A filter is used to filter your search against a subset of the documents
in the index based on the results of a query.
What I am doing is reading all of the stored values in the index for
every document into an array when warming up a searcher. This is a nice
performance win that eliminates duplicate calls to reading stored values
out of the document and parsing them into integers (the unique id of the
data in an external database) when returning the results to the user
interface. It takes a minute or so to do this on warm-up, but it does
shave time off the execution of each search.
Michael
Erich Eichinger wrote:
Hi,
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.
maybe I'm missing something: but isn't a filter nearly doing what you are describing here? Where is the difference - especially regarding performance?
-Erich
________________________________
From: Michael Garski [mailto:[EMAIL PROTECTED]
Sent: Mon 2007-05-21 21:57
To: [email protected]
Subject: Re: Result Relevance (was: Handling Duplicates(
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
