Backport ANSI skipped-operand fix for arithmetic and concat to branch-1.2

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难度
4/5
预计耗时
3-5 天
新手友好度
35/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
活跃
技术栈
rust, scala
领域
backend, databases

调研方向

Read docs/source/contributor-guide/backporting.md and compare the branch-1.2 implementation using NullShortCircuit with the fix proposed in PR 7456, which depends on LazyLogical from PR 7326. Reproduce the ANSI-mode query in the issue and investigate whether wrapping operands gives Spark-compatible results and what performance tradeoff it introduces. Done means proposing and implementing a viable backport approach with correctness and performance addressed.

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描述

area:expressions bug priority:medium
Describe the bug

branch-1.2 has the ANSI bug from https://github.com/apache/datafusion-comet/issues/7246 for arithmetic and concat: native Comet evaluates an operand on rows where Spark skips it, so a query Spark answers fails with CAST_INVALID_INPUT. For example, with spark.sql.ansi.enabled=true:

CREATE TABLE t(n int, txt string) USING parquet;
INSERT INTO t VALUES (NULL, 'bad'), (3, '6');
SELECT n + CAST(txt AS INT) FROM t;  -- Spark: NULL, 9. Comet: CAST_INVALID_INPUT

The fix on main is https://github.com/apache/datafusion-comet/pull/7456 (not merged yet). It cannot be cherry-picked as is: it builds on https://github.com/apache/datafusion-comet/pull/7326 (LazyLogical, speculative evaluation), which branch-1.2 does not have. branch-1.2 does have NullShortCircuit (https://github.com/apache/datafusion-comet/pull/6716), so a backport could wrap the operands without speculation.

This issue tracks whether, and how, to backport the fix to branch-1.2, as docs/source/contributor-guide/backporting.md asks for a correctness fix.

Steps to reproduce

Run the query above on branch-1.2 with ANSI mode on.

Expected behavior

Comet returns the same result as Spark: NULL where n is NULL, without evaluating CAST(txt AS INT) there.

Additional context
Willingness to contribute

I can contribute a fix for this bug independently

主要语言
Scala
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环境准备

从这里开始

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  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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