Profile/qualification tool error handling improvements and support spark < 3.1.1

rapids-4-spark-tools/README.md

@@ -9,7 +9,7 @@ Information such as Spark version, executor information, properties and so on. W
 (The code is based on Apache Spark 3.1.1 source code, and tested using Spark 3.0.x and 3.1.1 event logs)
 
 ## Prerequisites
-- Spark 3.1.1 or newer installed
+- Spark 3.0.1 or newer installed
 - Java 8 or above
 - Complete Spark event log(s) from Spark 3.0 or above version.
 

rapids-4-spark-tools/src/main/scala/com/nvidia/spark/rapids/tool/profiling/CollectInformation.scala

@@ -117,11 +117,15 @@ class CollectInformation(apps: ArrayBuffer[ApplicationInfo], fileWriter: FileWri
   def printSQLPlanMetrics(shouldGenDot: Boolean, outputDir: String,
       writeOutput: Boolean = true): Unit ={
     for (app <- apps){
-      val messageHeader = "\nSQL Plan Metrics for Application:\n"
-      val accums = app.runQuery(app.generateSQLAccums, fileWriter = Some(fileWriter),
-        messageHeader=messageHeader)
-      if (shouldGenDot) {
-        generateDot(outputDir, Some(accums))
+      if (app.allDataFrames.contains(s"sqlMetricsDF_${app.index}") &&
+        app.allDataFrames.contains(s"driverAccumDF_${app.index}") &&
+        app.allDataFrames.contains(s"taskStageAccumDF_${app.index}")) {
+        val messageHeader = "\nSQL Plan Metrics for Application:\n"
+        val accums = app.runQuery(app.generateSQLAccums, fileWriter = Some(fileWriter),
+          messageHeader=messageHeader)
+        if (shouldGenDot) {
+          generateDot(outputDir, Some(accums))
+        }
       }
     }
   }

rapids-4-spark-tools/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileMain.scala

@@ -71,37 +71,51 @@ object ProfileMain extends Logging {
     if (appArgs.compare()) {
       // Create an Array of Applications(with an index starting from 1)
       val apps: ArrayBuffer[ApplicationInfo] = ArrayBuffer[ApplicationInfo]()
-      var index: Int = 1
-      for (path <- allPaths.filter(p => !p.getName.contains("."))) {
-        apps += new ApplicationInfo(numOutputRows, sparkSession, path, index)
-        index += 1
-      }
-
-      //Exit if there are no applications to process.
-      if (apps.isEmpty) {
-        logInfo("No application to process. Exiting")
-        return 0
+      try {
+        var index: Int = 1
+        for (path <- allPaths.filter(p => !p.getName.contains("."))) {
+          apps += new ApplicationInfo(numOutputRows, sparkSession, path, index)
+          index += 1
+        }
+
+        //Exit if there are no applications to process.
+        if (apps.isEmpty) {
+          logInfo("No application to process. Exiting")
+          return 0
+        }
+        processApps(apps, generateDot = false)
+      } catch {
+        case e: com.fasterxml.jackson.core.JsonParseException =>
+          fileWriter.close()
+          logError(s"Error parsing JSON", e)
+          return 1
       }
-      processApps(apps, generateDot = false)
       // Show the application Id <-> appIndex mapping.
       for (app <- apps) {
         logApplicationInfo(app)
       }
     } else {
       // This mode is to process one application at one time.
       var index: Int = 1
-      for (path <- allPaths.filter(p => !p.getName.contains("."))) {
-        // This apps only contains 1 app in each loop.
-        val apps: ArrayBuffer[ApplicationInfo] = ArrayBuffer[ApplicationInfo]()
-        val app = new ApplicationInfo(numOutputRows, sparkSession, path, index)
-        apps += app
-        logApplicationInfo(app)
-        // This is a bit odd that we process apps individual right now due to
-        // memory concerns. So the aggregation functions only aggregate single
-        // application not across applications.
-        processApps(apps, appArgs.generateDot())
-        app.dropAllTempViews()
-        index += 1
+      try {
+        for (path <- allPaths.filter(p => !p.getName.contains("."))) {
+          // This apps only contains 1 app in each loop.
+          val apps: ArrayBuffer[ApplicationInfo] = ArrayBuffer[ApplicationInfo]()
+          val app = new ApplicationInfo(numOutputRows, sparkSession, path, index)
+          apps += app
+          logApplicationInfo(app)
+          // This is a bit odd that we process apps individual right now due to
+          // memory concerns. So the aggregation functions only aggregate single
+          // application not across applications.
+          processApps(apps, appArgs.generateDot())
+          app.dropAllTempViews()
+          index += 1
+        }
+      } catch {
+        case e: com.fasterxml.jackson.core.JsonParseException =>
+          fileWriter.close()
+          logError(s"Error parsing JSON", e)
+          return 1
       }
     }
 

