Re: Solr search performance
Hi Fred,
Thanks for the pointer! 'cursorMark' is a lot more performant alright,
though apparently it doesn't suit our use case.
I've written a loop function using OTP's httpc that reads each page, gets
the cursorMark and repeats, and it returns all 147 pages with consistent
times in the 40-60ms bracket which is an excellent improvement!
I would have been asking about the effort involved in making the protocol
buffers client support this, but instead our GUI guys insist that they need
to request a page number as sometimes they want to start in the middle of a
set of data.
So I'm almost back to square one.
Can you shed any light on the internal workings of SOLR that produce the
slow-down in my original question?
I'm hoping I can find a way to restructure my index data without having to
change the higher-level API's that I support.
Cheers,
//Sean.
On Mon, Sep 19, 2016 at 10:00 PM, Fred Dushin wrote:
> All great questions, Sean.
>
> A few things. First off, for result sets that are that large, you are
> probably going to want to use Solr cursor marks [1], which are supported in
> the current version of Solr we ship. Riak allows queries using cursor
> marks through the HTTP interface. At present, it does not support cursors
> using the protobuf API, due to some internal limitations of the server-side
> protobuf library, but we do hope to fix that in the future.
>
> Secondly, we have found sorting with distributed queries to be far more
> performant using Solr 4.10.4. Currently released versions of Riak use Solr
> 4.7, but as you can see on github [2], Solr 4.10.4 support has been merged
> into the develop-2.2 branch, and is in the pipeline for release. I can't
> say when the next version of Riak is that will ship with this version
> because of indeterminacy around bug triage, but it should not be too long.
>
> I would start to look at using cursor marks and measure their relative
> performance in your scenario. My guess is that you should see some
> improvement there.
>
> -Fred
>
> [1] https://cwiki.apache.org/confluence/display/solr/Pagination+of+Results
> [2] https://github.com/basho/yokozuna/commit/
> f64e19cef107d982082f5b95ed598da96fb419b0
>
>
> > On Sep 19, 2016, at 4:48 PM, sean mcevoy wrote:
> >
> > Hi All,
> >
> > We have an index with ~548,000 entries, ~14,000 of which match one of
> our queries.
> > We read these in a paginated search and the first page (of 100 hits)
> returns quickly in ~70ms.
> > This response time seems to increase exponentially as we walk through
> the pages:
> > the 4th page takes ~200ms,
> > the 8th page takes ~1200ms
> > the 12th page takes ~2100ms
> > the 16th page takes ~6100ms
> > the 20th page takes ~24000ms
> >
> > And by the time we're searching for the 22nd page it regularly times out
> at the default 60 seconds.
> >
> > I have a good unsderstanding of riak KV internals but absolutely nothing
> of Lucene which I think is what's most relevant here. If anyone in the know
> can point me towards any relevant resource or can explain what's happening
> I'd be much obliged :-)
> > As I would also be if anyone with experience of using Riak/Lucene can
> tell me:
> > - Is 500K a crazy number of entries to put into one index?
> > - Is 14K a crazy number of entries to expect to be returned?
> > - Are there any methods we can use to make the search time more constant
> across the full search?
> > I read one blog post on inlining but it was a bit old & not very obvious
> how to implement using riakc_pb_socket calls.
> >
> > And out of curiosity, do we not traverse the full range of hits for each
> page? I naively thought that because I'm sorting the returned values we'd
> have to get them all first and then sort, but the response times suggests
> otherwise. Does Lucene store the data sorted by each field just in case a
> query asks for it? Or what other magic is going on?
> >
> >
> > For the technical details, we use the "_yz_default" schema and all the
> fields stored are strings:
> > - entry_id_s: unique within the DB, the aim of the query is to gather a
> list of these
> > - type_s: has one of 2 values
> > - sub_category_id_s: in the query described above all 14K hits will
> match on this, in the DB of ~500K entries there are ~43K different values
> for this field, withe each category typically having 2-6 sub categories
> > - category_id_s: not matched in this query, in the DB of ~500K entries
> there are ~13K different values for this field
> > - status_s: has one of 2 values, in the query described baove all hits
> will have the value "active"
> > - user_id_s: unique within the DB but not matched in this query
> > - first_name_s: almost unique within the DB, this query will sort by
> this field
> > - last_name_s: almost unique within the DB, this query will sort by this
> field
> >
> > This search query looks like:
> > <<"sub_category_id_s:test_1 AND status_s:active AND
> type_s:sub_category">>
> >
> > Our options parameter has the sort directive:
> > {sort, <<"f
Re: Solr search performance
All great questions, Sean.
A few things. First off, for result sets that are that large, you are probably
going to want to use Solr cursor marks [1], which are supported in the current
version of Solr we ship. Riak allows queries using cursor marks through the
HTTP interface. At present, it does not support cursors using the protobuf
API, due to some internal limitations of the server-side protobuf library, but
we do hope to fix that in the future.
Secondly, we have found sorting with distributed queries to be far more
performant using Solr 4.10.4. Currently released versions of Riak use Solr
4.7, but as you can see on github [2], Solr 4.10.4 support has been merged into
the develop-2.2 branch, and is in the pipeline for release. I can't say when
the next version of Riak is that will ship with this version because of
indeterminacy around bug triage, but it should not be too long.
