Hi Otis,

Sorry I missed your reply, and thanks for trying to find a similar report.

Wondering if I should file a Jira issue? That might get more attention :)

-- Ken

On Jul 5, 2013, at 1:05pm, Otis Gospodnetic wrote:

> Hi Ken,
> 
> Uh, I left this email until now hoping I could find you a reference to
> similar reports, but I can't find them now.  I am quite sure I saw
> somebody with a similar report within the last month.  Plus, several
> people have reported issues with performance dropping when they went
> from 3.x to 4.x and maaaaaybe this is why.
> 
> Otis
> --
> Solr & ElasticSearch Support -- http://sematext.com/
> Performance Monitoring -- http://sematext.com/spm
> 
> 
> 
> On Tue, Jul 2, 2013 at 3:01 PM, Ken Krugler <kkrugler_li...@transpac.com> 
> wrote:
>> Hi all,
>> 
>> After upgrading from Solr 3.5 to 4.2.1, I noticed our filterCache hit ratio 
>> had dropped significantly.
>> 
>> Previously it was at 95+%, but now it's < 50%.
>> 
>> I enabled recording 100 entries for debugging, and in looking at them it 
>> seems that edismax (and faceting) is creating entries for me.
>> 
>> This is in a sharded setup, so it's a distributed search.
>> 
>> If I do a search for the string "bogus text" using edismax on two fields, I 
>> get an entry in each of the shard's filter caches that looks like:
>> 
>> item_+(((field1:bogus | field2:bogu) (field1:text | field2:text))~2):
>> 
>> Is this expected?
>> 
>> I have a similar situation happening during faceted search, even though my 
>> fields are single-value/untokenized strings, and I'm not using the enum 
>> facet method.
>> 
>> But I'll get many, many entries in the filterCache for facet values, and 
>> they all look like "item_<facet field>:<facet value>:"
>> 
>> The net result of the above is that even with a very big filterCache size of 
>> 2K, the hit ratio is still only 60%.
>> 
>> Thanks for any insights,
>> 
>> -- Ken

--------------------------
Ken Krugler
+1 530-210-6378
http://www.scaleunlimited.com
custom big data solutions & training
Hadoop, Cascading, Cassandra & Solr





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