Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/13766#discussion_r67610305
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala ---
@@ -245,29 +245,17 @@ final class DataFrameWriter[T] private[sql](ds:
Dataset[T]) {
if (partitioningColumns.isDefined) {
throw new AnalysisException(
"insertInto() can't be used together with partitionBy(). " +
- "Partition columns are defined by the table into which is being
inserted."
+ "Partition columns have already be defined for the table. " +
+ "It is not necessary to use partitionBy()."
)
}
- val partitions = normalizedParCols.map(_.map(col => col ->
Option.empty[String]).toMap)
- val overwrite = mode == SaveMode.Overwrite
-
- // A partitioned relation's schema can be different from the input
logicalPlan, since
- // partition columns are all moved after data columns. We Project to
adjust the ordering.
- // TODO: this belongs to the analyzer.
- val input = normalizedParCols.map { parCols =>
- val (inputPartCols, inputDataCols) = df.logicalPlan.output.partition
{ attr =>
- parCols.contains(attr.name)
- }
- Project(inputDataCols ++ inputPartCols, df.logicalPlan)
- }.getOrElse(df.logicalPlan)
-
--- End diff --
These lines are not needed because we do not allow users to use partitionBy
with insertInto together.
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