Riak maximum throughput

Bryan Fink bryan at basho.com
Thu Feb 11 21:01:28 EST 2010


On Thu, Feb 11, 2010 at 12:11 PM, LKolin <LKolin at weather.com> wrote:
> We’re investigating Riak as a means of persisting some data in a very
> read-heavy environment. Part of this process is determining the maximum
> number of requests a second that a Riak instance can handle, and I’ve
> created a simple Junit test to hammer the box with multiple worker threads
> that do reads, writes and deletes. I’ve found that around 8 concurrent
> reader threads, the instance tops out at 950-975 requests a second (these
> are very small JSON objects with a single value in them), on a 4-core 3Ghz
> Xeon running SuSE x64. 4GB of RAM.
>
> I seem to have pegged the Riak box, since CPU utilization across all 4 cores
> is around 90% user, 5-7% kernel and about 3-5% idle. Nothing else on the box
> is doing anything, and there’s around 1+ GB of physical RAM available. No
> swap file usage. I tried different back-end storage types, but ets and dets
> seemed about the same (??) and fs was noticeably slower.  Does 1000 requests
> a second seem like a reasonable upper-end, or have I missed something
> obvious, tuning-wise? I’m somewhat new to this.
>
> Cheers!
>
> Luke


Hi, Luke.  Out of the box, 1000 requests/second on a single node
doesn't sound that out of line to me.  But, there are quite a few
knobs to play with.  I'll list a few here, as well as some questions.
Please feel free to respond here, or to our internal, basho-only list,
riak at basho.com.

- You said you're using a JUnit test suite.  Is it running on the same
machine as Riak?  On the same switch as the machine running Riak?
We've built our own benchmarking, if you're interested in having a
look at it.

- I assume you're using one of the HTTP interfaces: is it /jiak or
/raw?  We're planning to deprecate /jiak as it's not as efficient, and
doesn't provide much other benefit over /raw.

- Did you happen to try the innostore backend
(http://hg.basho.com/innostore)?  We've found that one to be the
fastest and most predictable in the large/heavy use case.

- How big was your total dataset (# of documents)?  How random were
your accesses?  What percentage of your requests were gets vs. puts
vs. deletes?

- Are you using the standard configuration, or have you tweaked
anything, like ring_creation_size?

- Standard N-value (3) for all data?

- Are you sure you obeyed all guidance on X-Riak-Vclock and
X-Riak-ClientId headers?  Omitting vector clock or client-id headers
can cause vector clocks to grow very large, inflating the size of the
data being pushed around.

Please get in touch any way you feel comfortable, and we'll be happy
to give you a hand figuring out if there's a way to improve your
performance.

-Bryan




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