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From "Robert Muir (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (LUCENE-6276) Add matchCost() api to TwoPhaseDocIdSetIterator
Date Sat, 21 Feb 2015 19:55:12 GMT

    [ https://issues.apache.org/jira/browse/LUCENE-6276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14330411#comment-14330411
] 

Robert Muir commented on LUCENE-6276:
-------------------------------------

{quote}
I'm curious if you already have concrete ideas for the match costs of our existing queries?
{quote}

See above in the description. we know the average number of positions per doc (totalTermFreq/docFreq)
and so on. So we can compute the amortized cost of reading one position, and its easy from
there.

{quote}
Maybe it should not only measure the cost of the operation but also how likely it is to match?
{quote}

I don't agree. You can already get this with Scorer.getApproximation().cost()/Scorer.cost().


> Add matchCost() api to TwoPhaseDocIdSetIterator
> -----------------------------------------------
>
>                 Key: LUCENE-6276
>                 URL: https://issues.apache.org/jira/browse/LUCENE-6276
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Robert Muir
>
> We could add a method like TwoPhaseDISI.matchCost() defined as something like estimate
of nanoseconds or similar. 
> ConjunctionScorer could use this method to sort its 'twoPhaseIterators' array so that
cheaper ones are called first. Today it has no idea if one scorer is a simple phrase scorer
on a short field vs another that might do some geo calculation or more expensive stuff.
> PhraseScorers could implement this based on index statistics (e.g. totalTermFreq/maxDoc)



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