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https://issues.apache.org/jira/browse/SOLR-12343?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16540330#comment-16540330
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Hoss Man commented on SOLR-12343:
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[~ysee...@gmail.com] - i've been testing this out with the SKG (relatedness())
function -- where i initially discovered bug -- and trying to remove the
workarounds for this that are currently in TestCloudJSONFacetSKG (grep for
SOLR-12343) but i'm seeing some failures that I think i've traced back to a
mistake in isBucketComplete() that _only_ affects facets using
{{processEmpty:true}} ...
{panel}
in {{getRefinement()}} you've got {{returnedAllBuckets}} taking into
consideration {{processEmpty:true}} -- so that even if a shardA doesn't say it
has {{more:true}} we will still send it candidate bucketX for refinement if we
didn't explicitly {{saw}} bucketX on shardA. so far so good.
but then, once all the refinement is done, and we have a fully refined bucketX
it might now sort "lower" then an incomplete bucketY ... and
{{isBucketComplete}} doesn't pay any attention to {{processEmpty:true}} ... so
it sees that shardA does *not* have {{more:true}} and thinks (the incomplete)
bucketY is ok to return.
{panel}
...I'll work up an isolated test case
> JSON Field Facet refinement can return incorrect counts/stats for sorted
> buckets
> --------------------------------------------------------------------------------
>
> Key: SOLR-12343
> URL: https://issues.apache.org/jira/browse/SOLR-12343
> Project: Solr
> Issue Type: Bug
> Security Level: Public(Default Security Level. Issues are Public)
> Reporter: Hoss Man
> Assignee: Yonik Seeley
> Priority: Major
> Attachments: SOLR-12343.patch, SOLR-12343.patch, SOLR-12343.patch,
> SOLR-12343.patch, SOLR-12343.patch, SOLR-12343.patch
>
>
> The way JSON Facet's simple refinement "re-sorts" buckets after refinement
> can cause _refined_ buckets to be "bumped out" of the topN based on the
> refined counts/stats depending on the sort - causing _unrefined_ buckets
> originally discounted in phase#2 to bubble up into the topN and be returned
> to clients *with inaccurate counts/stats*
> The simplest way to demonstrate this bug (in some data sets) is with a
> {{sort: 'count asc'}} facet:
> * assume shard1 returns termX & termY in phase#1 because they have very low
> shard1 counts
> ** but *not* returned at all by shard2, because these terms both have very
> high shard2 counts.
> * Assume termX has a slightly lower shard1 count then termY, such that:
> ** termX "makes the cut" off for the limit=N topN buckets
> ** termY does not make the cut, and is the "N+1" known bucket at the end of
> phase#1
> * termX then gets included in the phase#2 refinement request against shard2
> ** termX now has a much higher _known_ total count then termY
> ** the coordinator now sorts termX "worse" in the sorted list of buckets
> then termY
> ** which causes termY to bubble up into the topN
> * termY is ultimately included in the final result _with incomplete
> count/stat/sub-facet data_ instead of termX
> ** this is all indepenent of the possibility that termY may actually have a
> significantly higher total count then termX across the entire collection
> ** the key problem is that all/most of the other terms returned to the
> client have counts/stats that are the cumulation of all shards, but termY
> only has the contributions from shard1
> Important Notes:
> * This scenerio can happen regardless of the amount of overrequest used.
> Additional overrequest just increases the number of "extra" terms needed in
> the index with "better" sort values then termX & termY in shard2
> * {{sort: 'count asc'}} is not just an exceptional/pathelogical case:
> ** any function sort where additional data provided shards during refinement
> can cause a bucket to "sort worse" can also cause this problem.
> ** Examples: {{sum(price_i) asc}} , {{min(price_i) desc}} , {{avg(price_i)
> asc|desc}} , etc...
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