Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14313#discussion_r72005085
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
---
@@ -322,46 +322,135 @@ private[sql] class JDBCRDD(
}
}
- // Each JDBC-to-Catalyst conversion corresponds to a tag defined here so
that
- // we don't have to potentially poke around in the Metadata once for
every
- // row.
- // Is there a better way to do this? I'd rather be using a type that
- // contains only the tags I define.
- abstract class JDBCConversion
- case object BooleanConversion extends JDBCConversion
- case object DateConversion extends JDBCConversion
- case class DecimalConversion(precision: Int, scale: Int) extends
JDBCConversion
- case object DoubleConversion extends JDBCConversion
- case object FloatConversion extends JDBCConversion
- case object IntegerConversion extends JDBCConversion
- case object LongConversion extends JDBCConversion
- case object BinaryLongConversion extends JDBCConversion
- case object StringConversion extends JDBCConversion
- case object TimestampConversion extends JDBCConversion
- case object BinaryConversion extends JDBCConversion
- case class ArrayConversion(elementConversion: JDBCConversion) extends
JDBCConversion
+ // A `JDBCConversion` is responsible for converting a value from
`ResultSet`
+ // to a value in a field for `InternalRow`.
+ private type JDBCConversion = (ResultSet, Int) => Any
--- End diff --
also explain what's the 2 arguments in the comment?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
