Magma read performance

[Chris Muller]

It is not a real world magma application.  As I said, it was just a
internal benchmark test.

On Fri, Nov 26, 2010 at 1:35 PM, Facundo Vozzi <facundov79 at gmail.com> wrote:
> Thanks you Chris,
> good to know that there is a real world magma application with 24 GB of
> size.
> See you,
> Facu
> On Fri, Nov 26, 2010 at 3:43 PM, Chris Muller <asqueaker at gmail.com> wrote:
>>
>> It's a proprietary data-aggregation tool that permutes every
>> combination of data-attributes of an input-source at multiple levels.
>> Even small inputs into the system can lead to very large output
>> graphs.  It's a signature test-application for Magma; building and
>> accessing a fairly large and complex data-structure and something I
>> think would be very difficult to do, at least abstractly, with an
>> RDBMS..
>>
>> On Thu, Nov 25, 2010 at 6:56 AM, Facundo Vozzi <facundov79 at gmail.com>
>> wrote:
>> > Hi Chris,
>> > what kind of application is that? At work I'm working on a ten years old
>> > production system with Oracle DBMS and it's 1 GB of size.
>> >
>> > Thanks for share your analysis again,
>> > Facu
>> > On Wed, Nov 24, 2010 at 2:38 PM, Chris Muller <ma.chris.m at gmail.com>
>> > wrote:
>> >>
>> >> There has been interest in Magma's read and query performance lately,
>> >> so I thought I would share results of a recent benchmark test.
>> >>
>> >> It's an actual application which does very heavy reading and writing
>> >> to a Magma repository.  This test was 24GB of repository work, over
>> >> two days.  My goal was to determine, once the persistent model becomes
>> >> many times the size of RAM and HD access appeared to become the
>> >> limiting factor:
>> >>
>> >>  - how fast is Magma, in terms of "objects per second" and in
>> >> "kilobytes per second"?
>> >>  - how fast is this relative to the speed when the repository was
>> >> empty?
>> >>
>> >> Conclusion:
>> >>
>> >>  - Magma started at 4K objects per second (empty repository), 282K per
>> >> second.
>> >>  - Finished with 2.3K objects per second (6GB repository), 750K per
>> >> second.
>> >>  - Memory consumption by the image never exceeded 300MB.
>> >>
>> >> It is important to note, these times are from the client MagmaSession
>> >> point-of-view, including the full server roundtrip plus
>> >> materialization.  Also, as can be seen from the attached data, there
>> >> were many requests which only brought back one or two objects which,
>> >> while dramatically lowering the overall reported throughput, is
>> >> actually a real-world scenario for applications.
>> >>
>> >> Verbose description:
>> >>
>> >> When the test first started the repository was tiny, and there were
>> >> only ~4K server requests during a 5-minute monitored period.  The
>> >> total number of objects read across all ~4K requests was ~17M for an
>> >> average throughput of 4K objects per second (ops).  As the model grew
>> >> in size and complexity, more and more objects during the 5-minute
>> >> monitored intervals were required to perform application-posting of
>> >> the same number of input records; doubling to ~8K server requests
>> >> during a 5-minute period, however only a few more objects brought back
>> >> (total 21M), for an average of 2500 ops.  32 hours after that, the
>> >> rate of reads dropped to about 2300 ops.  This is due to two factors:
>> >>
>> >>  - the objects were larger (e.g., more pointers to other objects)
>> >>  - they were less clustered (having been replaced with objects which
>> >> could not be co-located with the original object)
>> >>
>> >>
>> >>
>> >> The fact that objects got bigger (e.g., more pointers to other
>> >> objects) is corroborated by another stat, "the number of *bytes* per
>> >> second" read off the HD in order to access those objects.  Initially,
>> >> when the test first started, there were about 4K *requests* for
>> >> objects in one of the first five-minute periods, which were read at a
>> >> rate of 282K per second.  24 hours later, there were only 2 times as
>> >> many requests for objects, but were read-and-materialized at a rate of
>> >> 750K bytes / second.
>> >>
>> >>
>> >>  - Chris
>> >>
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