Hello all:
We've done some tests with Em's approach of putting a BooleanQuery in front
of our user query, that means:
BooleanQuery
must (DismaxQuery)
should (FunctionQuery)
The FunctionQuery obtains the SOLR IR score by means of a QueryValueSource,
then does the SQRT of this value, and then multiplies it by our custom
"query_score" float, pulling it by means of a FieldCacheSource.
In particular, we've proceeded in the following way:
- we've loaded the whole index in the page cache of the OS to make sure
we don't have disk IO problems that might affect the benchmarks (our
machine has enough memory to load all the index in RAM)
- we've executed an out-of-benchmark query 10-20 times to make sure that
everything is jitted and that Lucene's FieldCache is properly populated.
- we've disabled all the caches (filter query cache, document cache,
query cache)
- we've executed 8 different user queries with and without
FunctionQueries, with early termination in both cases (our collector stops
after collecting 50 documents per shard)
Em was correct, the query is much faster with the BooleanQuery in front,
but it's still 30-40% slower than the query without FunctionQueries.
Although one may think that it's reasonable that the query response time
increases because of the extra computations, we believe that the increase
is too big, given that we're collecting just 500-600 documents due to the
early query termination techniques we currently use.
Any ideas on how to make it faster?.
Thanks a lot,
Carlos
Carlos Gonzalez-Cadenas
CEO, ExperienceOn - New generation search
http://www.experienceon.com
Mobile: +34 652 911 201
Skype: carlosgonzalezcadenas
LinkedIn: http://www.linkedin.com/in/carlosgonzalezcadenas
On Fri, Feb 17, 2012 at 11:07 AM, Carlos Gonzalez-Cadenas <
c...@experienceon.com> wrote:
> Thanks Em, Robert, Chris for your time and valuable advice. We'll make
> some tests and will let you know soon.
>
>
>
> On Thu, Feb 16, 2012 at 11:43 PM, Em <mailformailingli...@yahoo.de> wrote:
>
>> Hello Carlos,
>>
>> I think we missunderstood eachother.
>>
>> As an example:
>> BooleanQuery (
>> clauses: (
>> MustMatch(
>> DisjunctionMaxQuery(
>> TermQuery("stopword_field", "barcelona"),
>> TermQuery("stopword_field", "hoteles")
>> )
>> ),
>> ShouldMatch(
>> FunctionQuery(
>> *please insert your function here*
>> )
>> )
>> )
>> )
>>
>> Explanation:
>> You construct an artificial BooleanQuery which wraps your user's query
>> as well as your function query.
>> Your user's query - in that case - is just a DisjunctionMaxQuery
>> consisting of two TermQueries.
>> In the real world you might construct another BooleanQuery around your
>> DisjunctionMaxQuery in order to have more flexibility.
>> However the interesting part of the given example is, that we specify
>> the user's query as a MustMatch-condition of the BooleanQuery and the
>> FunctionQuery just as a ShouldMatch.
>> Constructed that way, I am expecting the FunctionQuery only scores those
>> documents which fit the MustMatch-Condition.
>>
>> I conclude that from the fact that the FunctionQuery-class also has a
>> skipTo-method and I would expect that the scorer will use it to score
>> only matching documents (however I did not search where and how it might
>> get called).
>>
>> If my conclusion is wrong than hopefully Robert Muir (as far as I can
>> see the author of that class) can tell us what was the intention by
>> constructing an every-time-match-all-function-query.
>>
>> Can you validate whether your QueryParser constructs a query in the form
>> I drew above?
>>
>> Regards,
>> Em
>>
>> Am 16.02.2012 20:29, schrieb Carlos Gonzalez-Cadenas:
>> > Hello Em:
>> >
>> > 1) Here's a printout of an example DisMax query (as you can see mostly
>> MUST
>> > terms except for some SHOULD terms used for boosting scores for
>> stopwords)
>> > *
>> > *
>> > *((+stopword_shortened_phrase:hoteles
>> +stopword_shortened_phrase:barcelona
>> > stopword_shortened_phrase:en) | (+stopword_phrase:hoteles
>> > +stopword_phrase:barcelona
>> > stopword_phrase:en) | (+stopword_shortened_phrase:hoteles
>> +stopword_short
>> > ened_phrase:barcelona stopword_shortened_phrase:en) |
>> (+stopword_phrase:hoteles
>> > +stopword_phrase:barcelona stopword_phrase:en) | (+stopword_shor
>> > tened_phrase:hoteles +wildcard_stopword_shortened_phrase:barcelona
>> > stopword_shortened_phrase:en) | (+stopword_phrase:hoteles
>> +wildcard_stopw
>> > ord_phrase:barcelona stopword_phrase:en) |
>> (+stopword_shortened_phrase:hoteles
>> > +wildcard_stopword_shortened_phrase:barcelona
>> stopword_shortened_phrase:en)
>> > | (+stopword_phrase:hoteles +wildcard_stopword_phrase:barcelona
>> > stopword_phrase:en))*
>> > *
>> > *
>> > 2)* *The collector is inserted in the SolrIndexSearcher (replacing the
>> > TimeLimitingCollector). We trigger it through the SOLR interface by
>> passing
>> > the timeAllowed parameter. We know this is a hack but AFAIK there's no
>> > out-of-the-box way to specify custom collectors by now (
>> > https://issues.apache.org/jira/browse/SOLR-1680). In any case the
>> collector
>> > part works perfectly as of now, so clearly this is not the problem.
