incubator-cassandra-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Mike Malone <m...@simplegeo.com>
Subject Re: Cassandra Write Performance, CPU usage
Date Fri, 11 Jun 2010 16:20:06 GMT
Jonathan, while I agree with you re: this being an unusual load for the
system, it is interesting that he's found at least one use-case where
Cassandra is CPU-bound, not IO-bound. I'd definitely be interested in
learning what his critical path is and seeing if there's some low-hanging
fruit that may improve performance overall. I have also noticed very high
CPU usage during high write loads and have wondered whether write speed and
throughput could be improved by improving some of the algorithms along that
path.

I'm nowhere near being an expert on the whole Java ecosystem, but I've had
good luck with the `jvisualvm` tool that comes with Java SE 6. It's a nice
lightweight CPU and memory profiling tool that can attach to a running
process like Cassandra and dump stats in real time.

Mike

On Thu, Jun 10, 2010 at 7:39 PM, Jonathan Shook <jshook@gmail.com> wrote:

> You are testing Cassandra in a way that it was not designed to be used.
> Bandwidth to disk is not a meaningful example for nearly anything
> except for filesystem benchmarking and things very nearly the same as
> filesystem benchmarking.
> Unless the usage patterns of your application match your test data,
> there is not a good reason to expect a strong correlation between this
> test and actual performance.
>
> Cassandra is not simply shuffling data through IO when you write.
> There are calculations that have to be done as writes filter their way
> through various stages of processing. The point of this is to minimize
> the overall effort Cassandra has to make in order to retrieve the data
> again. One example would be bloom filters. Each column that is written
> requires bloom filter processing and potentially auxiliary IO. Some of
> these steps are allowed to happen in the background, but if you try,
> you can cause them to stack up on top of the available CPU and memory
> resources.
>
> In such a case (continuous bulk writes), you are causing all of these
> costs to be taken in more of a synchronous (not delayed) fashion. You
> are not allowing the background processing that helps reduce client
> blocking (by deferring some processing) to do its magic.
>
>
>
> On Thu, Jun 10, 2010 at 7:42 PM, Rishi Bhardwaj <khichrishi@yahoo.com>
> wrote:
> > Hi
> > I am investigating Cassandra write performance and see very heavy CPU
> usage
> > from Cassandra. I have a single node Cassandra instance running on a dual
> > core (2.66 Ghz Intel ) Ubuntu 9.10 server. The writes to Cassandra are
> being
> > generated from the same server using BatchMutate(). The client makes
> exactly
> > one RPC call at a time to Cassandra. Each BatchMutate() RPC contains 2 MB
> of
> > data and once it is acknowledged by Cassandra, the next RPC is done.
> > Cassandra has two separate disks, one for commitlog with a sequential b/w
> of
> > 130MBps and the other a solid state disk for data with b/w of 90MBps.
> Tuning
> > various parameters, I observe that I am able to attain a maximum write
> > performance of about 45 to 50 MBps from Cassandra. I see that the
> Cassandra
> > java process consistently uses 100% to 150% of CPU resources (as shown by
> > top) during the entire write operation. Also, iostat clearly shows that
> the
> > max disk bandwidth is not reached anytime during the write operation,
> every
> > now and then the i/o activity on "commitlog" disk and the data disk spike
> > but it is never consistently maintained by cassandra close to their
> peak. I
> > would imagine that the CPU is probably the bottleneck here. Does anyone
> have
> > any idea why Cassandra beats the heck out of the CPU here? Any
> suggestions
> > on how to go about finding the exact bottleneck here?
> > Some more information about the writes: I have 2 column families, the
> data
> > though is mostly written in one column family with column sizes of around
> > 32k and each row having around 256 or 512 columns. I would really
> appreciate
> > any help here.
> > Thanks,
> > Rishi
> >
> >
>

Mime
View raw message