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From Przemek Maciolek <pmacio...@gmail.com>
Subject Re: insert performance (1.2.8)
Date Tue, 20 Aug 2013 14:14:41 GMT
I had similar issues (sent a note on the list few weeks ago but nobody
responded). I think there's a serious bottleneck with using wide rows and
composite keys. I made a trivial benchmark, which you check here:
http://pastebin.com/qAcRcqbF  - it's written in cql-rb, but I ran the test
using astyanax/cql3 enabled and the results were the same.

In my case, inserting 10 000 entries took following time (seconds):

Using composite keys
Separetely: 12.892867
Batch: 189.731306

This means, I got 1000 rows/s when inserting them seperately and 52 (!!!)
when inserting them in a huge batch.

Using just partition key and wide row
Separetely: 11.292507
Batch: 0.093355

Again, 1000 rows/s when inserting them one by one. But batch obviously
improves thing and I easily got >10000 rows/s.

Anyone else with similar experiences?

Thanks,
Przemek


On Tue, Aug 20, 2013 at 4:04 PM, Nate McCall <nate@thelastpickle.com> wrote:

> John makes a good point re:prepared statements (I'd increase batch sizes
> again once you did this as well - separate, incremental runs of course so
> you can gauge the effect of each). That should take out some of the
> processing overhead of statement validation in the server (some - that load
> spike still seems high though).
>
> I'd actually be really interested as to what your results were after doing
> so - i've not tried any A/B testing here for prepared statements on
> inserts.
>
> Given your load is on the server, i'm not sure adding more async
> indirection on the client would buy you too much though.
>
> Also, at what RF and consistency level are you writing?
>
>
> On Tue, Aug 20, 2013 at 8:56 AM, Keith Freeman <8forty@gmail.com> wrote:
>
>>  Ok, I'll try prepared statements.   But while sending my statements
>> async might speed up my client, it wouldn't improve throughput on the
>> cassandra nodes would it?  They're running at pretty high loads and only
>> about 10% idle, so my concern is that they can't handle the data any
>> faster, so something's wrong on the server side.  I don't really think
>> there's anything on the client side that matters for this problem.
>>
>> Of course I know there are obvious h/w things I can do to improve server
>> performance: SSDs, more RAM, more cores, etc.  But I thought the servers I
>> have would be able to handle more rows/sec than say Mysql, since write
>> speed is supposed to be one of Cassandra's strengths.
>>
>>
>> On 08/19/2013 09:03 PM, John Sanda wrote:
>>
>> I'd suggest using prepared statements that you initialize at application
>> start up and switching to use Session.executeAsync coupled with Google
>> Guava Futures API to get better throughput on the client side.
>>
>>
>> On Mon, Aug 19, 2013 at 10:14 PM, Keith Freeman <8forty@gmail.com> wrote:
>>
>>>  Sure, I've tried different numbers for batches and threads, but
>>> generally I'm running 10-30 threads at a time on the client, each sending a
>>> batch of 100 insert statements in every call, using the
>>> QueryBuilder.batch() API from the latest datastax java driver, then calling
>>> the Session.execute() function (synchronous) on the Batch.
>>>
>>> I can't post my code, but my client does this on each iteration:
>>> -- divides up the set of inserts by the number of threads
>>> -- stores the current time
>>> -- tells all the threads to send their inserts
>>> -- then when they've all returned checks the elapsed time
>>>
>>> At about 2000 rows for each iteration, 20 threads with 100 inserts each
>>> finish in about 1 second.  For 4000 rows, 40 threads with 100 inserts each
>>> finish in about 1.5 - 2 seconds, and as I said all 3 cassandra nodes have a
>>> heavy CPU load while the client is hardly loaded.  I've tried with 10
>>> threads and more inserts per batch, or up to 60 threads with fewer, doesn't
>>> seem to make a lot of difference.
>>>
>>>
>>> On 08/19/2013 05:00 PM, Nate McCall wrote:
>>>
>>>  How big are the batch sizes? In other words, how many rows are you
>>> sending per insert operation?
>>>
>>>  Other than the above, not much else to suggest without seeing some
>>> example code (on pastebin, gist or similar, ideally).
>>>
>>> On Mon, Aug 19, 2013 at 5:49 PM, Keith Freeman <8forty@gmail.com> wrote:
>>>
>>>> I've got a 3-node cassandra cluster (16G/4-core VMs ESXi v5 on 2.5Ghz
>>>> machines not shared with any other VMs).  I'm inserting time-series data
>>>> into a single column-family using "wide rows" (timeuuids) and have a 3-part
>>>> partition key so my primary key is something like ((a, b, day),
>>>> in-time-uuid), x, y, z).
>>>>
>>>> My java client is feeding rows (about 1k of raw data size each) in
>>>> batches using multiple threads, and the fastest I can get it run reliably
>>>> is about 2000 rows/second.  Even at that speed, all 3 cassandra nodes are
>>>> very CPU bound, with loads of 6-9 each (and the client machine is hardly
>>>> breaking a sweat).  I've tried turning off compression in my table which
>>>> reduced the loads slightly but not much.  There are no other updates or
>>>> reads occurring, except the datastax opscenter.
>>>>
>>>> I was expecting to be able to insert at least 10k rows/second with this
>>>> configuration, and after a lot of reading of docs, blogs, and google, can't
>>>> really figure out what's slowing my client down.  When I increase the
>>>> insert speed of my client beyond 2000/second, the server responses are just
>>>> too slow and the client falls behind.  I had a single-node Mysql database
>>>> that can handle 10k of these data rows/second, so I really feel like I'm
>>>> missing something in Cassandra.  Any ideas?
>>>>
>>>>
>>>
>>>
>>
>>
>>  --
>>
>> - John
>>
>>
>>
>

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