openstack team mailing list archive

[Curtis Carter <curtis.carter@xxxxxxxxxxxxx>]

nice.

On Mar 8, 2011, at 1:14 PM, Eric Day wrote:

> Hi Curtis,
> 
> On Tue, Mar 08, 2011 at 04:31:59PM +0000, Curtis Carter wrote:
>> Couple of questions.
>> Where did you come up with 300 bytes per message for ets?
> 
> Raw message = key(16) + ttl(8) + hide(8) + body(100) = 132 bytes
> 
> I inserted the raw message data as the tuple {key/binary, ttl/integer,
> hide/integer, body/binary} in ets (5 million) and inspected the
> memory usage. It lines up with what should be used with the given
> type overheads in:
> 
> http://www.erlang.org/doc/efficiency_guide/advanced.html#id66654
> 
> It was very fast, but it did come with that overhead.
> 
> As far as queue storage, we won't be using a traditional queue
> structure alone. We need a few other indexes into the data store for
> efficient operations, not just inspecting beginning of the queue. For
> example, TTL and hide properties require timestamp-based indexes into
> the queue as well, which are probably best done with a secondary heap
> index or btree. We'll also need insert order and message ID indexed.
> 
>> When you say 2 threads for Erlang what do you mean?  Do you mean 2 schedulers and/or 2 run queues, Erlang processes, or Erlang vms.  
> 
> Sorry, two scheduler threads in one vm (os kernel threads). For C++
> this was also 2 threads with PTHREAD_SCOPE_SYSTEM. The main point
> is that all connections (erlang processes, eventlet green threads,
> state structures in C++ event loop) were running on two cores. For
> Python this was just a os.fork() after creating the listening socket.
> 
>> I wrote a basic queue using the queue module(double ended FIFO) that was handling around 526k a second with 100 clients on an old core2 duo laptop.  
>> 200000 8 byte messages per client (I do not know how the queue module is implemented)
>> 100 clients/queues
>> Was very unscientific in the front seat of my car while waiting on someone. NO HTTP
> 
> The main thing I was trying to test was language overhead, especially
> with HTTP parsing. For the raw echo test, erlang and python are pretty
> even. Python WSGI does have some overhead (just as Erlang modules
> like webmachine did), but that may be solved with an implementation
> optimization (like I did by not using webmachine).
> 
>> I know very apple/oranges here.  From what I've seen in the past Erlang does not pass other http servers until you hit a large amount of concurrent requests.  
> See: http://oddments.org/?p=494
> 
> Eventlet came in a bit behind C++ for the larger payload (512k data
> for each of the 32k connections), but it held up quite well. Eventlet
> was only running with a single process too, so I imagine with two
> processes the time would improve. In a later test I used Erlang and
> it came in between the C++ 2-thread test and Eventlet single thread
> (as you would expect from my other tests).
> 
> -Eric
> 
>> On Mar 7, 2011, at 3:32 PM, Eric Day wrote:
>> 
>>> I ran the tests again to verify:
>>> 
>>> 500k requests - 10 processes each running 50k requests.
>>> 
>>>               time req/s     cs us sy id
>>> 2 thread/proc
>>> echo c++      7.19 69541 142182 23 77  0
>>> echo erlang   9.53 52465 105871 39 61  0
>>> echo python   9.58 52192 108420 42 58  0
>>> 2 thread/proc
>>> wsgi python  58.74 8512   18132 86 14  0
>>> webob python 78.75 6349   13678 89 11  0
>>> webmachine*  63.50 7874   11834 89 11  0
>>> openstack    20.48 24414  49897 68 32  0
>>> 
>>> cs/us/sys/id are from vmstat while running the tests.
>>> 
>>> * webmachine degrades over time with long-lived, multi-request
>>> connections. This number was estimated with 1000 requests per
>>> connection. At 50k requests per connection, the rate dropped to
>>> 2582 req/s.
>>> 
>>> As you can see I was able to reproduce the same numbers. If
>>> anyone would like to do the same, you can grab lp:burrow for the
>>> "openstack" Erlang application (compile and run ./start), webmachine
>>> is at https://github.com/basho/webmachine (you need to create a demo
>>> app and make sure you set nodelay for the socket options), and I've
>>> attached the python server and client (start 10 client processes when
>>> testing). Find me on irc (eday in #openstack) if you have questions.
>>> 
>>> If we hit performance issues with this type of application, we'll
>>> probably hit them around the same time with both Erlang and Python
>>> (then we'll look to C/C++). Since most OpenStack developers are a lot
>>> more comfortable with Python, I suggest we make the switch. Please
>>> response with thoughts on this. I'll add a sqlite backend to the
>>> Python prototype and run some performance tests against that to see
>>> if any red flags come up.
>>> 
>>> -Eric
>>> 
>>> On Sat, Mar 05, 2011 at 10:39:18PM -0700, ksankar@xxxxxxxxxxxxxx wrote:
>>>>  Eric,
>>>>     Thanks for your experimentation and analysis. Somewhat illustrates the
>>>>  point about premature optimization. First cut, have to agree with you and
>>>>  conclude that python implementation is effective, overall. As you said,if
>>>>  we find performance bottlenecks, especially as the payload size increases
>>>>  (as well as if we require any complex processing at the http server layer)
>>>>  we can optimize specific areas.
>>>>      Just for sure, might be better for someone else to recheck. That way
>>>>  we have done our due diligence.
>>>>  Cheers
>>>>  <k/>
