Your output shows that node2 has 13 mappers and the reducer, while
node3 and node4 had only 8 mappers each. So I'd expect some
disparity. Since it's hard to correlate the mapper throughput against
the reducer throughput, it's possible that node3 got just as much work
done.
That doesn't explain why node4 is slower than node3, though.
-andy
On Mon, Jan 7, 2013 at 7:07 PM, Chen, Haifeng <haifeng.c...@intel.com> wrote:
> Dear sir,
>
> I encountered a strange problem that all the mappers on some nodes are much
> slower than the mappers on other nodes as following some times (not always).
> I didn’t see any reasons why they should slow down in this pattern.
>
>
>
> 000013(MAP on node4): --------(8.115)
>
> 000014(MAP on node4): --------(8.570)
>
> 000011(MAP on node4): --------(8.5)
>
> 000016(MAP on node4): --------(8.344)
>
> 000010(MAP on node4): --------(8.585)
>
> 000015(MAP on node4): --------(8.179)
>
> 000017(MAP on node4): --------(8.445)
>
> 000012(MAP on node4): --------(8.312)
>
> 000018(MAP on node2): ---(3.367)
>
> 000020(MAP on node2): ---(3.335)
>
> 000019(MAP on node2): ---(3.320)
>
> 000023(MAP on node2): ---(3.91)
>
> 000022(MAP on node2): ---(3.371)
>
> 000021(MAP on node2): ---(3.458)
>
> 000004(MAP on node3): -------------------(19.624)
>
> 000007(MAP on node3): -------------------(19.92)
>
> 000005(MAP on node3): --------------------(20.613)
>
> 000008(MAP on node3): --------------------(20.316)
>
> 000003(MAP on node3): --------------------(20.574)
>
> 000006(MAP on node3): --------------------(20.654)
>
> 000002(MAP on node3): -------------------(19.935)
>
> 000009(MAP on node3): --------------------(20.489)
>
> 000025(MAP on node2): --(2.877)
>
> 000026(MAP on node2): ---(3.112)
>
> 000027(MAP on node2): --(2.959)
>
> 000024(MAP on node2): --(2.845)
>
> 000029(MAP on node2): --(2.863)
>
> 000028(MAP on node2): --(2.933)
>
> 000031(MAP on node2): --(2.596)
>
> 000030(RED on node2): -------------(13.378)
>
>
>
> The testing is as following:
>
> I have a 4 nodes cluster and all of them has the same hardware and software
> configurations. One node acts as name node and yarn resource manager. Other
> three nodes act as both data node and yarn node manager.
>
>
>
> The test input file is around 7GB file on the HDFS cluster and the
> replication number is 3. (This means that each data node has a copy of every
> block of the file)
>
>
>
> The mapper did nothing and didn’t write out any records:
>
>
>
> public static class KeyMapper
>
> extends Mapper<Object, Text, Text, Text>{
>
> public void map(Object key, Text value, Context context
>
> ) throws IOException, InterruptedException {
>
>
>
> }
>
> }
>
>
>
> So this mapper logically is reading and iterating through its splits of data
> and then finish the job.
>
> I didn’t see any factors in the above configurations that will cause the
> above phenomenon.
>
> I turned on the debug log for each mapper task and it also showed that all
> the mapper’s DFSClient read data from its local data node.
>
>
>
> Can any experts help give some hints for this? I attached the log and client
> code for analysis.
>
>
>
> Thanks,
>
> Haifeng
