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From Todd Lipcon <t...@cloudera.com>
Subject Re: Exponential performance decay when inserting large number of blocks
Date Thu, 14 Jan 2010 03:53:00 GMT
On Wed, Jan 13, 2010 at 6:59 PM, Eric Sammer <eric@lifeless.net> wrote:

> On 1/13/10 8:12 PM, Zlatin.Balevsky@barclayscapital.com wrote:
> > Alex, Dhruba
> >
> > I repeated the experiment increasing the block size to 32k.  Still doing
> > 8 inserts in parallel, file size now is 512 MB; 11 datanodes.  I was
> > also running iostat on one of the datanodes.  Did not notice anything
> > that would explain an exponential slowdown.  There was more activity
> > while the inserts were active but far from the limits of the disk system.
> While creating many blocks, could it be that the replication pipe lining
> is eating up the available handler threads on the data nodes? By
> increasing the block size you would see better performance because the
> system spends more time writing data to local disk and less time dealing
> with things like replication "overhead." At a small block size, I could
> imagine you're artificially creating a situation where you saturate the
> default size configured thread pools or something weird like that.
> If you're doing 8 inserts in parallel from one machine with 11 nodes
> this seems unlikely, but it might be worth looking into. The question is
> if testing with an artificially small block size like this is even a
> viable test. At some point the overhead of talking to the name node,
> selecting data nodes for a block, and setting up replication pipe lines
> could become some abnormally high percentage of the run time.
The concern isn't why the insertion is slow, but rather why the scaling
curve looks the way it does. Looking at the data, it looks like the
insertion rate (blocks per second) is actually related as 1/n where N is the
number of blocks. Attaching another graph of the same data which I think is
a little clearer to read.

> Also, I wonder if the cluster is trying to rebalance blocks toward the
> end of your runtime (if the balancer daemon is running) and this is
> causing additional shuffling of data.

That's certainly one possibility.

Zlatin: here's a test to try: after the FS is full with 400,000 blocks, let
the cluster sit for a few hours, then come back and start another insertion.
Is the rate slow, or does it return to the fast starting speed?


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