[MINOR][SQL] Fix versions in the SQL migration guide for Spark 3.1
### What changes were proposed in this pull request? Change _To restore the behavior before Spark **3.0**_ to _To restore the behavior before Spark **3.1**_ in the SQL migration guide while telling about the behaviour before new version 3.1. ### Why are the changes needed? To have correct info in the SQL migration guide. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? N/A Closes #29336 from MaxGekk/fix-version-in-sql-migration. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
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## Upgrading from Spark SQL 3.0 to 3.1
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- In Spark 3.1, grouping_id() returns long values. In Spark version 3.0 and earlier, this function returns int values. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.integerGroupingId` to `true`.
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- In Spark 3.1, grouping_id() returns long values. In Spark version 3.0 and earlier, this function returns int values. To restore the behavior before Spark 3.1, you can set `spark.sql.legacy.integerGroupingId` to `true`.
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- In Spark 3.1, SQL UI data adopts the `formatted` mode for the query plan explain results. To restore the behavior before Spark 3.0, you can set `spark.sql.ui.explainMode` to `extended`.
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- In Spark 3.1, SQL UI data adopts the `formatted` mode for the query plan explain results. To restore the behavior before Spark 3.1, you can set `spark.sql.ui.explainMode` to `extended`.
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- In Spark 3.1, `from_unixtime`, `unix_timestamp`,`to_unix_timestamp`, `to_timestamp` and `to_date` will fail if the specified datetime pattern is invalid. In Spark 3.0 or earlier, they result `NULL`.
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