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From André Martin <m...@andremartin.de>
Subject Very weak mapred performance on small clusters with a massive amount of small files
Date Thu, 01 Nov 2007 09:49:20 GMT
Hi everyone,
we are experiencing a very weak map-red performance on the following 
mapred cluster setup:

- Hadoop - nightly build from 2007-10-25_17-03-53
- 5 tasktracker-/datanodes + 1 jobtracker-/namenode
- 3.7GB (53,050 files in 18,150 folders - avg. file size: 74kB)

A mapred job takes up to 24 hours before completion on our cluster. 
We've measured and monitored network bandwidth, diskIO, paging, swapping 
and CPU utilization in order to exclude those things as bottlenecks on 
our host machines / network itself. However, a closer look into the log 
files and the source codes revealed the following things:

During the mapping stage, we observed that each task tracker processes 
only one or (a maximum of) two file-splits at a time which equals pretty 
much to sequential reading/processing of 10.000+ files.
(Reading files off the DFS takes only a second or less and we measured a 
relatively high throughputs of ~1.5MB/s). Adjusting / increasing the 
"mapred.tasktracker.tasks.maximum" parameter from the given default 
value of 2 to 10 didn't work - each node still processes only two (at 
max) map tasks at a time...
Another major performance gap seems to lie in the reduce copy phase: The 
load balancing / anti swamping policy on line 972 (in ReduceTask.java) 
which guaranties that each tasktracker copies/fetches only one map 
output at a time (from the "neighboring" tasktrackers) causes very low 
average throughputs of  20kB/s and less. We disabled / commented out the 
"duplicate hosts" check and reached then throughputs up to ~1MB/s in 

It seems like Hadoop scales only well when processing large files on 
large clusters whereas we would like to use it for a huge amount of 
small files on a small cluster... Does anyone have similar 
experiences/cluster setups?

Any thoughts and ideas are much appreciated!
Thanks in advance!

Cu on the 'net,
                        Bye - bye,

                                   <<<<< André <<<< >>>>
èrbnA >>>>>

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