Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/15868#discussion_r87857574
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
---
@@ -667,9 +667,15 @@ object JdbcUtils extends Logging {
val getConnection: () => Connection = createConnectionFactory(options)
val batchSize = options.batchSize
val isolationLevel = options.isolationLevel
- df.foreachPartition(iterator => savePartition(
- getConnection, table, iterator, rddSchema, nullTypes, batchSize,
dialect, isolationLevel)
- )
+ if (options.numPartitions != null && options.numPartitions.toInt !=
df.rdd.getNumPartitions) {
+
df.repartition(options.numPartitions.toInt).foreachPartition(iterator =>
savePartition(
--- End diff --
Thank you for review, @srowen .
First, the property `numPartitions` already exists in [JDBCOptions.scala:
Optional parameters only for
reading](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCOptions.scala#L73-L83).
This PR makes that option meaningful during write operation.
Second, for dataframe usecases, we can call `repartition` before saving to
manage this. Actually, I asked @lichenglin that way. But, the main purpose of
issue requested by @lichenglin is about providing pure SQL way to control the
number of partitions for writing. In SQL, this looks reasonable to me.
---
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
