Submitting ResultStage 4 (MapPartitionsRDD[10] at saveAsTextFile at WordCount.scala:26), which has no missing parents
121 17/01/23 19:37:59 INFO TaskSetManager: Finished task 1.0 in stage 3.0 (TID 5) in 132 ms on hadoop02 (2/2)
122 17/01/23 19:37:59 INFO TaskSchedulerImpl: Removed TaskSet 3.0, whose tasks have all completed, from pool 
123 17/01/23 19:38:00 INFO MemoryStore: Block broadcast_4 stored as values in memory (estimated size 64.9 KB, free 250.0 KB)
124 17/01/23 19:38:00 INFO MemoryStore: Block broadcast_4_piece0 stored as bytes in memory (estimated size 22.5 KB, free 272.5 KB)
125 17/01/23 19:38:00 INFO BlockManagerInfo: Added broadcast_4_piece0 in memory on 192.168.71.11:59402 (size: 22.5 KB, free: 517.4 MB)
126 17/01/23 19:38:00 INFO SparkContext: Created broadcast 4 from broadcast at DAGScheduler.scala:1006
127 17/01/23 19:38:00 INFO DAGScheduler: Submitting 2 missing tasks from ResultStage 4 (MapPartitionsRDD[10] at saveAsTextFile at WordCount.scala:26)
128 17/01/23 19:38:00 INFO TaskSchedulerImpl: Adding task set 4.0 with 2 tasks
129 17/01/23 19:38:00 INFO TaskSetManager: Starting task 0.0 in stage 4.0 (TID 6, hadoop02, partition 0,NODE_LOCAL, 1958 bytes)
130 17/01/23 19:38:00 INFO BlockManagerInfo: Added broadcast_4_piece0 in memory on hadoop02:37066 (size: 22.5 KB, free: 146.2 MB)
131 17/01/23 19:38:00 INFO MapOutputTrackerMasterEndpoint: Asked to send map output locations for shuffle 1 to hadoop02:59859
132 17/01/23 19:38:00 INFO MapOutputTrackerMaster: Size of output statuses for shuffle 1 is 149 bytes
133 17/01/23 19:38:04 INFO TaskSetManager: Starting task 1.0 in stage 4.0 (TID 7, hadoop03, partition 1,ANY, 1958 bytes)
134 17/01/23 19:38:04 INFO BlockManagerInfo: Added broadcast_4_piece0 in memory on hadoop03:52009 (size: 22.5 KB, free: 146.2 MB)
135 17/01/23 19:38:04 INFO TaskSetManager: Finished task 0.0 in stage 4.0 (TID 6) in 4444 ms on hadoop02 (1/2)
136 17/01/23 19:38:04 INFO MapOutputTrackerMasterEndpoint: Asked to send map output locations for shuffle 1 to hadoop03:43916
137 17/01/23 19:38:06 INFO DAGScheduler: ResultStage 4 (saveAsTextFile at WordCount.scala:26) finished in 5.782 s
138 17/01/23 19:38:06 INFO TaskSetManager: Finished task 1.0 in stage 4.0 (TID 7) in 1827 ms on hadoop03 (2/2)
139 17/01/23 19:38:06 INFO TaskSchedulerImpl: Removed TaskSet 4.0, whose tasks have all completed, from pool 
140 17/01/23 19:38:06 INFO DAGScheduler: Job 1 finished: saveAsTextFile at WordCount.scala:26, took 7.582931 s
141 17/01/23 19:38:06 INFO SparkUI: Stopped Spark web UI at http://192.168.71.11:4040
142 17/01/23 19:38:06 INFO SparkDeploySchedulerBackend: Shutting down all executors
143 17/01/23 19:38:06 INFO SparkDeploySchedulerBackend: Asking each executor to shut down
144 17/01/23 19:38:06 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
145 17/01/23 19:38:08 INFO MemoryStore: MemoryStore cleared
146 17/01/23 19:38:08 INFO BlockManager: BlockManager stopped
147 17/01/23 19:38:08 INFO BlockManagerMaster: BlockManagerMaster stopped
148 17/01/23 19:38:08 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
149 17/01/23 19:38:08 INFO SparkContext: Successfully stopped SparkContext
150 17/01/23 19:38:08 INFO ShutdownHookManager: Shutdown hook called
151 17/01/23 19:38:08 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
152 17/01/23 19:38:08 INFO ShutdownHookManager: Deleting directory /tmp/spark-1be891d5-88d1-4e02-970b-023ff1e8c618/httpd-b73f26ff-5d13-4abd-953b-164a3f2d18e7
153 17/01/23 19:38:08 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
154 17/01/23 19:38:08 INFO ShutdownHookManager: Deleting directory /tmp/spark-1be891d5-88d1-4e02-970b-023ff1e8c618
155 17/01/23 19:38:08

