Hi Gary,

I think it will be tricky to translate read rates to qps based on doc
sizes. If I¹m correct, transfer between D and E is compressed tree data.
Reading from disk is even more complex, since the tree data is completely
dissected into strings and structural info. I¹m afraid you are best off
literally keeping count somehow, or for instance analyzing access logs..

Cheers,
Geert

On 6/16/16, 4:25 AM, "general-boun...@developer.marklogic.com on behalf of
Gary Russo" <general-boun...@developer.marklogic.com on behalf of
garyru...@hotmail.com> wrote:

>I'd like to measure the read query capacity of an existing cluster using
>the Monitoring History Tool.
>
>My objective is to determine the average "Read Queries Per Second" during
>a spurt of query activity.
>
>My plan is to use the "Query Read Rate" from the Disk I/O graph.
>
>Here's the info: 
>http://docs.marklogic.com/guide/monitoring/history#id_21175
>
>I ran some JMeter scripts to measure the average request response time
>which
>was .74 seconds.
>
>During this time, I saw the following Disk I/O and Memory I/O metrics.
>
>Disk I/O
>Query Read Rate  00.03 MB/sec
>Merge Read Rate  28.00 MB/sec
>
>Memory I/O
>Page-In  Rate: 22,436.3 pages/sec
>Page-Out Rate: 19,345.8 pages/sec
>
>How does this translate to Queries Per Second (QPS)?
>
>The average document (fragment) size is 4 KB (4096 bytes).
>
>The Query Read Rate is .03 MB/sec (30720 bytes/sec)
>
>Since each query returns a 4K document then 30720 divided by 4096 is 7.5
>QPS.
>
>If each query returned just a 1024 byte search snippet then it would be 30
>QPS.
>
>So I assume my answer QPS rates are:
> -  7.5 QPS when returning documents
> - 30.0 QPS when returning search snippets
>
>
>Please let me know if I'm missing something.
>
>
>
>Gary Russo
>NoSQL Architect and Developer
>http://garyrusso.wordpress.com
>http://twitter.com/garyprusso
>
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