Hadoop入门经典:WordCount 分类: A1_HADOOP 2014-08-20 14:43 2514人阅读 评论(0) 收藏
以下程序在hadoop1.2.1上测试成功。
本例先将源代码呈现,然后详细说明执行步骤,最后对源代码及执行过程进行分析。
一、源代码
package org.jediael.hadoopdemo.wordcount; 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.LongWritable; 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.input.TextInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; public class WordCount { public static class WordCountMap extends Mapper<LongWritable, Text, Text, IntWritable> { private final IntWritable one = new IntWritable(1); private Text word = new Text(); public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String line = value.toString(); StringTokenizer token = new StringTokenizer(line); while (token.hasMoreTokens()) { word.set(token.nextToken()); context.write(word, one); } } } public static class WordCountReduce extends Reducer<Text, IntWritable, Text, IntWritable> { public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException { int sum = 0; for (IntWritable val : values) { sum += val.get(); } context.write(key, new IntWritable(sum)); } } public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); Job job = new Job(conf); job.setJarByClass(WordCount.class); job.setJobName("wordcount"); job.setOutputKeyClass(Text.class); job.setOutputValueClass(IntWritable.class); job.setMapperClass(WordCountMap.class); job.setReducerClass(WordCountReduce.class); job.setInputFormatClass(TextInputFormat.class); job.setOutputFormatClass(TextOutputFormat.class); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); job.waitForCompletion(true); } }
二、执行程序
1、从eclipse从导出至wordcount.jar,并上传至hadoop服务器,本例中,将程序上传至/home/jediael/project。
2、安装hadoop伪分布模式,可参考Hadoop1.2.1伪分布模式安装指南,本实例将运行在hadoop的伪公布环境中。
3、在HDFS中创建目录wcinput,用作输入目录,并将需要分析的文件复制到目录下。
[root@jediael conf]# hadoop fs -mkdir wcinput [root@jediael conf]# hadoop fs -copyFromLocal * wcinput [root@jediael conf]# hadoop fs -ls wcinput Found 26 items -rw-r--r-- 1 root supergroup 1524 2014-08-20 12:29 /user/root/wcinput/automaton-urlfilter.txt -rw-r--r-- 1 root supergroup 1311 2014-08-20 12:29 /user/root/wcinput/configuration.xsl -rw-r--r-- 1 root supergroup 131090 2014-08-20 12:29 /user/root/wcinput/domain-suffixes.xml -rw-r--r-- 1 root supergroup 4649 2014-08-20 12:29 /user/root/wcinput/domain-suffixes.xsd -rw-r--r-- 1 root supergroup 824 2014-08-20 12:29 /user/root/wcinput/domain-urlfilter.txt -rw-r--r-- 1 root supergroup 3368 2014-08-20 12:29 /user/root/wcinput/gora-accumulo-mapping.xml -rw-r--r-- 1 root supergroup 3279 2014-08-20 12:29 /user/root/wcinput/gora-cassandra-mapping.xml -rw-r--r-- 1 root supergroup 3447 2014-08-20 12:29 /user/root/wcinput/gora-hbase-mapping.xml -rw-r--r-- 1 root supergroup 2677 2014-08-20 12:29 /user/root/wcinput/gora-sql-mapping.xml -rw-r--r-- 1 root supergroup 2993 2014-08-20 12:29 /user/root/wcinput/gora.properties -rw-r--r-- 1 root supergroup 983 2014-08-20 12:29 /user/root/wcinput/hbase-site.xml -rw-r--r-- 1 root supergroup 3096 2014-08-20 12:29 /user/root/wcinput/httpclient-auth.xml -rw-r--r-- 1 root supergroup 3948 2014-08-20 12:29 /user/root/wcinput/log4j.properties -rw-r--r-- 1 root supergroup 511 2014-08-20 12:29 /user/root/wcinput/nutch-conf.xsl -rw-r--r-- 1 root supergroup 42610 2014-08-20 12:29 /user/root/wcinput/nutch-default.xml -rw-r--r-- 1 root supergroup 753 2014-08-20 12:29 /user/root/wcinput/nutch-site.xml -rw-r--r-- 1 root supergroup 347 2014-08-20 12:29 /user/root/wcinput/parse-plugins.dtd -rw-r--r-- 1 root supergroup 