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https://issues.apache.org/jira/browse/BEAM-11747?focusedWorklogId=553996&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-553996
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ASF GitHub Bot logged work on BEAM-11747:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 18/Feb/21 00:42
Start Date: 18/Feb/21 00:42
Worklog Time Spent: 10m
Work Description: amaliujia commented on pull request #13898:
URL: https://github.com/apache/beam/pull/13898#issuecomment-780950443
Calcite does more for built-in operators than UDF. Using CAST as an example:
https://github.com/apache/calcite/blob/d815dc1209c3cc0728941e9fc81fce7d9e44c79b/core/src/main/java/org/apache/calcite/adapter/enumerable/RexToLixTranslator.java#L248
.
For UDF, fortunately, Calcite does less. Basically Calcite will either
generate the string representation of a value (i.e. Literal) or make a Row
field access (i.e. column), and then make a reflection call on the UDF
implementation. So for UDF, I think we only need to verify 1) whether Calcite
does anything that make the value lose precision 2) whether Calcite generates a
correct string representation for value or make correct field access to Row.
The verification work will be much less compared to checking the built-in
operators.
I agree this PR could be an upper bound for the limitation of Java UDF, what
I want to see is whether we can do better.
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Issue Time Tracking
-------------------
Worklog Id: (was: 553996)
Time Spent: 7h 50m (was: 7h 40m)
> Reject the mixed Java UDF and ZetaSQL builtin operators cases
> --------------------------------------------------------------
>
> Key: BEAM-11747
> URL: https://issues.apache.org/jira/browse/BEAM-11747
> Project: Beam
> Issue Type: Sub-task
> Components: dsl-sql-zetasql
> Reporter: Rui Wang
> Assignee: Rui Wang
> Priority: P2
> Time Spent: 7h 50m
> Remaining Estimate: 0h
>
> Before we have Calc splitting implemented, we can reject the mixed Java UDF
> and ZetaSQL builtin operators cases to maintain the correctness of a query.
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