View Code

13. 使用Java语言编写Spark的WordCount程序
上面我们使用Scala语言编写了一个Spark的WordCount程序，并成功提交了到Spark集群上进行了运行。现在我们在同一个工程中使用Java语言也编写一个Spark的WordCount单词计数程序。

1) 修改pom文件内容
原来的pom文件中只有一个编译scala程序的Maven插件，现在我们要编译java程序，就需要引入java的Maven编译插件。

完整的pom.xml文件内容如下(替换原来的pom文件内容，对原来scala版的WordCount程序不会有影响)：

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.xuebusi</groupId>
    <artifactId>spark</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>1.7</maven.compiler.source>
        <maven.compiler.target>1.7</maven.compiler.target>
        <encoding>UTF-8</encoding>
        <scala.version>2.10.6</scala.version>
        <spark.version>1.6.2</spark.version>
        <hadoop.version>2.6.4</hadoop.version>
    </properties>

    <dependencies>
        <!--  如果我们仅使用java来编写spark程序,可以不导此包 -->
        <!--  scala的语言核心包 -->
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>
        <!--  Hadoop的客户端 -->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>${hadoop.version}</version>
        </dependency>
        <!--  spark的核心包 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.10</artifactId>
            <version>${spark.version}</version>
        </dependency>
    </dependencies>

    <build>
        <pluginManagement>
            <plugins>
                <!--  scala-maven-plugin：编译scala程序的Maven插件 -->
                <plugin>
                    <groupId>net.alchim31.maven</groupId>
                    <artifactId>scala-maven-plugin</artifactId>
                    <version>3.2.2</version>
                </plugin>
                <!--  maven-compiler-plugin：编译java程序的Maven插件 -->
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    <artifactId>maven-compiler-plugin</artifactId>
                    <version>3.5.1</version>
                </plugin>
            </plugins>
        </pluginManagement>
        <plugins>
            <!--  编译scala程序的Maven插件的一些配置参数 -->
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <executions>
                    <execution>
                        <id>scala-compile-first</id>
                        <phase>process-resources</phase>
                        <goals>
                            <goal>add-source</goal>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                    <execution>
                        <id>scala-test-compile</id>
                        <phase>process-test-resources</phase>
                        <goals>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <!--  编译java程序的Maven插件的一些配置参数 -->
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <executions>
                    <execution>
                        <phase>compile</phase>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <!--  maven-shade-plugin：打jar包用的Mavne插件 -->
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>2.4.3</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <filters>
                                <filter>
                                    <artifact>*:*</artifact>
                                    <excludes>
                                        <exclude>META-INF/*.SF</exclude>
                                        <exclude>META-INF/*.DSA</exclude>
                                        <exclude>META-INF/*.RSA</exclude>
                                    </excludes>
                                </filter>
                            </filters>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

2) 刷新依赖
pom文件准备好以后，需要点击右侧的Maven Project中的刷新按钮，才会真正导入Maven依赖。如果本地的Maven仓库中缺少相关的依赖，Maven会自动到中央仓库中下载依赖的jar包，所以要求电脑必须能够联网。

3) 创建JavaWordCount类
在src/main/java目录下面创建JavaWordCount类：

完整的JavaWordCount类代码如下：

package com.xuebusi.spark;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.PairFunction;
import scala.Tuple2;

import java.util.Arrays;

/**
 * 这里我们仅使用Java的API编写一个简单的Spark应用程序,
 * 对数据做简单的处理,业务比较简单,
 * 在实际项目中可能要结合较为复杂的业务逻辑,
 * 比如操作数据库,操作HDFS/Kafka/Hbase等,
 * 或者和其他的第三方的组件进行整合等等;
 * 如果你对Scala语言不熟悉,你可以使用Java,
 * 没有倾向说哪一种语言更好,
 * 但是只要java能够完成的功能，scala也可以;
 *
 * Created by SYJ on 2017/1/23.
 */
public class JavaWordCount {
    /**
     * main方法的快捷键：psvm
     * 自动补全变量名的快捷键：Ctrl+Alt+V
     *
     * 由于JDK1.7版本还不支持函数式编程,
     * 所以你会看到给很多方法传递参数时,
     * 大量使用到了匿名类;
     *
     * 其实使用Java来编写Spark程序并不难,
     * 很多代码都不用我们自己写,
     * 因为IDEA开发工具提供了很好的代码提示和代码自动
     * 补全功能--根据提示使用Tab键可以快速补全代码;
     * @param args
     */
    public static void main(String[] args) {
        //创建SparkConf,并指定应用程序名称
        SparkConf conf = new SparkConf().setAppName("JavaWordCount");

