[jira] [Updated] (SPARK-28478) Optimizer rule to remove unnecessary explicit null checks for null-intolerant expressions (e.g. if(x is null, x, f(x)))
[
https://issues.apache.org/jira/browse/SPARK-28478?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dongjoon Hyun updated SPARK-28478:
--
Affects Version/s: (was: 3.0.0)
3.1.0
> Optimizer rule to remove unnecessary explicit null checks for null-intolerant
> expressions (e.g. if(x is null, x, f(x)))
> ---
>
> Key: SPARK-28478
> URL: https://issues.apache.org/jira/browse/SPARK-28478
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 3.1.0
>Reporter: Josh Rosen
>Priority: Major
>
> I ran across a family of expressions like
> {code:java}
> if(x is null, x, substring(x, 0, 1024)){code}
> or
> {code:java}
> when($"x".isNull, $"x", substring($"x", 0, 1024)){code}
> that were written this way because the query author was unsure about whether
> {{substring}} would return {{null}} when its input string argument is null.
> This explicit null-handling is unnecessary and adds bloat to the generated
> code, especially if it's done via a {{CASE}} statement (which compiles down
> to a {{do-while}} loop).
> In another case I saw a query compiler which automatically generated this
> type of code.
> It would be cool if Spark could automatically optimize such queries to remove
> these redundant null checks. Here's a sketch of what such a rule might look
> like (assuming that SPARK-28477 has been implement so we only need to worry
> about the {{IF}} case):
> * In the pattern match, check the following three conditions in the
> following order (to benefit from short-circuiting)
> ** The {{IF}} condition is an explicit null-check of a column {{c}}
> ** The {{true}} expression returns either {{c}} or {{null}}
> ** The {{false}} expression is a _null-intolerant_ expression with {{c}} as
> a _direct_ child.
> * If this condition matches, replace the entire {{If}} with the {{false}}
> branch's expression..
>
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[jira] [Updated] (SPARK-28478) Optimizer rule to remove unnecessary explicit null checks for null-intolerant expressions (e.g. if(x is null, x, f(x)))
[
https://issues.apache.org/jira/browse/SPARK-28478?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dongjoon Hyun updated SPARK-28478:
--
Component/s: (was: Optimizer)
> Optimizer rule to remove unnecessary explicit null checks for null-intolerant
> expressions (e.g. if(x is null, x, f(x)))
> ---
>
> Key: SPARK-28478
> URL: https://issues.apache.org/jira/browse/SPARK-28478
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Josh Rosen
>Priority: Major
>
> I ran across a family of expressions like
> {code:java}
> if(x is null, x, substring(x, 0, 1024)){code}
> or
> {code:java}
> when($"x".isNull, $"x", substring($"x", 0, 1024)){code}
> that were written this way because the query author was unsure about whether
> {{substring}} would return {{null}} when its input string argument is null.
> This explicit null-handling is unnecessary and adds bloat to the generated
> code, especially if it's done via a {{CASE}} statement (which compiles down
> to a {{do-while}} loop).
> In another case I saw a query compiler which automatically generated this
> type of code.
> It would be cool if Spark could automatically optimize such queries to remove
> these redundant null checks. Here's a sketch of what such a rule might look
> like (assuming that SPARK-28477 has been implement so we only need to worry
> about the {{IF}} case):
> * In the pattern match, check the following three conditions in the
> following order (to benefit from short-circuiting)
> ** The {{IF}} condition is an explicit null-check of a column {{c}}
> ** The {{true}} expression returns either {{c}} or {{null}}
> ** The {{false}} expression is a _null-intolerant_ expression with {{c}} as
> a _direct_ child.
> * If this condition matches, replace the entire {{If}} with the {{false}}
> branch's expression..
>
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