Github user ConeyLiu commented on a diff in the pull request:
https://github.com/apache/spark/pull/20844#discussion_r176327636
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
---
@@ -348,6 +348,13 @@ case class RangeExec(range:
org.apache.spark.sql.catalyst.plans.logical.Range)
override lazy val metrics = Map(
"numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of
output rows"))
+ /** Specifies how data is partitioned across different nodes in the
cluster. */
+ override def outputPartitioning: Partitioning = if (numSlices == 1 &&
numElements != 0) {
--- End diff --
This related to the [UT
error](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/88474/testReport/org.apache.spark.sql/DataFrameRangeSuite/SPARK_7150_range_api/).
`spark.range(-10, -9, -20, 1).count()` faild when `codegen` set to true and
`RangeExec.outputPartitioning' set to `SinglePartition`. I try to found the
root reason, but failed.
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