Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/4336#discussion_r24053791
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrameImpl.scala
---
@@ -260,11 +260,11 @@ private[sql] class DataFrameImpl protected[sql](
override def take(n: Int): Array[Row] = head(n)
- override def collect(): Array[Row] =
queryExecution.executedPlan.executeCollect()
+ override def collect(): Array[Row] = rdd.collect()
override def collectAsList(): java.util.List[Row] =
java.util.Arrays.asList(rdd.collect() :_*)
- override def count(): Long =
groupBy().count().rdd.collect().head.getLong(0)
+ override def count(): Long = rdd.count()
--- End diff --
Oh? If I understand correctly, I think the rdd.count() is the most
optimized (partial aggregation is done in before shuffling). @rxin , can you
confirm that? Sorry If I am wrong.
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