Ram Directory (was: Result Relevance (was: Handling Duplicates(

[Michael Garski <mg...@mac.com>]

Erich -

I do load the index into memory using a RAMDirectory, but the overhead 
of repetitively pulling a field from the index as a string and parsing 
out into a numerical value adds up when under load.  As my underlying 
index changes only once per hour, caching all of those values into an 
array saves clock cycles later when all I need to do is use the document 
id as the ordinal in an array as opposed to getting the field from the 
document and parsing it.

I've found that by pre-caching the stored data in the index that I need 
to include with my results nearly doubled the number of searches per 
second I can do, and as I have a very high volume system every bit of 
performance I can squeeze out is critical to me.

Michael

Erich Eichinger wrote:
>> What I am doing is reading all of the stored values in the index for every document 
>>     
>  
> I missed this one.
>  
> Didn't you mention an index size of 900MB? So you are reading this completely into memory? Wouldn't a RAMDirectory be an easier choice then?
>  
> I suggested the filter idea since I've got a strong Web/Realtime background. There's no time for 1 minute warmup during a webrequest - at least if you want your users to return ;-). Using a filter to sort out all irrelevant documents during search is the fastest way I can think of in this case.
>  
> -Erich
>
> ________________________________
>
> From: Michael Garski [mailto:mgarski@mac.com]
> Sent: Tue 2007-05-22 02:13
> To: lucene-net-user@incubator.apache.org
> Subject: Re: Result Relevance (was: Handling Duplicates(
>
>
>
> 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:mgarski@mac.com]
>> Sent: Mon 2007-05-21 21:57
>> To: lucene-net-user@incubator.apache.org
>> 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 <E....@diamonddogs.cc> 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:digydigy@gmail.com]
>>>> Sent: Sun 2007-05-20 00:32
>>>> To: lucene-net-user@incubator.apache.org
>>>> 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:pburrows@gmail.com]
>>>> Sent: Saturday, May 19, 2007 6:34 PM
>>>> To: lucene-net-user@incubator.apache.org
>>>> 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 <mg...@mac.com> 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
>>>>>        
>>>>>           
>>>>      
>>>>         
>>>    
>>>       
>>
>>
>>  
>>     
>
>
>
>
>   

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[Sergiy Savchenko <ma...@gmail.com>]