Github user MaxGekk commented on a diff in the pull request:
https://github.com/apache/spark/pull/23253#discussion_r239998397
--- Diff: docs/sql-migration-guide-upgrade.md ---
@@ -37,6 +37,8 @@ displayTitle: Spark SQL Upgrading Guide
- 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.
+ - In Spark version 2.4 and earlier, JSON datasource and JSON functions
like `from_json` convert a bad JSON record to a row with all `null`s in the
PERMISSIVE mode when specified schema is `StructType`. Since Spark 3.0,
returned row can contain non-`null` fields if some of JSON column values were
parsed and converted to desired types successfully.
+
--- End diff --
In the `PERMISSIVE` mode, no way but at the moment (without the PR) you
cannot distinguish a row produced from a bad record from a row produced from
JSON object with all `null` fields too.
A row itself with all null cannot be an indicator of bad record. Need an
additional flag. `null` or non-`null` in the corrupt column plays such role.
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