组合键正在更改,Hadoop Map Reduce



我刚刚开始学习hadoop,并使用自定义partitioner和comparator运行hadoop map reduce程序。我面临的问题是,主要和次要排序没有在复合键上完成,一个复合键的更多部分正在与其他复合键部分一起更改。

例如,我正在映射程序中创建以下密钥

key1 -> tagA,1 
key2 -> tagA,1 
key3 -> tagA,1
key4 -> tagA,1 
key5 -> tagA,2 
key6 -> tagA,2
key7 -> tagB,1 
key8 -> tagB,1 
key9 -> tagB,1
key10 -> tagB,1 
key11 -> tagB,2 
key12 -> tagB,2

以及分割器和组合器如下

    //Partitioner
public static class TaggedJoiningPartitioner implements Partitioner<Text, Text> {   
    @Override
    public int getPartition(Text key, Text value, int numPartitions) {
        String line = key.toString();
        String tokens[] = line.split(",");
        return (tokens[0].hashCode() & Integer.MAX_VALUE)% numPartitions;
    }
    @Override
    public void configure(JobConf arg0) {
        // TODO Auto-generated method stub //NOT OVERRIDING THIS METHOD
    }
}
//Comparator
public static class TaggedJoiningGroupingComparator extends WritableComparator {
    public TaggedJoiningGroupingComparator() {
        super(Text.class, true);
    }
    @Override
    public int compare(WritableComparable a, WritableComparable b) {
        String taggedKey1[] = ((Text)a).toString().split(",");
        String taggedKey2[] = ((Text)b).toString().split(",");
        return taggedKey1[0].compareTo(taggedKey2[0]);
    }
}

在reducer中,这些键根据标签正确分组,但没有正确排序。减速器中密钥的顺序和内容如下:

//REDUCER 1
key1 -> tagA,1 
key2 -> tagA,1 
key3 -> tagA,1
key5 -> tagA,1 //2 changed by 1 here
key6 -> tagA,1 //2 changed by 1 here
key4 -> tagA,1 
//REDUCER 2
key7 ->  tagB,1 
key11 -> tagB,1 //2 changed by 1 here
key12 -> tagB,1 //2 changed by 1 here
key8 ->  tagB,1 
key9 ->  tagB,1
key10 -> tagB,1  

花了很长时间试图解决这个问题,但还没有成功,有什么帮助吗?

终于让它工作起来了,实际上我改变了

conf.setOutputKeyComparatorClass(TaggedJoiningGroupingComparator.class); 

conf.setOutputValueGroupingComparator(TaggedJoiningGroupingComparator.class);

同样来自hadoop API文档。——

setOutputValueGroupingComparator(Class<? extends RawComparator> theClass)
Set the user defined RawComparator comparator for grouping keys in the input to the reduce.

相关内容

  • 没有找到相关文章

最新更新