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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/11/03 13:52:32 UTC
[GitHub] [spark] AngersZhuuuu commented on a change in pull request #30202: [SPARK-33248][SQL][FOLLOWUP] Update migration guide to make clear what behavior changed and make variable names and configuration name more clearer
AngersZhuuuu commented on a change in pull request #30202:
URL: https://github.com/apache/spark/pull/30202#discussion_r515933291
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File path: docs/sql-migration-guide.md
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@@ -52,7 +52,7 @@ license: |
- In Spark 3.1, the `schema_of_json` and `schema_of_csv` functions return the schema in the SQL format in which field names are quoted. In Spark 3.0, the function returns a catalog string without field quoting and in lower case.
- - In Spark 3.1, when `spark.sql.legacy.transformationPadNullWhenValueLessThenSchema` is true, Spark will pad NULL value when script transformation's output value size less then schema size in default-serde mode(script transformation with row format of `ROW FORMAT DELIMITED`). If false, Spark will keep original behavior to throw `ArrayIndexOutOfBoundsException`.
+ - In Spark 3.1, when script transformation output's value size is less then schema size in default-serde mode(script transformation with row format of `ROW FORMAT DELIMITED`), Spark will pad NUll value to supplement data. In Spark 3.0 or earlier, Spark will do nothing and throw `ArrayIndexOutOfBoundsException`. To restore the behavior before Spark 3.1, you can set `spark.sql.legacy.transformationNotPadNullToSupplementData.enabled` to `true`.
Review comment:
So, What should I do next? Personally, we need to let users know about this change
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File path: docs/sql-migration-guide.md
##########
@@ -52,7 +52,7 @@ license: |
- In Spark 3.1, the `schema_of_json` and `schema_of_csv` functions return the schema in the SQL format in which field names are quoted. In Spark 3.0, the function returns a catalog string without field quoting and in lower case.
- - In Spark 3.1, when `spark.sql.legacy.transformationPadNullWhenValueLessThenSchema` is true, Spark will pad NULL value when script transformation's output value size less then schema size in default-serde mode(script transformation with row format of `ROW FORMAT DELIMITED`). If false, Spark will keep original behavior to throw `ArrayIndexOutOfBoundsException`.
+ - In Spark 3.1, when script transformation output's value size is less then schema size in default-serde mode(script transformation with row format of `ROW FORMAT DELIMITED`), Spark will pad NUll value to supplement data. In Spark 3.0 or earlier, Spark will do nothing and throw `ArrayIndexOutOfBoundsException`. To restore the behavior before Spark 3.1, you can set `spark.sql.legacy.transformationNotPadNullToSupplementData.enabled` to `true`.
Review comment:
All right, we can just revert last pr.
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