Here is the method I use to alter the relevancy of Lucene's search
results based on other attributes of a document, while keeping
performance very high.
At index time, I store a value in the index that will be used to alter
the score, which is computed based on several business logic rules. To
improve performance at search time, during searcher warm up I create an
array the length of the document count then walk through each document
in the index reading the stored value, parsing into a number, and
caching in the array. In a high-volume system, the repetitive index i/o
to read and parse a stored value has a performance penalty but now I
only need to get the value out of the array with the document id of the
search hit.
I use a hit collector that I inherited from the TopDocCollector, which
from my experimentation is a big boon for performance when you only need
the highest scoring results. I have a 9 million document index that for
some searches on common terms and phrases can yield over 400,000 hits -
only the first few thousand of which are all that relevant and if I try
to use a normal HitCollector with that many hits performance suffers
when trying to do a sort to get the top results. With a collector
derived from TopDocCollector in the Collect method, call Base.Collect
with your altered relevancy score and the document id. As an added
bonus, the TopDocs return value is already sorted for you.
Hope this can help you,
Michael
Patrick Burrows wrote:
> What about physical storage order? In a traditional RDBMS (like SQL
> Server)
> you could create a clustered index for your table which sets the order
> the
> records are stored on disk.
>
> I know a full-text index is not the same thing, so I don't know if
> there is
> a similar concept or not.
>
> Because any scheme to order the results will not be as efficient as
> having
> the results ordered on return. Depending on the number of results,
this
> could be an enormous difference.
>
>
>
> On 5/20/07, Erich Eichinger <[EMAIL PROTECTED]> wrote:
>>
>> Hi all,
>>
>> did anyone ever try to write a custom filter for such a task? This
could
>> at least reduce the number resulting indexdocs that need to be
sorted.
>>
>> I'm thinking of something like this:
>>
>> 1) fetch all dbentity keys matching a certain relevance criteria
("where
>> popularity > 90")
>> 2) filter out all indexdocs where the key is not contained in the
list
>> fetched at step 1)
>>
>> of course this assumes that there is some key stored with the index
>> to be
>> able to associate an indexdoc<->dbentity
>>
>> just thinking loud,
>> Erich
>>
>>
>> ________________________________
>>
>> From: Digy [mailto:[EMAIL PROTECTED]
>> Sent: Sun 2007-05-20 00:32
>> To: [email protected]
>> Subject: RE: Result Relevance (was: Handling Duplicates(
>>
>>
>>
>> Hi Patrick,
>>
>> I also think that doing a db query for each result can degrade the
>> performance dramatically. Therefore storing relevance factor
within the
>> index is a better idea. But then ,as you say, cost of sorting arises.
To
>> minimize the cost, the number of hits to return can be limited to a
>> number(nDocs param of Search method of IndexSearcher). But this time,
>> the
>> ranking algorithm of lucene may skip out more relevant documents
before
>> sorting.
>>
>> So, I think
>> 1- making a search without a "nDoc" limitation
>> 2- Passing on the result set once and collecting the most
>> relevant
>> N
>> results(say 100 or 1000)
>> 3- Then sorting this results
>> can be better solution.
>>
>> DIGY
>>
>>
>> -----Original Message-----
>> From: Patrick Burrows [mailto:[EMAIL PROTECTED]
>> Sent: Saturday, May 19, 2007 6:34 PM
>> To: [email protected]
>> Subject: Result Relevance (was: Handling Duplicates(
>>
>> Thinking about this more, I don't think doing a second DB lookup for
>> each
>> result is going to scale well. It is possible that a single search
>> returns
>> tens of thousands of results, the very last one might be the most
>> relevant.
>> I am going to have to store the relevancy factors (it is more than
just
>> popularity) within the index itself.
>>
>> I think I will write something to update the relevancy rating once a
>> week
>> or
>> so for each indexed document. Afterall, I don't think Google updates
>> their
>> PageRank more than once a month or so.
>>
>> After that it is just a matter of sorting by that relevancy rating.
>> Though,
>> I read on the forums that sorting is a bit of an expensive procedure.
>> Someone mentioned 100 searches / sec going down to 10 / sec. Not sure
>> the
>> details or the hardware. But that is an order of magnitude
>> difference, if
>> those results can be believed.
>>
>> Gonna experiment, I guess.
>>
>>
>> On 5/18/07, Michael Garski <[EMAIL PROTECTED]> wrote:
>> >
>> > Patrick,
>> >
>> > I've had to do something very similar, and you have a couple of
>> options:
>> >
>> > 1. If the 'popularity' value is stored in a database, you can
look up
>> > those values after performing your search against the index and
then
>> > sort.
>> >
>> > 2. Continually update the index to reflect the most recent
>> > 'popularity' value and then perform a custom sort during your
search.
>> >
>> > For my application, #2 is what we fond to be most efficient.
>> >
>> > Michael
>> >
>> >
>> > On May 18, 2007, at 4:48 AM, Patrick Burrows wrote:
>> >
>> > > Thanks guys. I'll try it out.
>> > >
>> > > My next question is going to be about ranking the results of my
>> > > searches
>> > > based on information that is not in the index (popularity, for
>> > > instance,
>> > > which might change hourly). Is there some reading I can do on the
>> > > subject
>> > > before I start asking questions?
>> > >
>> > >
>> >
>> > --
>> > -
>> > P
>>
>>
>>
>>
>
>
