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Key: HBASE-1044
URL: https://issues.apache.org/jira/browse/HBASE-1044
Project: Hadoop HBase
Issue Type: Bug
Reporter: stack
From IRC (with some improving text added -- finishes on a good point made by jgray):
{code}18:53 < St^Ack> The coupling in a MR cluster is looser than it is in hbase cluster
18:53 < St^Ack> TTs only need report in every ten minutes and a task can fail and be restarted
18:54 < St^Ack> Whereas with hbase, it must report in at least every two minutes (IIRC) and cannot 'redo' lost edit -- no chance of a redo
18:54 < St^Ack> So, your MR job can be rougher about getting to the finish line; messier.
18:55 < tim_s> yeah.
18:55 < St^Ack> If MR is running on same nodes as those hosting hbase, then it can rob resources from hbase in a way that damages hbase but not TT
18:56 < St^Ack> So, maybe we need to look at the hbase config; make it more tolerant when its running beside a hogging TT job
18:57 < tim_s> hmm, that would be lovely
18:57 < St^Ack> Need to look at HDFS; see how 'fragile' it is too; hbase should be at least that 'fragile'
18:57 < jgray> yeah, most issues we see come from resource issues on shared hdfs/tt/rs nodes
18:57 < tim_s> so is it common to host hbase elsewhere?
18:57 < St^Ack> Let me make an issue on it because this is common failure case for hbase (Setup hbase then run your old MR job as though nothing has changed -- then surprise when the little hbase lady faints)
18:57 < jgray> tim_s: currently, no. common practice is shared
18:58 < St^Ack> ... and its better if shared -- locality benefits
18:58 < tim_s> would that be a good idea though? cause I don't really need to have hadoop local I guess.
18:58 < tim_s> ahh
18:58 < apurtell> we share also
...
18:59 < jgray> beyond locality, sharing makes sense as hdfs and hbase nodes have different requirements... hdfs being heaviest on io (where hbase has no use), hbase heavy in memory, TTs vary greatly but most often heavy in cpu/io
{code}
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