【发布时间】:2013-06-22 07:53:44
【问题描述】:
我有 hadoop 运行,基本上只是聚合键,它的代码: (mapper是身份映射器)
public void reduce(Text key, Iterator<Text> values,
OutputCollector<Text, Text> results, Reporter reporter) throws IOException {
String res = new String("");
while(values.hasNext())
{
res += values.next().toString();
}
Text outputValue = new Text("<all><id>"+key.toString()+"</id>"+res+"</all>");
results.collect(key, outputValue);
}
它停留在这个水平:
12/11/26 06:19:23 INFO mapred.JobClient: Running job: job_201210240845_0099
12/11/26 06:19:24 INFO mapred.JobClient: map 0% reduce 0%
12/11/26 06:19:37 INFO mapred.JobClient: map 20% reduce 0%
12/11/26 06:19:40 INFO mapred.JobClient: map 80% reduce 0%
12/11/26 06:19:41 INFO mapred.JobClient: map 100% reduce 0%
12/11/26 06:19:46 INFO mapred.JobClient: map 100% reduce 6%
12/11/26 06:19:55 INFO mapred.JobClient: map 100% reduce 66%
我在本地运行它并看到了这个:
12/11/26 06:06:48 INFO mapred.LocalJobRunner:
12/11/26 06:06:48 INFO mapred.Merger: Merging 5 sorted segments
12/11/26 06:06:48 INFO mapred.Merger: Down to the last merge-pass, with 5 segments left of total size: 82159206 bytes
12/11/26 06:06:48 INFO mapred.LocalJobRunner:
12/11/26 06:06:54 INFO mapred.LocalJobRunner: reduce > reduce
12/11/26 06:06:55 INFO mapred.JobClient: map 100% reduce 66%
12/11/26 06:06:57 INFO mapred.LocalJobRunner: reduce > reduce
12/11/26 06:07:00 INFO mapred.LocalJobRunner: reduce > reduce
12/11/26 06:07:03 INFO mapred.LocalJobRunner: reduce > reduce
...
a lot of reduce > reduce ...
...
最后,它完成了工作。我想问:
1) 它在这个 reduce > reduce 阶段做了什么?
2) 我该如何改进?
【问题讨论】: