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From Erick Erickson <erickerick...@gmail.com>
Subject Re: Solr performance tuning - disk i/o?
Date Fri, 03 Jun 2011 20:44:56 GMT
Quick impressions:

The faceting is usually best done on fields that don't have lots of unique
values for three reasons:
1> It's questionable how much use to the user to have a gazillion facets.
     In the case of a unique field per document, in fact, it's useless.
2> resource requirements go up as a function of the number of unique
     terms. This is true for faceting and sorting.
3> warmup times grow the more terms have to be read into memory.


Glancing at your warmup stuff, things like publishDate, authorStr and maybe
callnumber-first are questionable. publishDate depends on how coarse the
resolution is. If it's by day, that's not really much use. authorStr.. How many
authors have more than one publication? Would this be better served by some
kind of autosuggest rather than facets? callnumber-first... I don't
really know, but
if it's unique per document it's probably not something the user would
find useful
as a facet.

The admin page will help you determine the number of unique terms per field,
which may guide you whether or not to continue to facet on these fields.

As Otis said, doing a sort on the fields during warmup will also help.

Watch your polling interval for any slaves in relation to the warmup times.
If your polling interval is shorter than the warmup times, you run a risk of
"runaway warmups".

As you've figured out, measuring responses to the first few queries doesn't
always measure what you really need <G>..

I don't have the pages handy, but autowarming is a good topic to understand,
so you might spend some time tracking it down.

Best
Erick

On Fri, Jun 3, 2011 at 11:21 AM, Demian Katz <demian.katz@villanova.edu> wrote:
> Thanks to you and Otis for the suggestions!  Some more information:
>
> - Based on the Solr stats page, my caches seem to be working pretty well (few or no evictions,
hit rates in the 75-80% range).
> - VuFind is actually doing two Solr queries per search (one initial search followed by
a supplemental spell check search -- I believe this is necessary because VuFind has two separate
spelling indexes, one for shingled terms and one for single words).  That is probably exaggerating
the problem, though based on searches with debugQuery on, it looks like it's always the initial
search (rather than the supplemental spelling search) that's consuming the bulk of the time.
> - enableLazyFieldLoading is set to true.
> - I'm retrieving 20 documents per page.
> - My JVM settings: -server -Xloggc:/usr/local/vufind/solr/jetty/logs/gc.log -Xms4096m
-Xmx4096m -XX:+UseParallelGC -XX:+UseParallelOldGC -XX:NewRatio=5
>
> It appears that a large portion of my problem had to do with autowarming, a topic that
I've never had a strong grasp on, though perhaps I'm finally learning (any recommended primer
links would be welcome!).  I did have some autowarming settings in solrconfig.xml (an arbitrary
search for a bunch of random keywords in the newSearcher and firstSearcher events, plus autowarmCount
settings on all of my caches).  However, when I looked at the debugQuery output, I noticed
that a huge amount of time was being wasted loading facets on the first search after restarting
Solr, so I changed my newSearcher and firstSearcher events to this:
>
>      <arr name="queries">
>        <lst>
>          <str name="q">*:*</str>
>          <str name="start">0</str>
>          <str name="rows">10</str>
>          <str name="facet">true</str>
>          <str name="facet.mincount">1</str>
>          <str name="facet.field">collection</str>
>          <str name="facet.field">format</str>
>          <str name="facet.field">publishDate</str>
>          <str name="facet.field">callnumber-first</str>
>          <str name="facet.field">topic_facet</str>
>          <str name="facet.field">authorStr</str>
>          <str name="facet.field">language</str>
>          <str name="facet.field">genre_facet</str>
>          <str name="facet.field">era_facet</str>
>          <str name="facet.field">geographic_facet</str>
>        </lst>
>      </arr>
>
> Overall performance has now increased dramatically, and now the biggest bottleneck in
the debug output seems to be the shingle spell checking!
>
> Any other suggestions are welcome, since I suspect there's still room to squeeze more
performance out of the system, and I'm still not sure I'm making the most of autowarming...
 but this seems like a big step in the right direction.  Thanks again for the help!
>
> - Demian
>
>> -----Original Message-----
>> From: Erick Erickson [mailto:erickerickson@gmail.com]
>> Sent: Friday, June 03, 2011 9:41 AM
>> To: solr-user@lucene.apache.org
>> Subject: Re: Solr performance tuning - disk i/o?
>>
>> This doesn't seem right. Here's a couple of things to try:
>> 1> attach &debugQuery=on to your long-running queries. The QTime
>> returned
>>      is the time taken to search, NOT including the time to load the
>> docs. That'll
>>      help pinpoint whether the problem is the search itself, or
>> assembling the
>>      documents.
>> 2> Are you autowarming? If so, be sure it's actually done before
>> querying.
>> 3> Measure queries after the first few, particularly if you're sorting
>> or
>>      faceting.
>> 4> What are your JVM settings? How much memory do you have?
>> 5> is <enableLazyFieldLoading> set to true in your solrconfig.xml?
>> 6> How many docs are you returning?
>>
>>
>> There's more, but that'll do for a start.... Let us know if you gather
>> more data
>> and it's still slow.
>>
>> Best
>> Erick
>>
>> On Fri, Jun 3, 2011 at 8:44 AM, Demian Katz <demian.katz@villanova.edu>
>> wrote:
>> > Hello,
>> >
>> > I'm trying to move a VuFind installation from an ailing physical
>> server into a virtualized environment, and I'm running into performance
>> problems.  VuFind is a Solr 1.4.1-based application with fairly large
>> and complex records (many stored fields, many words per record).  My
>> particular installation contains about a million records in the index,
>> with a total index size around 6GB.
>> >
>> > The virtual environment has more RAM and better CPUs than the old
>> physical box, and I am satisfied that my Java environment is well-
>> tuned.  My index is optimized.  Searches that hit the cache respond
>> very well.  The problem is that non-cached searches are very slow - the
>> more keywords I add, the slower they get, to the point of taking 6-12
>> seconds to come back with results on a quiet box and well over a minute
>> under stress testing.  (The old box still took a while for equivalent
>> searches, but it was about twice as fast as the new one).
>> >
>> > My gut feeling is that disk access reading the index is the
>> bottleneck here, but I know little about the specifics of Solr's
>> internals, so it's entirely possible that my gut is wrong.  Outside
>> testing does show that the the virtual environment's disk performance
>> is not as good as the old physical server, especially when multiple
>> processes are trying to access the same file simultaneously.
>> >
>> > So, two basic questions:
>> >
>> >
>> > 1.)    Would you agree that I'm dealing with a disk bottleneck, or
>> are there some other factors I should be considering?  Any good
>> diagnostics I should be looking at?
>> >
>> > 2.)    If the problem is disk access, is there anything I can tune on
>> the Solr side to alleviate the problems?
>> >
>> > Thanks,
>> > Demian
>> >
>

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