[SPARK-26277][SQL][TEST] WholeStageCodegen metrics should be tested w…

…ith whole-stage codegen enabled

## What changes were proposed in this pull request?
In `org.apache.spark.sql.execution.metric.SQLMetricsSuite`, there's a test case named "WholeStageCodegen metrics". However, it is executed with whole-stage codegen disabled. This PR fixes this by enable whole-stage codegen for this test case.

## How was this patch tested?
Tested locally using exiting test cases.

Closes #23224 from seancxmao/codegen-metrics.

Authored-by: seancxmao <seancxmao@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>

sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsSuite.scala

@@ -77,11 +77,16 @@ class SQLMetricsSuite extends SparkFunSuite with SQLMetricsTestUtils with Shared
   }
 
   test("WholeStageCodegen metrics") {
-    // Assume the execution plan is
-    // WholeStageCodegen(nodeId = 0, Range(nodeId = 2) -> Filter(nodeId = 1))
+    // Assume the execution plan with node id is
+    // WholeStageCodegen(nodeId = 0)
+    //   Filter(nodeId = 1)
+    //     Range(nodeId = 2)
     // TODO: update metrics in generated operators
     val ds = spark.range(10).filter('id < 5)
-    testSparkPlanMetrics(ds.toDF(), 1, Map.empty)
+    testSparkPlanMetricsWithPredicates(ds.toDF(), 1, Map(
+      0L -> (("WholeStageCodegen", Map(
+        "duration total (min, med, max)" -> {_.toString.matches(timingMetricPattern)})))
+    ), true)
   }
 
   test("Aggregate metrics") {

sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsTestUtils.scala

@@ -144,6 +144,7 @@ trait SQLMetricsTestUtils extends SQLTestUtils {
    * @param df `DataFrame` to run
    * @param expectedNumOfJobs number of jobs that will run
    * @param expectedNodeIds the node ids of the metrics to collect from execution data.
+   * @param enableWholeStage enable whole-stage code generation or not.
    */
   protected def getSparkPlanMetrics(
        df: DataFrame,
@@ -210,13 +211,15 @@ trait SQLMetricsTestUtils extends SQLTestUtils {
    * @param expectedNumOfJobs number of jobs that will run
    * @param expectedMetricsPredicates the expected metrics predicates. The format is
    *                                  `nodeId -> (operatorName, metric name -> metric predicate)`.
+   * @param enableWholeStage enable whole-stage code generation or not.
    */
   protected def testSparkPlanMetricsWithPredicates(
       df: DataFrame,
       expectedNumOfJobs: Int,
-      expectedMetricsPredicates: Map[Long, (String, Map[String, Any => Boolean])]): Unit = {
+      expectedMetricsPredicates: Map[Long, (String, Map[String, Any => Boolean])],
+      enableWholeStage: Boolean = false): Unit = {
     val optActualMetrics =
-      getSparkPlanMetrics(df, expectedNumOfJobs, expectedMetricsPredicates.keySet)
+      getSparkPlanMetrics(df, expectedNumOfJobs, expectedMetricsPredicates.keySet, enableWholeStage)
     optActualMetrics.foreach { actualMetrics =>
       assert(expectedMetricsPredicates.keySet === actualMetrics.keySet)
       for ((nodeId, (expectedNodeName, expectedMetricsPredicatesMap))