Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/1072#discussion_r13736739
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala
---
@@ -55,14 +66,26 @@ private[sql] case class InMemoryColumnarTableScan(
cached.count()
cached
}
+}
+
+private[sql] case class InMemoryColumnarTableScan(
+ attributes: Seq[Attribute],
+ relation: InMemoryRelation)
+ extends LeafNode {
+
+ override def output: Seq[Attribute] = attributes
override def execute() = {
- cachedColumnBuffers.mapPartitions { iterator =>
+ relation.cachedColumnBuffers.mapPartitions { iterator =>
val columnBuffers = iterator.next()
assert(!iterator.hasNext)
new Iterator[Row] {
- val columnAccessors = columnBuffers.map(ColumnAccessor(_))
+ // Find the ordinals of the requested columns. If none are
requested, use the first.
+ val requestedColumns =
+ if (attributes.isEmpty) Seq(0) else
attributes.map(relation.output.indexOf(_))
--- End diff --
Correct.
That sounds like a nice optimization for a future PR :) Really at that
point we might special case COUNT such that we just get that statistic instead
of calling next() `n` times.
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