        //创建JavaSparkContext
        JavaSparkContext sc = new JavaSparkContext(conf);

        //从文件系统读取数据
        //注意在Java的数组取下标使用中括号args[0],而scala使用小括号args(0)
        //其实JavaRDD继承了Spark的RDD,对其做了扩展
        JavaRDD<String> lines = sc.textFile(args[0]);

        /**
         * 切分单词
         *
         * FlatMapFunction是匿名类,
         * 它的两个参数中,第一个参数是输入的数据类型,
         * 第二个参数是输出的数据类型;
         * 这里输入一行数据line,返回一个迭代器,
         * 迭代器中装的一行文本被按照空格切分后的单词;
         */
        JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
            @Override
            public Iterable<String> call(String line) throws Exception {
                return Arrays.asList(line.split(" "));
            }
        });

        /**
         * 每个单词每出现一次就计数为1
         * 在scala中调用的是map方法,而在java中调用的则是mapToPair方法,
         * mapToPair方法表示将一个map变成一个元组;
         *
         * 匿名函数PairFunction的泛型有3个:
         *  (1)第一个参数表示输入,这里输入的是单词;
         *  (2)第二个和第三个参数是返回的元组中的两个元素的数据类型,这里返回的是单词和数字1;
         *
         * 在java中没有Tuple类型的数据结构,所以它就搞了一个Tuple2类来模拟Scala中的Tuple;
         */
        JavaPairRDD<String, Integer> ones = words.mapToPair(new PairFunction<String, String, Integer>() {
            @Override
            public Tuple2<String, Integer> call(String word) throws Exception {
                return new Tuple2<String, Integer>(word, 1);
            }
        });

        /**
         * 分组聚合
         *
         * 我们可以调用GroupByKey方法,但是它的效率比较低,
         * 我们可以调用ReduceByKey方法,它会先在局部聚合,
         * 然后再全局聚合,相当于有一个Combine的功能;
         *
         * reducebyKey需要一个Function2类型的匿名类,
         * 这个Function2有3个泛型,前两个类型表示要对输入的两个数字进行叠加,
         * 最后一个类型表示返回两个数字叠加后的和;
         * reducebyKey只对value进行聚合,而key不用管;
         */
        JavaPairRDD<String, Integer> counts =  ones.reduceByKey(new Function2<Integer, Integer, Integer>() {
            @Override
            public Integer call(Integer i1, Integer i2) throws Exception {
                return i1 + i2;
            }
        });

        /**
         * 反转,反转是为了后面的排序
         */
        JavaPairRDD<Integer, String> swapedPair = counts.mapToPair(new PairFunction<Tuple2<String, Integer>, Integer, String>() {
            @Override
            public Tuple2<Integer, String> call(Tuple2<String, Integer> tp) throws Exception {
                //将元组中数据交换位置的第一种方式(下面还有第二种方式)
                return new Tuple2<Integer, String>(tp._2, tp._1);
            }
        });

        /**
         * 排序
         *
         * java只提供了sortByKey,它只能按照key进行排序,
         * 而我们要按照value来排序,所以需要先将元组中的两个
         * 元素进行反转,在根据key进行排序,最后再反转回来;
         */
        JavaPairRDD<Integer, String> sortedPair = swapedPair.sortByKey(false);

        JavaPairRDD<String, Integer> finalResult = sortedPair.mapToPair(new PairFunction<Tuple2<Integer, String>, String, Integer>() {
            @Override
            public Tuple2<String, Integer> call(Tuple2<Integer, String> tp) throws Exception {
                //将元组中的数据交换位置的第二种方式(swap就是交换的意思)
                return tp.swap();
            }
        });

        //将结果存储到文件系统
        finalResult.saveAsTextFile(args[1]);

        //释放资源
        sc.stop();

    }
}

4) 运行程序
将编写好的JavaWordCount程序打成jar包并上传到Spark集群服务器。
在运行程序之前，检查一下hdfs上是否已经存在“/wordcount/output”目录，若存在则删除。
在集群环境都正常运行的前提下，使用如下命令来运行我们的JavaWordCount程序，注意要使用“—class”来指定要运行的类为“com.xuebusi.spark.JavaWordCount”：

/root/apps/spark/bin/spark-submit \
--master spark://hadoop01:7077,hadoop02:7077 \
--executor-memory 512m \
--total-executor-cores 7 \
--class com.xuebusi.spark.JavaWordCount \
/root/spark-1.0-SNAPSHOT.jar \
hdfs://hadoop01:9000/wordcount/input \
hdfs://hadoop01:9000/wordcount/output