3016 2014-08-20 12:29 /user/root/wcinput/parse-plugins.xml -rw-r--r-- 1 root supergroup 857 2014-08-20 12:29 /user/root/wcinput/prefix-urlfilter.txt -rw-r--r-- 1 root supergroup 2484 2014-08-20 12:29 /user/root/wcinput/regex-normalize.xml -rw-r--r-- 1 root supergroup 1736 2014-08-20 12:29 /user/root/wcinput/regex-urlfilter.txt -rw-r--r-- 1 root supergroup 18969 2014-08-20 12:29 /user/root/wcinput/schema-solr4.xml -rw-r--r-- 1 root supergroup 6020 2014-08-20 12:29 /user/root/wcinput/schema.xml -rw-r--r-- 1 root supergroup 1766 2014-08-20 12:29 /user/root/wcinput/solrindex-mapping.xml -rw-r--r-- 1 root supergroup 1044 2014-08-20 12:29 /user/root/wcinput/subcollections.xml -rw-r--r-- 1 root supergroup 1411 2014-08-20 12:29 /user/root/wcinput/suffix-urlfilter.txt4、运行程序
[root@jediael project]# hadoop org.jediael.hadoopdemo.wordcount.WordCount wcinput wcoutput3 14/08/20 12:50:25 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same. 14/08/20 12:50:26 INFO input.FileInputFormat: Total input paths to process : 26 14/08/20 12:50:26 INFO util.NativeCodeLoader: Loaded the native-hadoop library 14/08/20 12:50:26 WARN snappy.LoadSnappy: Snappy native library not loaded 14/08/20 12:50:26 INFO mapred.JobClient: Running job: job_201408191134_0005 14/08/20 12:50:27 INFO mapred.JobClient: map 0% reduce 0% 14/08/20 12:50:38 INFO mapred.JobClient: map 3% reduce 0% 14/08/20 12:50:39 INFO mapred.JobClient: map 7% reduce 0% 14/08/20 12:50:50 INFO mapred.JobClient: map 15% reduce 0% 14/08/20 12:50:57 INFO mapred.JobClient: map 19% reduce 0% 14/08/20 12:50:58 INFO mapred.JobClient: map 23% reduce 0% 14/08/20 12:51:00 INFO mapred.JobClient: map 23% reduce 5% 14/08/20 12:51:04 INFO mapred.JobClient: map 30% reduce 5% 14/08/20 12:51:06 INFO mapred.JobClient: map 30% reduce 10% 14/08/20 12:51:11 INFO mapred.JobClient: map 38% reduce 10% 14/08/20 12:51:16 INFO mapred.JobClient: map 38% reduce 11% 14/08/20 12:51:18 INFO mapred.JobClient: map 46% reduce 11% 14/08/20 12:51:19 INFO mapred.JobClient: map 46% reduce 12% 14/08/20 12:51:22 INFO mapred.JobClient: map 46% reduce 15% 14/08/20 12:51:25 INFO mapred.JobClient: map 53% reduce 15% 14/08/20 12:51:31 INFO mapred.JobClient: map 53% reduce 17% 14/08/20 12:51:32 INFO mapred.JobClient: map 61% reduce 17% 14/08/20 12:51:39 INFO mapred.JobClient: map 69% reduce 17% 14/08/20 12:51:40 INFO mapred.JobClient: map 69% reduce 20% 14/08/20 12:51:45 INFO mapred.JobClient: map 73% reduce 20% 14/08/20 12:51:46 INFO mapred.JobClient: map 76% reduce 23% 14/08/20 12:51:52 INFO mapred.JobClient: map 80% reduce 23% 14/08/20 12:51:53 INFO mapred.JobClient: map 84% reduce 23% 14/08/20 12:51:55 INFO mapred.JobClient: map 84% reduce 25% 14/08/20 12:51:59 INFO mapred.JobClient: map 88% reduce 25% 14/08/20 12:52:00 INFO mapred.JobClient: map 92% reduce 25% 14/08/20 12:52:02 INFO mapred.JobClient: map 92% reduce 29% 14/08/20 12:52:06 INFO mapred.JobClient: map 96% reduce 29% 14/08/20 12:52:07 INFO mapred.JobClient: map 100% reduce 29% 14/08/20 12:52:11 INFO mapred.JobClient: map 100% reduce 30% 14/08/20 12:52:15 INFO mapred.JobClient: map 100% reduce 100% 14/08/20 12:52:17 INFO mapred.JobClient: Job complete: job_201408191134_0005 14/08/20 12:52:18 INFO mapred.JobClient: Counters: 29 14/08/20 12:52:18 INFO mapred.JobClient: Job Counters 14/08/20 12:52:18 INFO mapred.JobClient: Launched reduce tasks=1 14/08/20 12:52:18 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=192038 14/08/20 12:52:18 