Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/15596#discussion_r84706830
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScanExec.scala
---
@@ -47,6 +50,22 @@ case class LocalTableScanExec(
private lazy val rdd = sqlContext.sparkContext.parallelize(unsafeRows,
numParallelism)
+ protected override def doProduce(ctx: CodegenContext): String = {
--- End diff --
Let `LocalTableScanExec` support whole stage codegen.
Because `CollectLimitExec` now supports whole stage codegen, the test in
`SQLMetricsSuite`:
val df2 = spark.createDataset(Seq(1, 2, 3)).limit(2)
df2.collect()
val metrics2 =
df2.queryExecution.executedPlan.collectLeaves().head.metrics
assert(metrics2.contains("numOutputRows"))
assert(metrics2("numOutputRows").value === 2)
will execute the `LocalTableScanExec` node to get its RDD. Then an
InputAdapter will connect it to `CollectLimitExec`'s whole stage codegen node.
So it will output all 3 rows in the local table.
Adding this whole stage code support seems straightforward. So I adds it
here to pass the tests.
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