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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2021/10/19 07:18:00 UTC
[jira] [Commented] (SPARK-37055) Apply 'compute.eager_check' across
all the codebase
[ https://issues.apache.org/jira/browse/SPARK-37055?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17430361#comment-17430361 ]
Hyukjin Kwon commented on SPARK-37055:
--------------------------------------
[~dchvn] please feel free to create JIRAs as sub-tasks, and proceed. This will be one of the large items in Spark 3.3 :-).
> Apply 'compute.eager_check' across all the codebase
> ---------------------------------------------------
>
> Key: SPARK-37055
> URL: https://issues.apache.org/jira/browse/SPARK-37055
> Project: Spark
> Issue Type: Umbrella
> Components: PySpark
> Affects Versions: 3.3.0
> Reporter: dch nguyen
> Priority: Major
>
> As [~hyukjin.kwon] guide
> 1 Make every input validation like this covered by the new configuration. For example:
> {code:python}
> - a == b
> + def eager_check(f): # Utility function
> + return not config.compute.eager_check and f()
> +
> + eager_check(lambda: a == b)
> {code}
> 2 We should check if the output makes sense although the behaviour is not matched with pandas'. If the output does not make sense, we shouldn't cover it with this configuration.
> 3 Make this configuration enabled by default so we match the behaviour to pandas' by default.
>
> We have to make sure listing which API is affected in the description of 'compute.eager_check'
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