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From "jess canabou (JIRA)" <>
Subject [jira] [Commented] (SOLR-2218) Performance of start= and rows= parameters are exponentially slow with large data sets
Date Tue, 14 Jun 2011 07:04:47 GMT


jess canabou commented on SOLR-2218:

Hi all

I'm a bit confused by this thread, but think I have the same or almost same issue. I'm searching
on a document with over 7000000 entries. I'm using the start and rows parameters (querying
30000 recs at a time), and notice the query times getting increasingly large, the further
into the document I get. Unlike Bill, I do not care about scores or relevancy, and am having
difficulty understanding whether the docid is a suitable solution to my problem. Is there
something I can simply tack onto the end of my query to help speed up these query times? From
what I understand, it's not necessary for me to be sorting all the rows before the chunk of
data I'm querying on
My query looks as below.
of fields>

Any help would be greatly appreciated :)

> Performance of start= and rows= parameters are exponentially slow with large data sets
> --------------------------------------------------------------------------------------
>                 Key: SOLR-2218
>                 URL:
>             Project: Solr
>          Issue Type: Improvement
>          Components: Build
>    Affects Versions: 1.4.1
>            Reporter: Bill Bell
> With large data sets, > 10M rows.
> Setting start=<large number> and rows=<large numbers> is slow, and gets slower
the farther you get from start=0 with a complex query. Random also makes this slower.
> Would like to somehow make this performance faster for looping through large data sets.
It would be nice if we could pass a pointer to the result set to loop, or support very large
> Something like:
> rows=1000
> start=0
> spointer=string_my_query_1
> Then within interval (like 5 mins) I can reference this loop:
> Something like:
> rows=1000
> start=1000
> spointer=string_my_query_1
> What do you think? Since the data is too great the cache is not helping.

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