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[SPARK-26151][SQL][FOLLOWUP] Return partial results for bad CSV records #23235

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[SPARK-26151][SQL][FOLLOWUP] Return partial results for bad CSV records #23235

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Updating the migration guide
MaxGekk Dec 5, 2018
463f9e1
Removing the part about StructType
MaxGekk Dec 5, 2018
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2 changes: 2 additions & 0 deletions docs/sql-migration-guide-upgrade.md
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Expand Up @@ -35,6 +35,8 @@ displayTitle: Spark SQL Upgrading Guide

- Since Spark 3.0, CSV datasource uses java.time API for parsing and generating CSV content. New formatting implementation supports date/timestamp patterns conformed to ISO 8601. To switch back to the implementation used in Spark 2.4 and earlier, set `spark.sql.legacy.timeParser.enabled` to `true`.

- In Spark version 2.4 and earlier, CSV datasource converts a malformed CSV string to a row with all `null`s in the PERMISSIVE mode. Since Spark 3.0, returned row can contain non-`null` fields if some of CSV column values were parsed and converted to desired types successfully.

## Upgrading From Spark SQL 2.3 to 2.4

- In Spark version 2.3 and earlier, the second parameter to array_contains function is implicitly promoted to the element type of first array type parameter. This type promotion can be lossy and may cause `array_contains` function to return wrong result. This problem has been addressed in 2.4 by employing a safer type promotion mechanism. This can cause some change in behavior and are illustrated in the table below.
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