[jira] [Updated] (BEAM-10409) Add combiner packing to graph optimizer phases

["Beam JIRA Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-10409?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Beam JIRA Bot updated BEAM-10409:
---------------------------------
    Labels:   (was: stale-assigned)

> Add combiner packing to graph optimizer phases
> ----------------------------------------------
>
>                 Key: BEAM-10409
>                 URL: https://issues.apache.org/jira/browse/BEAM-10409
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-core
>            Reporter: Yifan Mai
>            Priority: P2
>          Time Spent: 6.5h
>  Remaining Estimate: 0h
>
> Some use cases of Beam (e.g. [TensorFlow Transform|https://github.com/tensorflow/transform]) create thousands of Combine stages with a common parent. The large number of stages can cause performance issues on some runners. To alleviate, a graph optimization phase could be added to the translations module that packs compatible Combine stages into a single stage.
> The graph optimization for CombinePerKey would work as follows: If CombinePerKey stages have a common input, one input each, and one output each, pack the stages into a single stage that runs all CombinePerKeys and outputs resulting tuples to a new PCollection. A subsequent stage unpacks tuples from this PCollection and sends them to the original output PCollections.
> There is an additional issue with supporting this for CombineGlobally: because of the intermediate KeyWithVoid stage between the CombinePerKey stages and the input stage, the CombinePerKey stages do not have a common input stage, and cannot be packed. To support CombineGlobally, a common sibling elimination graph optimization phase can be used to combine the KeyWithVoid stages. After this, the CombinePerKey stages would have a common input and can be packed.



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