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From "Rob Audenaerde (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (LUCENE-5476) Facet sampling
Date Mon, 03 Mar 2014 12:46:22 GMT

    [ https://issues.apache.org/jira/browse/LUCENE-5476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13918017#comment-13918017
] 

Rob Audenaerde edited comment on LUCENE-5476 at 3/3/14 12:46 PM:
-----------------------------------------------------------------

Quick update:

I implemented the single pass on the 'addDoc' method using a fixed interval (which should
be the fastest implementation I guess)

Exact: 180ms
Single Pass (no-clone) Fixed Interval: 38ms. 

This is an almost 4.75x speed-up. 

I will compare this later on with a single pass random indexed approach. 

{quote}
Hmm, I don't think the single-pass option would require
xorshift.nextInt() on every call? Couldn't you keep a countInBin
field in your SampledDocs, increment it on each Docs.addDoc, and when
it's == randomIndex, add to the sampled bits and then pick a new
randomIndex? This should save a 2nd pass iteration?
{quote}

Yes I thought of this too. I will update this. I think I prefer the single pass option myself,
as I do not need the original bitset and the faster option. 


was (Author: robau):
Quick update:

I implemented the single pass on the 'addDoc' method using a fixed interval (which should
be the fastest implementation I guess)

Exact: 180ms
Single Pass (no-clone) Fixed Interval: 38ms. 

This is a 4.5x speed-up. 

I will compare this later on with a single pass random indexed approach. 

{quote}
Hmm, I don't think the single-pass option would require
xorshift.nextInt() on every call? Couldn't you keep a countInBin
field in your SampledDocs, increment it on each Docs.addDoc, and when
it's == randomIndex, add to the sampled bits and then pick a new
randomIndex? This should save a 2nd pass iteration?
{quote}

Yes I thought of this too. I will update this. I think I prefer the single pass option myself,
as I do not need the original bitset and the faster option. 

> Facet sampling
> --------------
>
>                 Key: LUCENE-5476
>                 URL: https://issues.apache.org/jira/browse/LUCENE-5476
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Rob Audenaerde
>         Attachments: LUCENE-5476.patch, LUCENE-5476.patch, SamplingComparison_SamplingFacetsCollector.java,
SamplingFacetsCollector.java
>
>
> With LUCENE-5339 facet sampling disappeared. 
> When trying to display facet counts on large datasets (>10M documents) counting facets
is rather expensive, as all the hits are collected and processed. 
> Sampling greatly reduced this and thus provided a nice speedup. Could it be brought back?



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