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https://issues.apache.org/jira/browse/SOLR-6351?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14158244#comment-14158244
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Hoss Man commented on SOLR-6351:
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bq. One thing though, what is expected behavior for pivots where count is 0?
Currently, you'll get the full entry with NaN, infinity and such in it. Should
it be null or empty instead? Or should it even show up at all?
Great question.
I think in this case we should leave out "stats" subsection completely for
brevity -- similar to how the "pivot" subsection is left out whenever there are
no sub-pivots to report counts for. it's also mostly consistent with the
common case of sub-pivots when the parent count is 0 in distributed pivots
since mincount=0 isn't really viable (SOLR-6329).
But i could be persuaded that we should leave in an empty 'stats' section ... a
stats section full of fields reporting a bunch of NaN and Infinity counts seems
likeit's just asking for causing user error though.
> Let Stats Hang off of Pivots (via 'tag')
> ----------------------------------------
>
> Key: SOLR-6351
> URL: https://issues.apache.org/jira/browse/SOLR-6351
> Project: Solr
> Issue Type: Sub-task
> Reporter: Hoss Man
> Attachments: SOLR-6351.patch, SOLR-6351.patch, SOLR-6351.patch
>
>
> he goal here is basically flip the notion of "stats.facet" on it's head, so
> that instead of asking the stats component to also do some faceting
> (something that's never worked well with the variety of field types and has
> never worked in distributed mode) we instead ask the PivotFacet code to
> compute some stats X for each leaf in a pivot. We'll do this with the
> existing {{stats.field}} params, but we'll leverage the {{tag}} local param
> of the {{stats.field}} instances to be able to associate which stats we want
> hanging off of which {{facet.pivot}}
> Example...
> {noformat}
> facet.pivot={!stats=s1}category,manufacturer
> stats.field={!key=avg_price tag=s1 mean=true}price
> stats.field={!tag=s1 min=true max=true}user_rating
> {noformat}
> ...with the request above, in addition to computing the min/max user_rating
> and mean price (labeled "avg_price") over the entire result set, the
> PivotFacet component will also include those stats for every node of the tree
> it builds up when generating a pivot of the fields "category,manufacturer"
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