The cache is currently being stored as a static HashMap on the MLT
object and expired at the discretion of the application code using a
static MLT.flushCache() method. Use of the cache at all is opt-in,
using a non-static MLT.setCache(true) and a new constructor signature
on MLTQuery that includes a useCache parameter.

It's not pretty but it's enough for our use case.

Feel free to suggest nicer solutions if you've got them.



2009/4/10 Grant Ingersoll <gsing...@apache.org>:
> What was your approach to handling stale cache entries?  Did you flush it
> when you opened a new reader?
>
> On Apr 7, 2009, at 2:28 AM, Richard Marr wrote:
>
>> Hi all,
>>
>> I've been exploring MoreLikeThisQuery as part of a recent project and
>> something that came out of that might be useful to others here.
>>
>> I found that using MoreLikeThisQuery could be quite slow for my use
>> case, but that most of the time involved was spent looking up term
>> frequencies to calculate weightings. Since those term frequencies
>> usually don't need to be anywhere near real-time I found that caching
>> them in a hashmap had a very good cost/benefit ratio for my
>> application, speeding up MLT queries by an order of magnitude.
>>
>> My use case was possibly unusual in that I was looking at a limited
>> vocabulary rather than full English, but in theory other applications
>> that make use of the MLT class could benefit.
>>
>> So at this point I have some questions: (1) Have others experienced
>> similar performance characteristics for MLT code? (2) Am I missing
>> some fatal flaw in this approach? (3) Are the modifications worth
>> sharing?
>>
>> Cheers,
>>
>> Rich
>>
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-- 
Richard Marr
richard.m...@gmail.com
07976 910 515

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