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0 14/08/20 12:52:18 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0 14/08/20 12:52:18 INFO mapred.JobClient: Launched map tasks=26 14/08/20 12:52:18 INFO mapred.JobClient: Data-local map tasks=26 14/08/20 12:52:18 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=95814 14/08/20 12:52:18 INFO mapred.JobClient: File Output Format Counters 14/08/20 12:52:18 INFO mapred.JobClient: Bytes Written=123950 14/08/20 12:52:18 INFO mapred.JobClient: FileSystemCounters 14/08/20 12:52:18 INFO mapred.JobClient: FILE_BYTES_READ=352500 14/08/20 12:52:18 INFO mapred.JobClient: HDFS_BYTES_READ=247920 14/08/20 12:52:18 INFO mapred.JobClient: FILE_BYTES_WRITTEN=2177502 14/08/20 12:52:18 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=123950 14/08/20 12:52:18 INFO mapred.JobClient: File Input Format Counters 14/08/20 12:52:18 INFO mapred.JobClient: Bytes Read=244713 14/08/20 12:52:18 INFO mapred.JobClient: Map-Reduce Framework 14/08/20 12:52:18 INFO mapred.JobClient: Map output materialized bytes=352650 14/08/20 12:52:18 INFO mapred.JobClient: Map input records=7403 14/08/20 12:52:18 INFO mapred.JobClient: Reduce shuffle bytes=352650 14/08/20 12:52:18 INFO mapred.JobClient: Spilled Records=45210 14/08/20 12:52:18 INFO mapred.JobClient: Map output bytes=307281 14/08/20 12:52:18 INFO mapred.JobClient: Total committed heap usage (bytes)=3398606848 14/08/20 12:52:18 INFO mapred.JobClient: CPU time spent (ms)=14400 14/08/20 12:52:18 INFO mapred.JobClient: Combine input records=0 14/08/20 12:52:18 INFO mapred.JobClient: SPLIT_RAW_BYTES=3207 14/08/20 12:52:18 INFO mapred.JobClient: Reduce input records=22605 14/08/20 12:52:18 INFO mapred.JobClient: Reduce input groups=6749 14/08/20 12:52:18 INFO mapred.JobClient: Combine output records=0 14/08/20 12:52:18 INFO mapred.JobClient: Physical memory (bytes) snapshot=4799041536 14/08/20 12:52:18 INFO mapred.JobClient: Reduce output records=6749 14/08/20 12:52:18 INFO mapred.JobClient: Virtual memory (bytes) snapshot=19545337856 14/08/20 12:52:18 INFO mapred.JobClient: Map output records=226055、查看结果
root@jediael project]# hadoop fs -ls wcoutput3 Found 3 items -rw-r--r-- 1 root supergroup 0 2014-08-20 12:52 /user/root/wcoutput3/_SUCCESS drwxr-xr-x - root supergroup 0 2014-08-20 12:50 /user/root/wcoutput3/_logs -rw-r--r-- 1 root supergroup 123950 2014-08-20 12:52 /user/root/wcoutput3/part-r-00000 [root@jediael project]# hadoop fs -cat wcoutput3/part-r-00000 !! 2 !ci.*.*.us 1 !co.*.*.us 1 !town.*.*.us 1 "AS 22 "Accept" 1 "Accept-Language" 1 "License"); 22 "NOW" 1 "WiFi" 1 "Z" 1 "all" 1 "content" 1 "delete 1 "delimiter" 1………………
三、程序分析
1、WordCountMap类继承了org.apache.hadoop.mapreduce.Mapper,4个泛型类型分别是map函数输入key的类型,输入value的类型,输出key的类型,输出value的类型。
2、WordCountReduce类继承了org.apache.hadoop.mapreduce.Reducer,4个泛型类型含义与map类相同。
3、map的输出类型与reduce的输入类型相同,而一般情况下,map的输出类型与reduce的输出类型相同,因此,reduce的输入类型与输出类型相同。
4、hadoop根据以下代码确定输入内容的格式:
job.setInputFormatClass(TextInputFormat.class);
TextInputFormat是hadoop默认的输入方法,它继承自FileInputFormat。在TextInputFormat中,它将数据集切割成小数据集InputSplit,每一个InputSplit由一个mapper处理。此外,InputFormat还提供了一个RecordReader的实现,将一个InputSplit解析成<key,value>的形式,并提供给map函数:
key:这个数据相对于数据分片中的字节偏移量,数据类型是LongWritable。
value:每行数据的内容,类型是Text。
因此,在本例中,map函数的key/value类型是LongWritable与Text。
5、Hadoop根据以下代码确定输出内容的格式:
job.setOutputFormatClass(TextOutputFormat.class);
TextOutputFormat是hadoop默认的输出格式,它会将每条记录一行的形式存入文本文件,如
the 30
happy 23
……
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