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https://issues.apache.org/jira/browse/SOLR-8593?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15753373#comment-15753373
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Joel Bernstein commented on SOLR-8593:
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If you we have two grouping fields *A, B* nested facets will be gathered using
the following approach:
1) Gather the *top N* facets for field A.
2) For each of the *top N* facets of field A, find the top N sub-facets for
field B
This avoids the exhaustive processing of all the unique combinations of A, B.
This is very performant (sub-second) when N is a relatively small number and
the cardinality of A, B is not too high.
In high cardinality scenarios we can switch to MapReduce mode which sorts the
Tuples on the GROUP BY fields and shuffles them to worker nodes. In MapReduce
mode the order of the GROUP BY fields is not important.
Having the ability to use faceting or MapReduce depending on cardinality is one
of the key features of Solr's SQL implementation.
> Integrate Apache Calcite into the SQLHandler
> --------------------------------------------
>
> Key: SOLR-8593
> URL: https://issues.apache.org/jira/browse/SOLR-8593
> Project: Solr
> Issue Type: Improvement
> Reporter: Joel Bernstein
> Assignee: Joel Bernstein
> Attachments: SOLR-8593.patch, SOLR-8593.patch
>
>
> The Presto SQL Parser was perfect for phase one of the SQLHandler. It was
> nicely split off from the larger Presto project and it did everything that
> was needed for the initial implementation.
> Phase two of the SQL work though will require an optimizer. Here is where
> Apache Calcite comes into play. It has a battle tested cost based optimizer
> and has been integrated into Apache Drill and Hive.
> This work can begin in trunk following the 6.0 release. The final query plans
> will continue to be translated to Streaming API objects (TupleStreams), so
> continued work on the JDBC driver should plug in nicely with the Calcite work.
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