[SPARK-32822][SQL] Change the number of partitions to zero when a ran…

…ge is empty with WholeStageCodegen disabled or falled back

### What changes were proposed in this pull request?

This PR changes the behavior of RangeExec with WholeStageCodegen disabled or falled back to change the number of partitions to zero when a range is empty.

In the current master, if WholeStageCodegen effects, the number of partitions of an empty range will be changed to zero.
```
spark.range(1, 1, 1, 1000).rdd.getNumPartitions
res0: Int = 0
```
But it doesn't if WholeStageCodegen is disabled or falled back.
```
spark.conf.set("spark.sql.codegen.wholeStage", false)
spark.range(1, 1, 1, 1000).rdd.getNumPartitions
res2: Int = 1000
```

### Why are the changes needed?

To archive better performance even though WholeStageCodegen disabled or falled back.

### Does this PR introduce _any_ user-facing change?

Yes. the number of partitions gotten with `getNumPartitions` for an empty range will be changed when WholeStageCodegen is disabled.

### How was this patch tested?

New test.

Closes #29681 from sarutak/zero-size-range.

Authored-by: Kousuke Saruta <[email protected]>
Signed-off-by: Takeshi Yamamuro <[email protected]>

sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala

@@ -371,6 +371,7 @@ case class RangeExec(range: org.apache.spark.sql.catalyst.plans.logical.Range)
   val step: Long = range.step
   val numSlices: Int = range.numSlices.getOrElse(sparkContext.defaultParallelism)
   val numElements: BigInt = range.numElements
+  val isEmptyRange: Boolean = start == end || (start < end ^ 0 < step)
 
   override val output: Seq[Attribute] = range.output
 
@@ -396,7 +397,7 @@ case class RangeExec(range: org.apache.spark.sql.catalyst.plans.logical.Range)
   }
 
   override def inputRDDs(): Seq[RDD[InternalRow]] = {
-    val rdd = if (start == end || (start < end ^ 0 < step)) {
+    val rdd = if (isEmptyRange) {
       new EmptyRDD[InternalRow](sqlContext.sparkContext)
     } else {
       sqlContext.sparkContext.parallelize(0 until numSlices, numSlices).map(i => InternalRow(i))
@@ -562,58 +563,64 @@ case class RangeExec(range: org.apache.spark.sql.catalyst.plans.logical.Range)
 
   protected override def doExecute(): RDD[InternalRow] = {
     val numOutputRows = longMetric("numOutputRows")
-    sqlContext
-      .sparkContext
-      .parallelize(0 until numSlices, numSlices)
-      .mapPartitionsWithIndex { (i, _) =>
-        val partitionStart = (i * numElements) / numSlices * step + start
-        val partitionEnd = (((i + 1) * numElements) / numSlices) * step + start
-        def getSafeMargin(bi: BigInt): Long =
-          if (bi.isValidLong) {
-            bi.toLong
-          } else if (bi > 0) {
-            Long.MaxValue
-          } else {
-            Long.MinValue
-          }
-        val safePartitionStart = getSafeMargin(partitionStart)
-        val safePartitionEnd = getSafeMargin(partitionEnd)
-        val rowSize = UnsafeRow.calculateBitSetWidthInBytes(1) + LongType.defaultSize
-        val unsafeRow = UnsafeRow.createFromByteArray(rowSize, 1)
-        val taskContext = TaskContext.get()
-
-        val iter = new Iterator[InternalRow] {
-          private[this] var number: Long = safePartitionStart
-          private[this] var overflow: Boolean = false
-          private[this] val inputMetrics = taskContext.taskMetrics().inputMetrics
-
-          override def hasNext =
-            if (!overflow) {
-              if (step > 0) {
-                number < safePartitionEnd
-              } else {
-                number > safePartitionEnd
-              }
-            } else false
-
-          override def next() = {
-            val ret = number
-            number += step
-            if (number < ret ^ step < 0) {
-              // we have Long.MaxValue + Long.MaxValue < Long.MaxValue
-              // and Long.MinValue + Long.MinValue > Long.MinValue, so iff the step causes a step
-              // back, we are pretty sure that we have an overflow.
-              overflow = true
+    if (isEmptyRange) {
+      new EmptyRDD[InternalRow](sqlContext.sparkContext)
+    } else {
+      sqlContext
+        .sparkContext
+        .parallelize(0 until numSlices, numSlices)
+        .mapPartitionsWithIndex { (i, _) =>
+          val partitionStart = (i * numElements) / numSlices * step + start
+          val partitionEnd = (((i + 1) * numElements) / numSlices) * step + start
+
+          def getSafeMargin(bi: BigInt): Long =
+            if (bi.isValidLong) {
+              bi.toLong
+            } else if (bi > 0) {
+              Long.MaxValue
+            } else {
+              Long.MinValue
             }
 
-            numOutputRows += 1
-            inputMetrics.incRecordsRead(1)
-            unsafeRow.setLong(0, ret)
-            unsafeRow
+          val safePartitionStart = getSafeMargin(partitionStart)
+          val safePartitionEnd = getSafeMargin(partitionEnd)
+          val rowSize = UnsafeRow.calculateBitSetWidthInBytes(1) + LongType.defaultSize
+          val unsafeRow = UnsafeRow.createFromByteArray(rowSize, 1)
+          val taskContext = TaskContext.get()
+
+          val iter = new Iterator[InternalRow] {
+            private[this] var number: Long = safePartitionStart
+            private[this] var overflow: Boolean = false
+            private[this] val inputMetrics = taskContext.taskMetrics().inputMetrics
+
+            override def hasNext =
+              if (!overflow) {
+                if (step > 0) {
+                  number < safePartitionEnd
+                } else {
+                  number > safePartitionEnd
+                }
+              } else false
+
+            override def next() = {
+              val ret = number
+              number += step
+              if (number < ret ^ step < 0) {
+                // we have Long.MaxValue + Long.MaxValue < Long.MaxValue
+                // and Long.MinValue + Long.MinValue > Long.MinValue, so iff the step causes a step
+                // back, we are pretty sure that we have an overflow.
+                overflow = true
+              }
+
+              numOutputRows += 1
+              inputMetrics.incRecordsRead(1)
+              unsafeRow.setLong(0, ret)
+              unsafeRow
+            }
           }
+          new InterruptibleIterator(taskContext, iter)
         }
-        new InterruptibleIterator(taskContext, iter)
-      }
+    }
   }
 
   override def simpleString(maxFields: Int): String = {

sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala

@@ -994,6 +994,13 @@ class PlannerSuite extends SharedSparkSession with AdaptiveSparkPlanHelper {
       }
     }
   }
+
+  testWithWholeStageCodegenOnAndOff("Change the number of partitions to zero " +
+    "when a range is empty") { _ =>
+    val range = spark.range(1, 1, 1, 1000)
+    val numPartitions = range.rdd.getNumPartitions
+    assert(numPartitions == 0)
+  }
 }
 
 // Used for unit-testing EnsureRequirements