Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/19092#discussion_r136251106
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLMetricsSuite.scala
---
@@ -17,112 +17,10 @@
package org.apache.spark.sql.hive.execution
-import java.io.File
-
-import org.apache.spark.sql.catalyst.TableIdentifier
-import org.apache.spark.sql.functions._
+import org.apache.spark.sql.execution.metric.SQLMetricsTestUtils
import org.apache.spark.sql.hive.test.TestHiveSingleton
-import org.apache.spark.sql.test.SQLTestUtils
-import org.apache.spark.util.Utils
-
-class SQLMetricsSuite extends SQLTestUtils with TestHiveSingleton {
- import spark.implicits._
-
- /**
- * Get execution metrics for the SQL execution and verify metrics values.
- *
- * @param metricsValues the expected metric values (numFiles,
numPartitions, numOutputRows).
- * @param func the function can produce execution id after running.
- */
- private def verifyWriteDataMetrics(metricsValues: Seq[Int])(func: =>
Unit): Unit = {
- val previousExecutionIds =
spark.sharedState.listener.executionIdToData.keySet
- // Run the given function to trigger query execution.
- func
- spark.sparkContext.listenerBus.waitUntilEmpty(10000)
- val executionIds =
-
spark.sharedState.listener.executionIdToData.keySet.diff(previousExecutionIds)
- assert(executionIds.size == 1)
- val executionId = executionIds.head
-
- val executionData =
spark.sharedState.listener.getExecution(executionId).get
- val executedNode = executionData.physicalPlanGraph.nodes.head
-
- val metricsNames = Seq(
- "number of written files",
- "number of dynamic part",
- "number of output rows")
-
- val metrics =
spark.sharedState.listener.getExecutionMetrics(executionId)
-
- metricsNames.zip(metricsValues).foreach { case (metricsName, expected)
=>
- val sqlMetric = executedNode.metrics.find(_.name == metricsName)
- assert(sqlMetric.isDefined)
- val accumulatorId = sqlMetric.get.accumulatorId
- val metricValue = metrics(accumulatorId).replaceAll(",", "").toInt
- assert(metricValue == expected)
- }
-
- val totalNumBytesMetric = executedNode.metrics.find(_.name == "bytes
of written output").get
- val totalNumBytes =
metrics(totalNumBytesMetric.accumulatorId).replaceAll(",", "").toInt
- assert(totalNumBytes > 0)
- }
-
- private def testMetricsNonDynamicPartition(
- dataFormat: String,
- tableName: String): Unit = {
- withTable(tableName) {
- Seq((1, 2)).toDF("i", "j")
- .write.format(dataFormat).mode("overwrite").saveAsTable(tableName)
-
- val tableLocation =
- new
File(spark.sessionState.catalog.getTableMetadata(TableIdentifier(tableName)).location)
- // 2 files, 100 rows, 0 dynamic partition.
- verifyWriteDataMetrics(Seq(2, 0, 100)) {
- (0 until 100).map(i => (i, i + 1)).toDF("i", "j").repartition(2)
- .write.format(dataFormat).mode("overwrite").insertInto(tableName)
- }
-
assert(Utils.recursiveList(tableLocation).count(_.getName.startsWith("part-"))
== 2)
- }
- }
-
- private def testMetricsDynamicPartition(
- provider: String,
- dataFormat: String,
- tableName: String): Unit = {
- withTempPath { dir =>
- spark.sql(
- s"""
- |CREATE TABLE $tableName(a int, b int)
- |USING $provider
- |PARTITIONED BY(a)
- |LOCATION '${dir.toURI}'
- """.stripMargin)
- val table =
spark.sessionState.catalog.getTableMetadata(TableIdentifier(tableName))
- assert(table.location == makeQualifiedPath(dir.getAbsolutePath))
-
- val df = spark.range(start = 0, end = 40, step = 1, numPartitions =
1)
- .selectExpr("id a", "id b")
-
- // 40 files, 80 rows, 40 dynamic partitions.
- verifyWriteDataMetrics(Seq(40, 40, 80)) {
- df.union(df).repartition(2, $"a")
- .write
- .format(dataFormat)
- .mode("overwrite")
- .insertInto(tableName)
- }
- assert(Utils.recursiveList(dir).count(_.getName.startsWith("part-"))
== 40)
- }
- }
-
- test("writing data out metrics: parquet") {
- testMetricsNonDynamicPartition("parquet", "t1")
- }
-
- test("writing data out metrics with dynamic partition: parquet") {
--- End diff --
The above two test cases are moved to
`sql/execution/metric/SQLMetricsSuite.scala`
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