Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/23235#discussion_r239049825
--- Diff: docs/sql-migration-guide-upgrade.md ---
@@ -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 if specified schema
is `StructType`. 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.
--- End diff --
Ah, `from_csv` and `to_csv` are added in 3.0 so it's intentionally not
mentioned. BTW, I think CSV functionalities can only have `StructType` so maybe
we don't have to mention.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
