Distribute Cached 使用

  在Kettle中说到Pentaho的MapReduce要用到它,就查了一下关于它的资料,以下是从官方查到的内容,记录一下。

  DistributedCache: 一些比较小的需要共享的文件或者jar包,我们先存到hdfs上,然后在MapReduce线程当中进行共享,直接用了。

    // Setting up the cache for the application
     
     1. Copy the requisite files to the FileSystem:
     
     $ bin/hadoop fs -copyFromLocal lookup.dat /myapp/lookup.dat  
     $ bin/hadoop fs -copyFromLocal map.zip /myapp/map.zip  
     $ bin/hadoop fs -copyFromLocal mylib.jar /myapp/mylib.jar
     $ bin/hadoop fs -copyFromLocal mytar.tar /myapp/mytar.tar
     $ bin/hadoop fs -copyFromLocal mytgz.tgz /myapp/mytgz.tgz
     $ bin/hadoop fs -copyFromLocal mytargz.tar.gz /myapp/mytargz.tar.gz
2. Setup the application's JobConf: JobConf job = new JobConf();
   // #lookup.dat 表示给前面的这个文件取一个别名,类似sql里面的as别名一样
DistributedCache.addCacheFile(
new URI("/myapp/lookup.dat#lookup.dat"), job); DistributedCache.addCacheArchive(new URI("/myapp/map.zip", job); DistributedCache.addFileToClassPath(new Path("/myapp/mylib.jar"), job); DistributedCache.addCacheArchive(new URI("/myapp/mytar.tar", job); DistributedCache.addCacheArchive(new URI("/myapp/mytgz.tgz", job); DistributedCache.addCacheArchive(new URI("/myapp/mytargz.tar.gz", job);
3. Use the cached files in the Mapper or Reducer: public static class MapClass extends MapReduceBase implements Mapper<K, V, K, V> { private Path[] localArchives; private Path[] localFiles; public void configure(JobConf job) { // Get the cached archives/files localArchives = DistributedCache.getLocalCacheArchives(job); localFiles = DistributedCache.getLocalCacheFiles(job); } public void map(K key, V value, OutputCollector<K, V> output, Reporter reporter) throws IOException { // Use data from the cached archives/files here // ... // ... output.collect(k, v); } }

  查看代码了才知道其实它根本不是什么缓存,它只不过是在配置文件中的指定属性记录下相应的值,然后在mapreduce的时候,调用配置文件里面的属性值,然后取得需要的文件盒jar包。

 

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