Hey Scott,
I'm still not sure I understand what your dynamic boosts are for: they
are the names of fields, right, not terms in the fields? So in terms
of your example { company = microsoft, city = redmond, size = big },
the three possible choices for keys in your map are company, city,
or size, right?
So if you passed in { company => 0.5, size => 0.3 } as your map,
how would you compute the score for the two documents
{ company: microsoft, city: redmond, size: big } and
{ company: google, city: mountain view, size: big }
Where is the Float that you have stored in the doc, that you're
accessing via Float.parseFloat( document.get(fieldName) ) ?
So is it that you have fields in the index, which basically contain
numeric data, and then you want to multiply those indexed floats
by query-time values to make the score?
I'm sorry if I'm not fully following how this works. Can you restate
your example showing what you have in the index, and what comes
in in the query?
-jake
On Fri, Oct 9, 2009 at 2:18 PM, scott w <scottbl...@gmail.com> wrote:
> (Apologies if this message gets sent more than once. I received an error
> sending it the first two times so sent directly to Jake but reposting to
> group.)
> Hi Jake --
>
> Thanks for the feedback.
>
> What I am trying to implement is a way to custom score documents using a
> scoring function that takes as input a map of fields (which may or may not
> be in any given document) and weights for those fields supplied at query
> time, and outputs an aggregate score that is based on taking the numeric
> field weights that are already stored and indexed and then readjusting
> those
> weights based on the map.
>
> Another thing I would like to do is the same thing but for fields that do
> not have weights associated with them in the index and so the query time
> supplied weights essentially get used directly instead of adjusting the
> already indexed weights.
>
> You can think of this is as implementing a form of personalization where
> you
> have a default set of weights and you want to adjust them on the fly
> although our use case is a little different.
>
> thanks,
> Scott
>
> On Fri, Oct 9, 2009 at 10:40 AM, Jake Mannix <jake.man...@gmail.com>
> wrote:
>
> > Scott,
> >
> > To reiterate what Erick and Andrzej's said: calling
> > IndexReader.document(docId)
> > in your inner scoring loop is the source of your performance problem -
> > iterating
> > over all these stored fields is what is killing you.
> >
> > To do this a better way, can you try to explain exactly what this Scorer
> > is
> > supposed to be doing? You're extending CustomScoreQuery and which
> > is usually used with ValueSourceQuery, but you don't use that part, and
> > ignore the valSrcScore in your computation.
> >
> > Where are the parts of your score coming from? The termWeight map
> > is used how exactly?
> >
> > -jake
> >
> > On Fri, Oct 9, 2009 at 10:30 AM, scott w <scottbl...@gmail.com> wrote:
> >
> > > Thanks for the suggestions Erick. I am using Lucene 2.3. Terms are
> stored
> > > and given Andrzej's comments in the follow up email sounds like it's
> not
> > > the
> > > stored field issue. I'll keep investigating...
> > >
> > > thanks,
> > > Scott
> > >
> > > On Thu, Oct 8, 2009 at 8:06 AM, Erick Erickson <
> erickerick...@gmail.com
> > > >wrote:
> > >
> > > > I suspect your problem here is the line:
> > > > document = indexReader.document( doc );
> > > >
> > > > See the caution in the docs
> > > >
> > > > You could try using lazy loading (so you don't load all
> > > > the terms of the document, just those you're interested
> > > > in). And I *think* (but it's been a while) that if the terms
> > > > you load are indexed that'll help. But this is mostly
> > > > a guess.
> > > >
> > > > What version of Lucene are you using???
> > > >
> > > > Good luck!
> > > > Erick
> > > >
> > > > On Thu, Oct 8, 2009 at 10:56 AM, scott w <scottbl...@gmail.com>
> wrote:
> > > >
> > > > > Oops, forgot to include the class I mentioned. Here it is:
> > > > >
> > > > > public class QueryTermBoostingQuery extends CustomScoreQuery {
> > > > > private Map<String, Float> queryTermWeights;
> > > > > private float bias;
> > > > > private IndexReader indexReader;
> > > > >
> > > > > public QueryTermBoostingQuery( Query q, Map<String, Float>
> > > termWeights,
> > > > > IndexReader indexReader, float bias) {
> > > > > super( q );
> > > > > this.indexReader = indexReader;
> > > > > if (bias < 0 || bias > 1) {
> > > > > throw new IllegalArgumentException( "Bias must be between 0
> and
> > 1"
> > > > );
> > > > > }
> > > > > this.bias = bias;
> > > > > queryTermWeights = termWeights;
> > > > > }
> > > > >
> > > > > @Override
> > > > > public float customScore( int doc, float subQueryScore, float
> > > > valSrcScore
> > > > > ) {
> > > > > Document document;
> > > > > try {
> > > > > document = indexReader.document( doc );
> > > > > } catch (IOException e) {
> > > > > throw new SearchException( e );
> > > > > }
> > > > > float termWeightedScore = 0;
> > > > >
> > > > > for (String field : queryTermWeights.keySet()) {
> > > > > String docFieldValue = document.get( field );
> > > > > if (docFieldValue != null) {
> > > > > Float weight = queryTermWeights.get( field );
> > > > > if (weight != null) {
> > > > > termWeightedScore += weight * Float.parseFloat(
> > docFieldValue
> > > );
> > > > > }
> > > > > }
> > > > > }
> > > > > return bias * subQueryScore + (1 - bias) * termWeightedScore;
> > > > > }
> > > > > }
> > > > >
> > > > > On Thu, Oct 8, 2009 at 7:54 AM, scott w <scottbl...@gmail.com>
> > wrote:
> > > > >
> > > > > > I am trying to come up with a performant query that will allow me
> > to
> > > > use
> > > > > a
> > > > > > custom score where the custom score is a sum-product over a set
> of
> > > > query
> > > > > > time weights where each weight gets applied only if the query
> time
> > > term
> > > > > > exists in the document . So for example if I have a doc with
> three
> > > > > fields:
> > > > > > company=Microsoft, city=Redmond, and size=large, I may want to
> > score
> > > > that
> > > > > > document according to the following function: city==Microsoft ?
> .3
> > :
> > > 0
> > > > *
> > > > > > size ==large ? 0.5 : 0 to get a score of 0.8. Attached is a
> > subclass
> > > I
> > > > > have
> > > > > > tested that implements this with one extra component which is
> that
> > it
> > > > > allow
> > > > > > the relevance score to be combined in.
> > > > > >
> > > > > > The problem is this custom score is not performant at all. For
> > > example,
> > > > > on
> > > > > > a small index of 5 million documents with 10 weights passed in it
> > > does
> > > > > 0.01
> > > > > > req/sec.
> > > > > >
> > > > > > Are there ways to make to compute the same custom score but in a
> > much
> > > > > more
> > > > > > performant way?
> > > > > >
> > > > > > thanks,
> > > > > > Scott
> > > > > >
> > > > >
> > > >
> > >
> >
>
