HyukjinKwon commented on code in PR #36726:
URL: https://github.com/apache/spark/pull/36726#discussion_r884667716
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala:
##########
@@ -226,6 +226,9 @@ class JDBCOptions(
// The prefix that is added to the query sent to the JDBC database.
// This is required to support some complex queries with some JDBC databases.
val prepareQuery = parameters.get(JDBC_PREPARE_QUERY).map(_ + "
").getOrElse("")
+
+ // Infers timestamp values as TimestampNTZ type when reading data.
+ val inferTimestampNTZType = parameters.getOrElse(JDBC_INFER_TIMESTAMP_NTZ,
"false").toBoolean
Review Comment:
Should we maybe check if `spark.sql.timestampType` is `TIMESTAMP_NTZ` if
`inferTimestampNTZType` is not set? That's how CSV type inference and Python
type inference do.
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala:
##########
@@ -226,6 +226,9 @@ class JDBCOptions(
// The prefix that is added to the query sent to the JDBC database.
// This is required to support some complex queries with some JDBC databases.
val prepareQuery = parameters.get(JDBC_PREPARE_QUERY).map(_ + "
").getOrElse("")
+
+ // Infers timestamp values as TimestampNTZ type when reading data.
+ val inferTimestampNTZType = parameters.getOrElse(JDBC_INFER_TIMESTAMP_NTZ,
"false").toBoolean
Review Comment:
cc @gengliangwang FYI
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