spark-reviews mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From dongjoon-hyun <>
Subject [GitHub] spark pull request #15868: [SPARK-18413][SQL] Control the number of JDBC con...
Date Mon, 14 Nov 2016 18:07:15 GMT
Github user dongjoon-hyun commented on a diff in the pull request:
    --- 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](
    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 or file a JIRA ticket
with INFRA.

To unsubscribe, e-mail:
For additional commands, e-mail:

View raw message