HyukjinKwon commented on a change in pull request #25605:
[SPARK-28730][SPARK-28495][SQL][FOLLOW-UP] Revise the doc of option
spark.sql.storeAssignmentPolicy
URL: https://github.com/apache/spark/pull/25605#discussion_r318437043
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -1643,12 +1643,16 @@ object SQLConf {
val STORE_ASSIGNMENT_POLICY =
buildConf("spark.sql.storeAssignmentPolicy")
.doc("When inserting a value into a column with different data type,
Spark will perform " +
- "type coercion. Currently we support 3 policies for the type coercion
rules: ansi, " +
- "legacy and strict. With ansi policy, Spark performs the type coercion
as per ANSI SQL. " +
- "With legacy policy, Spark allows casting any value to any data type.
" +
- "The legacy policy is the only behavior in Spark 2.x and it is
compatible with Hive. " +
+ "type coercion. Currently, we support 3 policies for the type coercion
rules: ANSI, " +
+ "legacy and strict. With ANSI policy, Spark performs the type coercion
as per ANSI SQL. " +
+ "In practice, it follows PostgreSQL. It disallows certain unreasonable
type conversions " +
Review comment:
Out of curiosity, should we mention PostgreSQL? For instance, if some
behaviours from PostgreSQL don't comply ANSI, and don't quite make sense to
Spark community, I think we might decide to don't follow just like we didn't
decided to don't add some PostgreSQL corresponding features.
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