序:本以为今天花点时间将WordCount例子完全理解到,但高估自己了,更别说我只是在大学选修一学期的java,之后再也没碰过java语言了
总的来说,从宏观上能理解具体的程序思路,但具体到每个代码有什么作用,什么原理,那还需要花点时间,毕竟需要一点java基础和hadoop的运行机制的知识
首先启动hadoop;
[hadoop@hadoop01 eclipse]$ cd ~/hadoop-3.2.0
[hadoop@hadoop01 hadoop-3.2.0]$ sbin/start-all.sh
WARNING: Attempting to start all Apache Hadoop daemons as hadoop in 10 seconds.
WARNING: This is not a recommended production deployment configuration.
WARNING: Use CTRL-C to abort.
Starting namenodes on [hadoop01]
Starting datanodes
Starting secondary namenodes [hadoop01]
Starting resourcemanager
Starting nodemanagers
[hadoop@hadoop01 hadoop-3.2.0]$ jps
8497 NameNode
9121 ResourceManager
8868 SecondaryNameNode
9268 NodeManager
9630 Jps
然后,进入root权限打开eclipse;
[hadoop@hadoop01 hadoop-3.2.0]$ su root
Password:
[root@hadoop01 hadoop-3.2.0]# cd ..
[root@hadoop01 hadoop]# cd eclipse
[root@hadoop01 eclipse]# ./eclipse
在eclipse的window里面show view打开terminal;
在eclipse中点击打开open a terminal,在终端中输入命令:gedit input.txt;
在文档中任意输入内容;
在终端中输入命令:hadoop fs -put /home/hadoop/input.txt /test/;
最后,file--new--project--MapReduce project并取项目名“Wordcount”,再从创建的文件下src中new--package并为包取名“com.hadoop”,又在src下new--class并为类取名“Wordcount”,然后将下面的代码粘贴进去。
然后可以run as hadoop,成功运行得到计算结果
注:若package下无log4j.properties,会报错,需在该文件下手动添加该文件。
内容 如下:
# Configure logging for testing: optionally with log file
#log4j.rootLogger=debug,appender
log4j.rootLogger=info,appender
#log4j.rootLogger=error,appender
#u8F93u51FAu5230u63A7u5236u53F0
log4j.appender.appender=org.apache.log4j.ConsoleAppender
#u6837u5F0Fu4E3ATTCCLayout
log4j.appender.appender.layout=org.apache.log4j.TTCCLayout
附代码:
/** * 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; public class WordCount { public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable>{ private final static IntWritable one = new IntWritable(1); private Text word = new Text(); public void map(Object key, Text value, Context context ) throws IOException, InterruptedException { StringTokenizer itr = new StringTokenizer(value.toString()); while (itr.hasMoreTokens()) { word.set(itr.nextToken()); context.write(word, one); } } } public static class IntSumReducer extends Reducer<Text,IntWritable,Text,IntWritable> { private IntWritable result = new IntWritable(); public void reduce(Text key, Iterable<IntWritable> values, Context context ) throws IOException, InterruptedException { int sum = 0; for (IntWritable val : values) { sum += val.get(); } result.set(sum); context.write(key, result); } } public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs(); if (otherArgs.length < 2) { System.err.println("Usage: wordcount <in> [<in>...] <out>"); System.exit(2); } Job job = Job.getInstance(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); for (int i = 0; i < otherArgs.length - 1; ++i) { FileInputFormat.addInputPath(job, new Path(otherArgs[i])); } FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1])); System.exit(job.waitForCompletion(true) ? 0 : 1); } }