>> >
>> > 3) Re: your sentence:
>> > *
>> > *
>> > **I* would expect that with a shrinking set of matching documents to
>> > the overall-query, the function query only checks those documents that
>> are
>> > guaranteed to be within the result set.*
>> > *
>> > *
>> > Yes, I agree with this, but this snippet of code in FunctionQuery.java
>> > seems to say otherwise:
>> >
>> > // instead of matching all docs, we could also embed a query.
>> > // the score could either ignore the subscore, or boost it.
>> > // Containment: floatline(foo:myTerm, "myFloatField", 1.0, 0.0f)
>> > // Boost: foo:myTerm^floatline("myFloatField",1.0,0.0f)
>> > @Override
>> > public int nextDoc() throws IOException {
>> > for(;;) {
>> > ++doc;
>> > if (doc>=maxDoc) {
>> > return doc=NO_MORE_DOCS;
>> > }
>> > if (acceptDocs != null && !acceptDocs.get(doc)) continue;
>> > return doc;
>> > }
>> > }
>> >
>> > It seems that the author also thought of maybe embedding a query in
>> order
>> > to restrict matches, but this doesn't seem to be in place as of now (or
>> > maybe I'm not understanding how the whole thing works :) ).
>> >
>> > Thanks
>> > Carlos
>> > *
>> > *
>> >
>> > Carlos Gonzalez-Cadenas
>> > CEO, ExperienceOn - New generation search
>> > http://www.experienceon.com
>> >
>> > Mobile: +34 652 911 201
>> > Skype: carlosgonzalezcadenas
>> > LinkedIn: http://www.linkedin.com/in/carlosgonzalezcadenas
>> >
>> >
>> > On Thu, Feb 16, 2012 at 8:09 PM, Em <mailformailingli...@yahoo.de>
>> wrote:
>> >
>> >> Hello Carlos,
>> >>
>> >>> We have some more tests on that matter: now we're moving from issuing
>> >> this
>> >>> large query through the SOLR interface to creating our own
>> >> QueryParser. The
>> >>> initial tests we've done in our QParser (that internally creates
>> multiple
>> >>> queries and inserts them inside a DisjunctionMaxQuery) are very good,
>> >> we're
>> >>> getting very good response times and high quality answers. But when
>> we've
>> >>> tried to wrap the DisjunctionMaxQuery within a FunctionQuery (i.e.
>> with a
>> >>> QueryValueSource that wraps the DisMaxQuery), then the times move from
>> >>> 10-20 msec to 200-300msec.
>> >> I reviewed the sourcecode and yes, the FunctionQuery iterates over the
>> >> whole index, however... let's see!
>> >>
>> >> In relation to the DisMaxQuery you create within your parser: What kind
>> >> of clause is the FunctionQuery and what kind of clause are your other
>> >> queries (MUST, SHOULD, MUST_NOT...)?
>> >>
>> >> *I* would expect that with a shrinking set of matching documents to the
>> >> overall-query, the function query only checks those documents that are
>> >> guaranteed to be within the result set.
>> >>
>> >>> Note that we're using early termination of queries (via a custom
>> >>> collector), and therefore (as shown by the numbers I included above)
>> even
>> >>> if the query is very complex, we're getting very fast answers. The
>> only
>> >>> situation where the response time explodes is when we include a
>> >>> FunctionQuery.
>> >> Could you give us some details about how/where did you plugin the
>> >> Collector, please?
>> >>
>> >> Kind regards,
>> >> Em
>> >>
>> >> Am 16.02.2012 19:41, schrieb Carlos Gonzalez-Cadenas:
>> >>> Hello Em:
>> >>>
>> >>> Thanks for your answer.
