網上的MapReduce WordCount教程對於如何編譯WordCount.java幾乎是一筆帶過… 而有寫到的,大多又是 0.20 等舊版本版本的做法,即 javac -classpath /usr/local/Hadoop/hadoop-1.0.1/hadoop-core-1.0.1.jar WordCount.java
,但較新的 2.X 版本中,已經沒有 hadoop-core*.jar 這個文件,因此編輯和打包自己的MapReduce程序與舊版本有所不同。
本文以 Hadoop 2.4.1 環境下的WordCount實例來介紹 2.x 版本中如何編輯自己的MapReduce程序。
Hadoop 2.x 版本中jar不再集中在一個 hadoop-core*.jar 中,而是分成多個 jar,如運行WordCount實例需要如下三個 jar:
將上述 jar 添加至 classpath 路徑:
export CLASSPATH="$HADOOP_HOME/share/hadoop/common/hadoop-common-2.4.1.jar:$HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.4.1.jar:$HADOOP_HOME/share/hadoop/common/lib/commons-cli-1.2.jar:$CLASSPATH"
接著就可以編譯 WordCount.java 了(使用的是 2.4.1 源碼中的 WordCount.java,源碼在文本最後面):
javac WordCount.java
編譯時會有警告,可以忽略。編譯後可以看到生成了幾個.class文件。
使用Javac編譯自己的MapReduce程序
接著把 .class 文件打包成 jar,才能在 Hadoop 中運行:
jar -cvf WordCount.jar ./WordCount*.class
打包完成後,運行試試,創建幾個輸入文件:
Mkdir input
echo "echo of the rainbow" > ./input/file0
echo "the waiting game" > ./input/file1
創建WordCount的輸入
開始運行:
/usr/local/hadoop/bin/hadoop jar WordCount.jar WordCount input output
不過這邊可能會遇到如下的提示 Exception in thread "main" java.lang.NoClassDefFoundError: WordCount
:
提示找不到 WordCount 類
因為程序中聲明了 package ,所以在命令中也要 org.apache.hadoop.examples
寫完整:
/usr/local/hadoop/bin/hadoop jar WordCount.jar org.apache.hadoop.examples.WordCount input output
正確運行後的結果如下:
WordCount 運行結果
使用命令行編譯運行MapReduce程序畢竟有些麻煩,修改一次就得手動編譯、打包一次,使用Eclipse編譯運行MapReduce程序會更加方便。
文件位於 hadoop-2.4.1-src\hadoop-mapreduce-project\hadoop-mapreduce-examples\src\main\java\org\apache\hadoop\examples 中:
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.examples;
import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
publicclassWordCount{
publicstaticclassTokenizerMapper
extendsMapper<Object,Text,Text,IntWritable>{
privatefinalstaticIntWritable one =newIntWritable(1);
privateText word =newText();
publicvoid map(Object key,Text value,Context context
)throwsIOException,InterruptedException{
StringTokenizer itr =newStringTokenizer(value.toString());
while(itr.hasMoreTokens()){
word.set(itr.nextToken());
context.write(word, one);
}
}
}
publicstaticclassIntSumReducer
extendsReducer<Text,IntWritable,Text,IntWritable>{
privateIntWritable result =newIntWritable();
publicvoid reduce(Text key,Iterable<IntWritable> values,
Context context
)throwsIOException,InterruptedException{
int sum =0;
for(IntWritable val : values){
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}
publicstaticvoid main(String[] args)throwsException{
Configuration conf =newConfiguration();
String[] otherArgs =newGenericOptionsParser(conf, args).getRemainingArgs();
if(otherArgs.length !=2){
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
Job job =newJob(conf,"word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job,newPath(otherArgs[0]));
FileOutputFormat.setOutputPath(job,newPath(otherArgs[1]));
System.exit(job.waitForCompletion(true)?0:1);
}
}
CentOS安裝和配置Hadoop2.2.0 http://www.linuxidc.com/Linux/2014-01/94685.htm
Ubuntu 13.04上搭建Hadoop環境 http://www.linuxidc.com/Linux/2013-06/86106.htm
Ubuntu 12.10 +Hadoop 1.2.1版本集群配置 http://www.linuxidc.com/Linux/2013-09/90600.htm
Ubuntu上搭建Hadoop環境(單機模式+偽分布模式) http://www.linuxidc.com/Linux/2013-01/77681.htm
Ubuntu下Hadoop環境的配置 http://www.linuxidc.com/Linux/2012-11/74539.htm
單機版搭建Hadoop環境圖文教程詳解 http://www.linuxidc.com/Linux/2012-02/53927.htm
搭建Hadoop環境(在Winodws環境下用虛擬機虛擬兩個Ubuntu系統進行搭建) http://www.linuxidc.com/Linux/2011-12/48894.htm
更多Hadoop相關信息見Hadoop 專題頁面 http://www.linuxidc.com/topicnews.aspx?tid=13