Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/13496#discussion_r66729833
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -452,6 +452,17 @@ class Analyzer(
def apply(plan: LogicalPlan): LogicalPlan = plan resolveOperators {
case i @ InsertIntoTable(u: UnresolvedRelation, parts, child, _, _)
if child.resolved =>
+ // 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.
+ val input = if (parts.nonEmpty) {
+ val (inputPartCols, inputDataCols) = child.output.partition {
attr =>
+ parts.contains(attr.name)
+ }
+ Project(inputDataCols ++ inputPartCols, child)
+ } else {
+ child
+ }
--- End diff --
Looks like Hive uses ordering not name to take dynamic partition columns. I
am not sure if we want to completely follow this Hive behavior.
DataFrameWriter's insertInto doesn't follow this. Besides, the rule in Analyzer
is not completely follow this too.
@liancheng @rxin @cloud-fan What do you think? Do you think we should
change current behavior to follow Hive?
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