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Posted to dev@lucene.apache.org by "Joel Bernstein (JIRA)" <ji...@apache.org> on 2016/05/10 20:59:13 UTC

[jira] [Commented] (SOLR-9096) Add PartitionStream to Streaming Expressions

    [ https://issues.apache.org/jira/browse/SOLR-9096?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15278880#comment-15278880 ] 

Joel Bernstein commented on SOLR-9096:
--------------------------------------

I'm curious about the implementation. How do the workers receive the data? are the streams pushed to the workers? or is it a callback?

> Add PartitionStream to Streaming Expressions
> --------------------------------------------
>
>                 Key: SOLR-9096
>                 URL: https://issues.apache.org/jira/browse/SOLR-9096
>             Project: Solr
>          Issue Type: New Feature
>            Reporter: Dennis Gove
>
> The basic idea of a PartitionStream is to take a one or more input streams of tuples, partition them out to a set of workers such that each worker can work with a subset of the tuples, and then bring them all back into a single stream. This differs from a ParallelStream because in ParallelStream the data is partitioned at the source whereas with a PartitionStream one can take an existing stream and spread it out across workers.
> The use-case here is for when one has a source stream (or more) which cannot be parallelized at the source but which can be parallelized after some level of processing. I see this being used most for parallelized sort, rollups, or graph searches.
> {code}
>                             /--- sort ----\
>                            /               \                      /--- Collection A
>                           / ---- sort ----- \                    /
> Client <--- rollup  <----<                    <----- innerJoin <
>                           \ ---- sort ----- /                    \
>                            \               /                      \--- Collection B
>                             \--- sort ----/
> {code}
> {code}
>                             /--- sort -- rollup ----\
>                            /                         \                      /--- Collection A
>                           / ---- sort -- rollup ----- \                    /
> Client <-- innerJoin <---<                              <----- innerJoin <
>                     \     \ ---- sort -- rollup ----- /                    \
>                      \     \                         /                      \--- Collection B
>                       \     \--- sort -- rollup ----/
>                        \
>                         \
>                          \ <--- jdbc source
> {code}
> {code}
>                             /--- sort -- innerJoin ----\
>                            /                            \  
>                           / ---- sort -- innerJoin ----- \  <--- jdbc source
> Client <-- innerJoin <---<                                | 
>                     \     \ ---- sort -- innerJoin ----- /  <--- rollup <---- Collection A
>                      \     \                            /  
>                       \     \--- sort -- innerJoin ----/
>                        \
>                         \
>                          \ <--- jdbc source
> {code}
> I imagine partition expression would look something like this
> {code}
> partition(
>   inputA=<source stream A>,
>   inputB=<source stream B>,
>   work=<stream for the workers>,
>   over="fieldA,fieldB",
>   workers=6,
>   zkHost=<zk connection string>
> )
> {code}
> for example
> {code}
> innerJoin(
>   partition(
>     inputA=jdbc(database1),
>     inputB=rollup(
>       search(collectionA, ...),
>       ...
>     ),
>     work=sort(
>       innerJoin(
>         inputA,
>         inputB,
>         on="fieldA,fieldB"
>       ),
>       by="jdbcFieldC asc, collectionAFieldB desc"
>     ),
>     workers=6,
>     zkHost=localhost:12345
>   ),
>   jdbc(database2),
>   on="fieldZ"
> )
> {code}



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