[jira] [Created] (SPARK-29881) Introduce API for manually breaking up dataset plan

["Devyn Cairns (Jira)" <ji...@apache.org>]

Devyn Cairns created SPARK-29881:
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             Summary: Introduce API for manually breaking up dataset plan
                 Key: SPARK-29881
                 URL: https://issues.apache.org/jira/browse/SPARK-29881
             Project: Spark
          Issue Type: Wish
          Components: SQL
    Affects Versions: 2.4.4
            Reporter: Devyn Cairns


I have an interesting situation where I'm calling functions that are relatively expensive from Spark SQL, and then using the result several times in a loop through {{transform}}.

Although the WholeStageCodegen is usually helpful, it always calls expressions as they're used, which means that in the case of, for example:

{{SELECT transform(sequence(0, 32), x -> expensive_result * x)}}
{{FROM (}}
{{  SELECT expensive_operation(foo) AS expensive_result FROM source}}
{{)}}

the expensive_operation function will almost certainly be called 32 times for each source row, without any explicit way to cache that value intermediately.

I've found a workaround for now is to insert something like {{.filter \{ _ => true }}} in the middle, which will create a barrier to whole-stage codegen without much negative impact, aside from preventing other optimizations like PushDown. This does indeed produce the intended result and expensive_operation is only run once.

But it would be great to have an API on Dataset like {{.barrier()}} to introduce an explicit barrier to whole-stage codegen without adding any additional behavior or getting in the way of any PushDown optimizations.



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