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From Eli Collins <...@cloudera.com>
Subject Re: DataNode internal balancing, performance recommendations
Date Mon, 03 Jan 2011 17:07:17 GMT
Hey Jonathan,

There's an option (dfs.datanode.failed.volumes.tolerated, introduced
in HDFS-1161) that allows you to specify the number of volumes that
are allowed to fail before a datanode stops offering service.

There's an operational issue that still needs to be addressed
(HDFS-1158) that you should be aware of - the DN will still not start
if any of the volumes have failed, so to restart the DN you'll need
you'll need to either unconfigure the failed volumes or fix them. I'd
like to make DN startup respect the config value so it tolerates
failed volumes on startup as well.


On Sun, Jan 2, 2011 at 7:20 PM, Jonathan Disher <jdisher@parad.net> wrote:
> I see that there was a thread on this in December, but I can't retrieve it to reply properly,
oh well.
> So, I have a 30 node cluster (plus separate namenode, jobtracker, etc).  Each is a 12
disk machine - two mirrored 250GB OS disks, ten 1TB data disks in JBOD.  Original system
config was six 1TB data disks - we added the last four disks months later.  I'm sure you
can all guess, we have some interesting internal usage balancing issues on most of the nodes.
 To date, when individual disks get critically low on space (earlier this week I had a node
with six disks around 97% full, four around 70%), we've been pulling them from the cluster,
formatting the data disks, and sticking them back in (with a rebalance running to keep the
cluster in some semblance of order).
> Obviously if there was a better way to do this, I'd love to see it.  I see that there
are recommendations of killing the DataNode process and manually moving files, but my concern
is that the DataNode process will spend an enormous amount of time tracking down these moves
(currently around 820,000 blocks/node).  And it's not necessarily easy to automate, so there's
the danger of nuking blocks, and making the problems worse.  Are there alternatives to manual
moves (or more automated ways that exist)?  Or has my brute-force rebalance got the best
chance of success, albeit slowly?
> We are also building a new cluster - starting around 1.2PB raw, eventually growing to
around 5PB, for near-line storage of data.  Our storage nodes will probably be 4U systems
with 72 data disks each (yeah, good times).  The problem with this becomes obvious - with
the way Hadoop works today, if a disk fails, the datanode process chokes and dies when it
tries to write to it.  We've been told repeatedly that Hadoop doesn't perform well when it
operates on RAID arrays, but, to scale efffectively, we're going to have to do just that -
three 24 disk controllers in RAID-6 mode.  How bad is this going to be?  JBOD just doesn't
scale beyond a couple disks per machine, the failure rate will knock machines out of the cluster
too often (and at 60TB per node, rebalancing will take forever, even if I let it saturate
> I appreciate opinions and suggestions.  Thanks!
> -j

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