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https://issues.apache.org/jira/browse/SOLR-7560?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14578827#comment-14578827
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Joel Bernstein commented on SOLR-7560:
--------------------------------------

Looks great!

A little background on this discussion. [~dpgove] is describing the Streaming 
Expression (SOLR-7377) syntax for the RollupStream which is being added in this 
ticket to support the SQL aggregate functions. The RollupStream does Map/Reduce 
style aggregations where group by fields are sorted first and the aggregates 
are rolled up one group at a time. This technique will be very strong for time 
series rollups and aggregating high cardinality fields.

There will be other aggregation streams added in the future that tap into Solr 
faceting directly. 

> Parallel SQL Support
> --------------------
>
>                 Key: SOLR-7560
>                 URL: https://issues.apache.org/jira/browse/SOLR-7560
>             Project: Solr
>          Issue Type: New Feature
>          Components: clients - java, search
>            Reporter: Joel Bernstein
>             Fix For: 5.3
>
>         Attachments: SOLR-7560.patch
>
>
> This ticket provides support for executing *Parallel SQL* queries across 
> SolrCloud collections. The SQL engine will be built on top of the Streaming 
> API (SOLR-7082), which provides support for *parallel relational algebra* and 
> *real-time map-reduce*.
> Basic design:
> 1) A new SQLHandler will be added to process SQL requests. The SQL statements 
> will be compiled to live Streaming API objects for parallel execution across 
> SolrCloud worker nodes.
> 2) SolrCloud collections will be abstracted as *Relational Tables*. 
> 3) The Presto SQL parser will be used to parse the SQL statements.
> 4) A JDBC thin client will be added as a Solrj client.
> This ticket will focus on putting the framework in place and providing basic 
> SELECT support and GROUP BY aggregate support.
> Future releases will build on this framework to provide additional SQL 
> features.



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