hbase-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Ted Yu <yuzhih...@gmail.com>
Subject Re: Region statistics created during major compaction
Date Wed, 30 Apr 2014 10:26:05 GMT
Interesting idea. 

How would the ranges of rows be determined per region ?

This reminds me of stripe compaction feature which is in 0.98
See HBASE-7667

Cheers

On Apr 30, 2014, at 3:07 AM, Jan Lukavsk√Ĺ <jan.lukavsky@firma.seznam.cz> wrote:

> Hi all,
> 
> I have a general idea I'd like to consult. A short description of a problem we are facing:
during mapreduce jobs run over HBase cluster, we very often see great disproportions in run
time of different map tasks (some tasks tend to finish in minutes or even seconds, while others
might take even hours). This causes the job to run inefficiently and the whole cluster to
be underutilized - reducers have to wait until all the map tasks finish - at least before
starting the sort phase. The number of long running map tasks is usually low, so the whole
cluster basically waits until several machines finish their work. We tried to get over this
by sampling the regions and creating some statistics (one statistic per mapreduce job), which
we then used to tune the input format splits to make the distribution of running time more
even. This seems to work (although at the time being might cause some issues with data locality,
which we think we can solve).
> 
> Now, the questions is, would it be possible to calculate some statistics during major
compactions and store them in the region directory on HDFS? What I mean by these statistics,
I think it could be possible to store for some reasonable ranges of rows (so that for each
region there would be like hundreds of these ranges):
> * total number of rows between specified rows
> * total number of KeyValues
> * amount of data stored on disk
> 
> These statistics could be calculated per column family and subsequently used in InputFormat
to tune the splits to match even distribution as close as possible.
> 
> Is anyone else interested in this? Does anyone have any other solution to the problem
I have described? I know we could say manually split regions that take long time to process,
but first, these regions are job-specific (so different jobs have different regions that take
long time to process), and second, ideally I'm looking for an automated solution.
> 
> Thanks for reply,
> Jan
> 

Mime
View raw message