>>>> 
>>>>    -------- Original Message --------
>>>>    Subject: [Openstack] Queue Service Implementation Thoughts
>>>>    From: Eric Day <eday@xxxxxxxxxxxx>
>>>>    Date: Sat, March 05, 2011 4:07 pm
>>>>    To: openstack@xxxxxxxxxxxxxxxxxxx
>>>> 
>>>>    Hi everyone,
>>>> 
>>>>    When deciding to move forward with Erlang, I first tried out the Erlang
>>>>    REST framework webmachine (it is built on top of mochiweb and used
>>>>    by projects like Riak). After some performance testing, I decided to
>>>>    write a simple wrapper over the HTTP packet parsing built into Erlang
>>>>    (also used by mochiweb/webmachine) to see if I could make things a
>>>>    bit more efficient. Here are the results:
>>>> 
>>>>    Erlang (2 threads)
>>>>    echo - 58823 reqs/sec
>>>>    webmachine - 7782 reqs/sec
>>>>    openstack - 24154 reqs/sec
>>>> 
>>>>    The test consists of four concurrent connections focused on packet
>>>>    parsing speed and framework overhead. A simple echo test was also
>>>>    done for a baseline (no parsing, just a simple recv/send loop). As
>>>>    you can see, the simple request/response wrapper I wrote did get some
>>>>    gains, although it's a little more hands-on to use (looks more like
>>>>    wsgi+webob in python).
>>>> 
>>>>    I decided to run the same tests against Python just for comparison. I
>>>>    ran echo, wsgi, and wsgi+webob decorators all using eventlet. I ran
>>>>    both single process and two process in order to compare with Erlang
>>>>    which was running with two threads.
>>>> 
>>>>    Python (eventlet)
>>>>    echo (1 proc) - 17857 reqs/sec
>>>>    echo (2 proc) - 52631 reqs/sec
>>>>    wsgi (1 proc) - 4859 reqs/sec
>>>>    wsgi (2 proc) - 8695 reqs/sec
>>>>    wsgi webob (1 proc) - 3430 reqs/sec
>>>>    wsgi webob (2 proc) - 6142 reqs/sec
>>>> 
>>>>    As you can see, the two process Python echo server was not too far
>>>>    behind the two thread Erlang echo server. The wsgi overhead was
>>>>    significant, especially with the webob decorators/objects. It was
>>>>    still on par with webmachine, but a factor of three less than my
>>>>    simple request/response wrapper.
>>>> 
>>>>    A multi-process python server does have the drawback of not being
>>>>    able to share resources between processes unless incurring the
>>>>    overhead of IPC. When thinking about a horizontally scalable service,
>>>>    where scaling-out is much more important than scaling-up, I think
>>>>    this becomes much less of a factor. Regardless of language choice,
>>>>    we will need a proxy to efficiently hash to a set of queue servers in
>>>>    any large deployment (or the clients will hash), but if that set is a
>>>>    larger number of single-process python servers (some running on the
>>>>    same machine) instead of a smaller number of multi-threaded Erlang
>>>>    servers, I don't think it will make too much of a difference (each
>>>>    proxy server will need to maintain more connections). In previous
>>>>    queue service threads I was much more concerned about this and was
>>>>    leaning away from Python, but I think I may be coming around.
>>>> 
>>>>    Another aspect I took a look at is options for message storage. For
>>>>    the fast, in-memory, unreliable queue type, here are some numbers
>>>>    for options in Python and Erlang:
>>>> 
>>>>    Raw message = key(16) + ttl(8) + hide(8) + body(100) = 132 bytes
>>>>    Python list/dict - 248 bytes/msg (88% overhead)
>>>>    Python sqlite3 - 168 bytes/msg (27% overhead)
>>>>    Erlang ets - 300 bytes/msg (127% overhead)
>>>> 
>>>>    The example raw message has no surrounding data structure, so it is
>>>>    obviously never possible to get down to 132 bytes. As the body grows,
>>>>    the overhead becomes less significant since they all grow the same
>>>>    amount. The best Python option is probably an in-memory sqlite table,
>>>>    which is also an option for disk-based storage as well.
>>>> 
>>>>    For Erlang, ets is really the only efficient in-memory option (mnesia
>>>>    is built on ets if you're thinking of that), and also has a disk
>>>>    counterpart called dets. The overhead was definitely more than I was
>>>>    expecting and is less memory efficient than both Python options.
>>>> 
>>>>    As we start looking at other stores to use, there are certainly more
>>>>    DB drivers available for Python than Erlang (due to the fact that
>>>>    Python is more popular). We'll want to push most of the heavy lifting
>>>>    to the pluggable databases, which makes the binding language less of
>>>>    a concern as well.
>>>> 
>>>>    So, in conclusion, and going against my previous opinion, I'm starting
>>>>    to feel that the performance gains of Erlang are really not that
>>>>    significant compared to Python for this style of application. If
>>>>    we're talking about a factor of three (and possibly less if we can
>>>>    optimize the wsgi driver or not use wsgi), and consider the database
>>>>    driver options for queue storage, Python doesn't look so bad. We'll
>>>>    certainly have more of a developer community too.
>>>> 
>>>>    We may still need to write parts in C/C++ if limits can't be overcome,
>>>>    but that would probably be the case for Erlang or Python.
>>>> 
>>>>    What do folks think?
>>>> 
>>>>    -Eric
>>>> 
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>> 
>> 
>> 
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