Hadoop笔记【1】
- What's Hadoop
一个支持数据密集型分布式系统的软件框架，使用java编程语言。能够支持成千上万个节点和海量数据处理的集群计算。
Hadoop Homepage:http://hadoop.apache.org/
Hadoop 中文资料：http://hadoop.apache.org/common/docs/r0.18.2/cn/index.html
- Linux安装
- 下载hadoop最新的release版本（hadoop-0.21.0）
- 安装jdk，配置好环境变量
- 安装ssh和rsync
- 详细教程见：http://hadoop.apache.org/common/docs/r0.18.2/cn/quickstart.html
- Hadoop Hello Word程序-WordCount
1. package org.myorg; 2. 3. import java.io.IOException; 4. import java.util.*; 5. 6. import org.apache.hadoop.fs.Path; 7. import org.apache.hadoop.conf.*; 8. import org.apache.hadoop.io.*; 9. import org.apache.hadoop.mapred.*; 10. import org.apache.hadoop.util.*; 11. 12. public class WordCount { 13. 14. public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> { 15. private final static IntWritable one = new IntWritable(1); 16. private Text word = new Text(); 17. 18. public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { 19. String line = value.toString(); 20. StringTokenizer tokenizer = new StringTokenizer(line); 21. while (tokenizer.hasMoreTokens()) { 22. word.set(tokenizer.nextToken()); 23. output.collect(word, one); 24. } 25. } 26. } 27. 28. public static class Reduce extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> { 29. public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { 30. int sum = 0; 31. while (values.hasNext()) { 32. sum += values.next().get(); 33. } 34. output.collect(key, new IntWritable(sum)); 35. } 36. } 37. 38. public static void main(String[] args) throws Exception { 39. JobConf conf = new JobConf(WordCount.class); 40. conf.setJobName("wordcount"); 41. 42. conf.setOutputKeyClass(Text.class); 43. conf.setOutputValueClass(IntWritable.class); 44. 45. conf.setMapperClass(Map.class); 46. conf.setCombinerClass(Reduce.class); 47. conf.setReducerClass(Reduce.class); 48. 49. conf.setInputFormat(TextInputFormat.class); 50. conf.setOutputFormat(TextOutputFormat.class); 51. 52. FileInputFormat.setInputPaths(conf, new Path(args[0])); 53. FileOutputFormat.setOutputPath(conf, new Path(args[1])); 54. 55. JobClient.runJob(conf); 57. } 58. } 59.
用eclipse将代码打包成jar文件：wordcount.jar。将wordcount.jar拷贝到hadoop的根目录下。
$:~cd hadoop-0.21.0 $:~mkdir input $:~cd input $:~mkdir test $:~cd test $:~echo "hello world haoop, hello hadoop" > testfile1.txt $:~echo "hello world haoop, hello hadoop" > testfile1.txt $:~bin/hadoop dfs -put ./input/test/ /input $:~bin/hadoop jar wordcount.jar WordCount ./input/test ./output/wordcount
- 结果