>> >>>
>> >>> Yes, we initially also thought that the excessive increase in response
>> >> time
>> >>> was caused by the several queries being executed, and we did another
>> >> test.
>> >>> We executed one of the subqueries that I've shown to you directly in
>> the
>> >>> "q" parameter and then we tested this same subquery (only this one,
>> >> without
>> >>> the others) with the function query "query($q1)" in the "q" parameter.
>> >>>
>> >>> Theoretically the times for these two queries should be more or less
>> the
>> >>> same, but the second one is several times slower than the first one.
>> >> After
>> >>> this observation we learned more about function queries and we learned
>> >> from
>> >>> the code and from some comments in the forums [1] that the
>> >> FunctionQueries
>> >>> are expected to match all documents.
>> >>>
>> >>> We have some more tests on that matter: now we're moving from issuing
>> >> this
>> >>> large query through the SOLR interface to creating our own
>> QueryParser.
>> >> The
>> >>> initial tests we've done in our QParser (that internally creates
>> multiple
>> >>> queries and inserts them inside a DisjunctionMaxQuery) are very good,
>> >> we're
>> >>> getting very good response times and high quality answers. But when
>> we've
>> >>> tried to wrap the DisjunctionMaxQuery within a FunctionQuery (i.e.
>> with a
>> >>> QueryValueSource that wraps the DisMaxQuery), then the times move from
>> >>> 10-20 msec to 200-300msec.
>> >>>
>> >>> Note that we're using early termination of queries (via a custom
>> >>> collector), and therefore (as shown by the numbers I included above)
>> even
>> >>> if the query is very complex, we're getting very fast answers. The
>> only
>> >>> situation where the response time explodes is when we include a
>> >>> FunctionQuery.
>> >>>
>> >>> Re: your question of what we're trying to achieve ... We're
>> implementing
>> >> a
>> >>> powerful query autocomplete system, and we use several fields to a)
>> >> improve
>> >>> performance on wildcard queries and b) have a very precise control
>> over
>> >> the
>> >>> score.
>> >>>
>> >>> Thanks a lot for your help,
>> >>> Carlos
>> >>>
>> >>> [1]:
>> >>
>> http://grokbase.com/p/lucene/solr-user/11bjw87bt5/functionquery-score-0
>> >>>
>> >>> Carlos Gonzalez-Cadenas
>> >>> CEO, ExperienceOn - New generation search
>> >>> http://www.experienceon.com
>> >>>
>> >>> Mobile: +34 652 911 201
>> >>> Skype: carlosgonzalezcadenas
>> >>> LinkedIn: http://www.linkedin.com/in/carlosgonzalezcadenas
>> >>>
>> >>>
>> >>> On Thu, Feb 16, 2012 at 7:09 PM, Em <mailformailingli...@yahoo.de>
>> >> wrote:
>> >>>
>> >>>> Hello Carlos,
>> >>>>
>> >>>> well, you must take into account that you are executing up to 8
>> queries
>> >>>> per request instead of one query per request.
>> >>>>
>> >>>> I am not totally sure about the details of the implementation of the
>> >>>> max-function-query, but I guess it first iterates over the results of
>> >>>> the first max-query, afterwards over the results of the second
>> max-query
>> >>>> and so on. This is a much higher complexity than in the case of a
>> normal
>> >>>> query.
>> >>>>
>> >>>> I would suggest you to optimize your request. I don't think that this
>> >>>> particular function query is matching *all* docs. Instead I think it
>> >>>> just matches those docs specified by your inner-query (although I
>> might
>> >>>> be wrong about that).
>> >>>>
>> >>>> What are you trying to achieve by your request?
>> >>>>
>> >>>> Regards,
>> >>>> Em
>> >>>>
>> >>>> Am 16.02.2012 16:24, schrieb Carlos Gonzalez-Cadenas:
>> >>>>> Hello Em:
>> >>>>>
>> >>>>> The URL is quite large (w/ shards, ...), maybe it's best if I paste
>> the
>> >>>>> relevant parts.
>> >>>>>
>> >>>>> Our "q" parameter is:
>> >>>>>
>> >>>>>
>> >>>>
>> >>
>> "q":"_val_:\"product(query_score,max(query($q8),max(query($q7),max(query($q4),query($q3)))))\"",
>> >>>>>
>> >>>>> The subqueries q8, q7, q4 and q3 are regular queries, for example:
>> >>>>>
>> >>>>> "q7":"stopword_phrase:colomba~1 AND stopword_phrase:santa AND
>> >>>>> wildcard_stopword_phrase:car^0.7 AND stopword_phrase:hoteles OR
>> >>>>> (stopword_phrase:las AND stopword_phrase:de)"
>> >>>>>
>> >>>>> We've executed the subqueries q3-q8 independently and they're very
>> >> fast,
>> >>>>> but when we introduce the function queries as described below, it
>> all
>> >>>> goes
>> >>>>> 10X slower.
