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From John Plevyak <>
Subject Re: Benchmarking ATS
Date Fri, 10 Jun 2011 18:03:42 GMT
There is also a question of RAM hit VS non-RAM hit.  RAM hits incur no
Miss writes are aggregated so misses are constrained by disk write
Non-RAM hits require seeks (approx 1 seek / MB) and that is what typically
performance for those operations.

Unless you have mostly RAM hits, a large number of disks or very little CPU
will probably be disk or network constrained.

I use a synthetic server with new URLs for misses and select from a "hotset"
for hits which is either sized to fit in RAM not depending on the type of

More sophisticated techniques often use a Zipf distribution, although there
is some controversy over how well that models actual traffic.   You could
also use logs to build a synthetic request stream which better models your
traffic, but then network delay issues and peculiarities (dropped packets,
MTU, etc.)  could be modeled as well and you are down the rabbit hole.


On Fri, Jun 10, 2011 at 10:17 AM, sridhar basam <> wrote:

> On Fri, Jun 10, 2011 at 9:54 AM, Mike Partridge <>wrote:
>> Is there an easy method to artificially vary the cache hit/miss ratio that
>> people would recommend.  I am currently just generating more random content
>> then can be cached by ATS?
>> This is what I was in process of doing, but was curious if there was a
>> better method others may have used.  I am trying to do this to benchmark ATS
>> at different cache hit/miss ratios.
> Hit/miss rates are determined by cache size and the ratio of requests
> incoming that are cachable. Using a combination of the 2, should you be able
> to vary the cache hit/miss rate.
>  Sridhar

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