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Posted to issues@spark.apache.org by "XiDuo You (Jira)" <ji...@apache.org> on 2022/05/27 08:22:00 UTC

[jira] [Created] (SPARK-39315) Refactor PromotePrecision and CheckOverflow with decimal binary arithmetic

XiDuo You created SPARK-39315:
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             Summary: Refactor PromotePrecision and CheckOverflow with decimal binary arithmetic
                 Key: SPARK-39315
                 URL: https://issues.apache.org/jira/browse/SPARK-39315
             Project: Spark
          Issue Type: Umbrella
          Components: SQL
    Affects Versions: 3.4.0
            Reporter: XiDuo You


For a decimal binary arithmetic expression, we correct its runtime data type and result data type at DecimalPrecision. It has two drawback:
 # it has some bug with the different ordering of the rules in TypeCoercion
 # it's unnecessary to change its runtime data type for decimal, as it supports eval with different precision. So what we need to do is change the result type precision.

 



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