[GitHub] [spark] dongjoon-hyun commented on a change in pull request #27478: [SPARK-25829][SQL] Add config `spark.sql.deduplicateMapKey.lastWinsPolicy.enabled` and change the default behavior

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dongjoon-hyun commented on a change in pull request #27478: [SPARK-25829][SQL] Add config `spark.sql.deduplicateMapKey.lastWinsPolicy.enabled` and change the default behavior
URL: https://github.com/apache/spark/pull/27478#discussion_r376213630
 
 

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 File path: docs/sql-migration-guide.md
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 @@ -49,7 +49,7 @@ license: |
 
   - In Spark version 2.4 and earlier, float/double -0.0 is semantically equal to 0.0, but -0.0 and 0.0 are considered as different values when used in aggregate grouping keys, window partition keys and join keys. Since Spark 3.0, this bug is fixed. For example, `Seq(-0.0, 0.0).toDF("d").groupBy("d").count()` returns `[(0.0, 2)]` in Spark 3.0, and `[(0.0, 1), (-0.0, 1)]` in Spark 2.4 and earlier.
 
-  - In Spark version 2.4 and earlier, users can create a map with duplicated keys via built-in functions like `CreateMap`, `StringToMap`, etc. The behavior of map with duplicated keys is undefined, e.g. map look up respects the duplicated key appears first, `Dataset.collect` only keeps the duplicated key appears last, `MapKeys` returns duplicated keys, etc. Since Spark 3.0, these built-in functions will remove duplicated map keys with last wins policy. Users may still read map values with duplicated keys from data sources which do not enforce it (e.g. Parquet), the behavior will be undefined.
+  - In Spark version 2.4 and earlier, users can create a map with duplicated keys via built-in functions like `CreateMap`, `StringToMap`, etc. The behavior of map with duplicated keys is undefined, e.g. map look up respects the duplicated key appears first, `Dataset.collect` only keeps the duplicated key appears last, `MapKeys` returns duplicated keys, etc. Since Spark 3.0, new config `spark.sql.deduplicateMapKey.lastWinsPolicy.enabled` was added, with the default value `false`, Spark will throw RuntimeException while duplicated keys are found. If set to `true`, these built-in functions will remove duplicated map keys with last wins policy. Users may still read map values with duplicated keys from data sources which do not enforce it (e.g. Parquet), the behavior will be undefined.
 
 Review comment:
   Hi, @cloud-fan , @gatorsmile , @rxin , @marmbrus .
   So, `RuntimeException by default` is better in Apache Spark 3.0.0?

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