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From "Zhang, jian" <jzh...@freewheel.tv>
Subject 答复: Problem with key aggregation when number of reduce tasks is more than 1
Date Fri, 11 Apr 2008 11:16:29 GMT

Please read this, you need to implement partitioner.
It controls which key is sent to which reducer, if u want to get unique key result, you need
to implement partitioner and the compareTO function should work properly. 

Partitioner partitions the key space.

Partitioner controls the partitioning of the keys of the intermediate map-outputs. The key
(or a subset of the key) is used to derive the partition, typically by a hash function. The
total number of partitions is the same as the number of reduce tasks for the job. Hence this
controls which of the m reduce tasks the intermediate key (and hence the record) is sent to
for reduction.

HashPartitioner is the default Partitioner.

Best Regards

Jian Zhang

发件人: Harish Mallipeddi [mailto:harish.mallipeddi@gmail.com] 
发送时间: 2008年4月11日 19:06
收件人: core-user@hadoop.apache.org
主题: Problem with key aggregation when number of reduce tasks is more than 1

Hi all,

I wrote a custom key class (implements WritableComparable) and implemented
the compareTo() method inside this class. Everything works fine when I run
the m/r job with 1 reduce task (via setNumReduceTasks). Keys are sorted
correctly in the output files.

But when I increase the number of reduce tasks, keys don't get aggregated
properly; same keys seem to end up in separate output files
(output/part-00000, output/part-00001, etc). This should not happen because
right before reduce() gets called, all (k,v) pairs from all map outputs with
the same 'k' are aggregated and the reduce function just iterates over the
values (v1, v2, etc)?

Do I need to implement anything else inside my custom key class other than
compareTo? I also tried implementing equals() but that didn't help either.
Then I came across setOutputKeyComparator(). So I added a custom Comparator
class inside the key class and tried setting this on the JobConf object. But
that didn't work either. What could be wrong?


Harish Mallipeddi
circos.com : poundbang.in/blog/

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