>> >>>>>
>> >>>>> Let me know if you need anything else.
>> >>>>>
>> >>>>> Thanks
>> >>>>> Carlos
>> >>>>>
>> >>>>>
>> >>>>> Carlos Gonzalez-Cadenas
>> >>>>> CEO, ExperienceOn - New generation search
>> >>>>> http://www.experienceon.com
>> >>>>>
>> >>>>> Mobile: +34 652 911 201
>> >>>>> Skype: carlosgonzalezcadenas
>> >>>>> LinkedIn: http://www.linkedin.com/in/carlosgonzalezcadenas
>> >>>>>
>> >>>>>
>> >>>>> On Thu, Feb 16, 2012 at 4:02 PM, Em <mailformailingli...@yahoo.de>
>> >>>> wrote:
>> >>>>>
>> >>>>>> Hello carlos,
>> >>>>>>
>> >>>>>> could you show us how your Solr-call looks like?
>> >>>>>>
>> >>>>>> Regards,
>> >>>>>> Em
>> >>>>>>
>> >>>>>> Am 16.02.2012 14:34, schrieb Carlos Gonzalez-Cadenas:
>> >>>>>>> Hello all:
>> >>>>>>>
>> >>>>>>> We'd like to score the matching documents using a combination of
>> >> SOLR's
>> >>>>>> IR
>> >>>>>>> score with another application-specific score that we store within
>> >> the
>> >>>>>>> documents themselves (i.e. a float field containing the
>> app-specific
>> >>>>>>> score). In particular, we'd like to calculate the final score
>> doing
>> >>>> some
>> >>>>>>> operations with both numbers (i.e product, sqrt, ...)
>> >>>>>>>
>> >>>>>>> According to what we know, there are two ways to do this in SOLR:
>> >>>>>>>
>> >>>>>>> A) Sort by function [1]: We've tested an expression like
>> >>>>>>> "sort=product(score, query_score)" in the SOLR query, where score
>> is
>> >>>> the
>> >>>>>>> common SOLR IR score and query_score is our own precalculated
>> score,
>> >>>> but
>> >>>>>> it
>> >>>>>>> seems that SOLR can only do this with stored/indexed fields (and
>> >>>>>> obviously
>> >>>>>>> "score" is not stored/indexed).
>> >>>>>>>
>> >>>>>>> B) Function queries: We've used _val_ and function queries like
>> max,
>> >>>> sqrt
>> >>>>>>> and query, and we've obtained the desired results from a
>> functional
>> >>>> point
>> >>>>>>> of view. However, our index is quite large (400M documents) and
>> the
>> >>>>>>> performance degrades heavily, given that function queries are
>> AFAIK
>> >>>>>>> matching all the documents.
>> >>>>>>>
>> >>>>>>> I have two questions:
>> >>>>>>>
>> >>>>>>> 1) Apart from the two options I mentioned, is there any other
>> >> (simple)
>> >>>>>> way
>> >>>>>>> to achieve this that we're not aware of?
>> >>>>>>>
>> >>>>>>> 2) If we have to choose the function queries path, would it be
>> very
>> >>>>>>> difficult to modify the actual implementation so that it doesn't
>> >> match
>> >>>>>> all
>> >>>>>>> the documents, that is, to pass a query so that it only operates
>> over
>> >>>> the
>> >>>>>>> documents matching the query?. Looking at the FunctionQuery.java
>> >> source
>> >>>>>>> code, there's a comment that says "// instead of matching all
>> docs,
>> >> we
>> >>>>>>> could also embed a query. the score could either ignore the
>> subscore,
>> >>>> or
>> >>>>>>> boost it", which is giving us some hope that maybe it's possible
>> and
>> >>>> even
>> >>>>>>> desirable to go in this direction. If you can give us some
>> directions
>> >>>>>> about
>> >>>>>>> how to go about this, we may be able to do the actual
>> implementation.
>> >>>>>>>
>> >>>>>>> BTW, we're using Lucene/SOLR trunk.
>> >>>>>>>
>> >>>>>>> Thanks a lot for your help.
>> >>>>>>> Carlos
>> >>>>>>>
>> >>>>>>> [1]: http://wiki.apache.org/solr/FunctionQuery#Sort_By_Function
>> >>>>>>>
>> >>>>>>
>> >>>>>
>> >>>>
>> >>>
>> >>
>> >
>>
>
>