I would start to look at using cursor marks and measure their relative
performance in your scenario. My guess is that you should see some improvement
there.
-Fred
[1] https://cwiki.apache.org/confluence/display/solr/Pagination+of+Results
[2]
https://github.com/basho/yokozuna/commit/f64e19cef107d982082f5b95ed598da96fb419b0
> On Sep 19, 2016, at 4:48 PM, sean mcevoy wrote:
>
> Hi All,
>
> We have an index with ~548,000 entries, ~14,000 of which match one of our
> queries.
> We read these in a paginated search and the first page (of 100 hits) returns
> quickly in ~70ms.
> This response time seems to increase exponentially as we walk through the
> pages:
> the 4th page takes ~200ms,
> the 8th page takes ~1200ms
> the 12th page takes ~2100ms
> the 16th page takes ~6100ms
> the 20th page takes ~24000ms
>
> And by the time we're searching for the 22nd page it regularly times out at
> the default 60 seconds.
>
> I have a good unsderstanding of riak KV internals but absolutely nothing of
> Lucene which I think is what's most relevant here. If anyone in the know can
> point me towards any relevant resource or can explain what's happening I'd be
> much obliged :-)
> As I would also be if anyone with experience of using Riak/Lucene can tell me:
> - Is 500K a crazy number of entries to put into one index?
> - Is 14K a crazy number of entries to expect to be returned?
> - Are there any methods we can use to make the search time more constant
> across the full search?
> I read one blog post on inlining but it was a bit old & not very obvious how
> to implement using riakc_pb_socket calls.
>
> And out of curiosity, do we not traverse the full range of hits for each
> page? I naively thought that because I'm sorting the returned values we'd
> have to get them all first and then sort, but the response times suggests
> otherwise. Does Lucene store the data sorted by each field just in case a
> query asks for it? Or what other magic is going on?
>
>
> For the technical details, we use the "_yz_default" schema and all the fields
> stored are strings:
> - entry_id_s: unique within the DB, the aim of the query is to gather a list
> of these
> - type_s: has one of 2 values
> - sub_category_id_s: in the query described above all 14K hits will match on
> this, in the DB of ~500K entries there are ~43K different values for this
> field, withe each category typically having 2-6 sub categories
> - category_id_s: not matched in this query, in the DB of ~500K entries there
> are ~13K different values for this field
> - status_s: has one of 2 values, in the query described baove all hits will
> have the value "active"
> - user_id_s: unique within the DB but not matched in this query
> - first_name_s: almost unique within the DB, this query will sort by this
> field
> - last_name_s: almost unique within the DB, this query will sort by this field
>
> This search query looks like:
> <<"sub_category_id_s:test_1 AND status_s:active AND type_s:sub_category">>
>
> Our options parameter has the sort directive:
> {sort, <<"first_name_s asc, last_name_s asc">>}
>
> The query was run on a 5-node cluster with n_val of 3.
>
> Thanks in advance fo rany pointers!
> //Sean.
>
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Solr search performance
Hi All,
We have an index with ~548,000 entries, ~14,000 of which match one of our
queries.
We read these in a paginated search and the first page (of 100 hits)
returns quickly in ~70ms.
This response time seems to increase exponentially as we walk through the
pages:
the 4th page takes ~200ms,
the 8th page takes ~1200ms
the 12th page takes ~2100ms
the 16th page takes ~6100ms
the 20th page takes ~24000ms
And by the time we're searching for the 22nd page it regularly times out at
the default 60 seconds.
I have a good unsderstanding of riak KV internals but absolutely nothing of
Lucene which I think is what's most relevant here. If anyone in the know
can point me towards any relevant resource or can explain what's happening
I'd be much obliged :-)
As I would also be if anyone with experience of using Riak/Lucene can tell
me:
- Is 500K a crazy number of entries to put into one index?
- Is 14K a crazy number of entries to expect to be returned?
- Are there any methods we can use to make the search time more constant
across the full search?
I read one blog post on inlining but it was a bit old & not very obvious
how to implement using riakc_pb_socket calls.
And out of curiosity, do we not traverse the full range of hits for each
page? I naively thought that because I'm sorting the returned values we'd
have to get them all first and then sort, but the response times suggests
otherwise. Does Lucene store the data sorted by each field just in case a
query asks for it? Or what other magic is going on?
For the technical details, we use the "_yz_default" schema and all the
fields stored are strings:
- entry_id_s: unique within the DB, the aim of the query is to gather a
list of these
- type_s: has one of 2 values
- sub_category_id_s: in the query described above all 14K hits will match
on this, in the DB of ~500K entries there are ~43K different values for
this field, withe each category typically having 2-6 sub categories
- category_id_s: not matched in this query, in the DB of ~500K entries
there are ~13K different values for this field
- status_s: has one of 2 values, in the query described baove all hits will
have the value "active"
- user_id_s: unique within the DB but not matched in this query
- first_name_s: almost unique within the DB, this query will sort by this
field
- last_name_s: almost unique within the DB, this query will sort by this
field
This search query looks like:
<<"sub_category_id_s:test_1 AND status_s:active AND type_s:sub_category">>
Our options parameter has the sort directive:
{sort, <<"first_name_s asc, last_name_s asc">>}
The query was run on a 5-node cluster with n_val of 3.
Thanks in advance fo rany pointers!
//Sean.
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