rapids-4-spark-tools/src/main/scala/com/nvidia/spark/rapids/tool/qualification/Qualification.scala

@@ -41,17 +41,22 @@ object Qualification extends Logging {
       numRows: Int,
       sparkSession: SparkSession,
       includeCpuPercent: Boolean,
-      dropTempViews: Boolean): DataFrame = {
+      dropTempViews: Boolean): Option[DataFrame] = {
     var index: Int = 1
     val apps: ArrayBuffer[ApplicationInfo] = ArrayBuffer[ApplicationInfo]()
     for (path <- allPaths.filterNot(_.getName.contains("."))) {
-      // This apps only contains 1 app in each loop.
-      val app = new ApplicationInfo(numRows, sparkSession,
-        path, index, true)
-      apps += app
-      logApplicationInfo(app)
-      index += 1
+      try {
+        // This apps only contains 1 app in each loop.
+        val app = new ApplicationInfo(numRows, sparkSession, path, index, true)
+        apps += app
+        logApplicationInfo(app)
+        index += 1
+      } catch {
+        case e: com.fasterxml.jackson.core.JsonParseException =>
+          logWarning(s"Error parsing JSON, skipping $path")
+      }
     }
+    if (apps.isEmpty) return None
     val analysis = new Analysis(apps, None)
     if (includeCpuPercent) {
       val sqlAggMetricsDF = analysis.sqlMetricsAggregation()
@@ -65,7 +70,7 @@ object Qualification extends Logging {
       sparkSession.catalog.dropTempView("sqlAggMetricsDF")
       apps.foreach( _.dropAllTempViews())
     }
-    df
+    Some(df)
   }
 
   def constructQueryQualifyApps(apps: ArrayBuffer[ApplicationInfo],
@@ -78,8 +83,7 @@ object Qualification extends Logging {
           case false => "(" + app.qualificationDurationNoMetricsSQL + ")"
         }
       }.mkString(" union ")
-    val df = apps.head.runQuery(query + " order by Rank desc, `App Duration` desc")
-    df
+    apps.head.runQuery(query + " order by Score desc, `App Duration` desc")
   }
 
   def writeQualification(df: DataFrame, outputDir: String,

rapids-4-spark-tools/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualificationMain.scala

@@ -34,7 +34,7 @@ object QualificationMain extends Logging {
    */
   def main(args: Array[String]) {
     val sparkSession = ProfileUtils.createSparkSession
-    val (exitCode, optDf) = mainInternal(sparkSession, new QualificationArgs(args))
+    val (exitCode, _) = mainInternal(sparkSession, new QualificationArgs(args))
     if (exitCode != 0) {
       System.exit(exitCode)
     }
@@ -60,13 +60,13 @@ object QualificationMain extends Logging {
     }
     val includeCpuPercent = appArgs.includeExecCpuPercent.getOrElse(false)
     val numOutputRows = appArgs.numOutputRows.getOrElse(1000)
-    val df = Qualification.qualifyApps(allPaths,
+    val dfOpt = Qualification.qualifyApps(allPaths,
       numOutputRows, sparkSession, includeCpuPercent, dropTempViews)
-    if (writeOutput) {
-      Qualification.writeQualification(df, outputDirectory,
+    if (writeOutput && dfOpt.isDefined) {
+      Qualification.writeQualification(dfOpt.get, outputDirectory,
         appArgs.outputFormat.getOrElse("csv"), includeCpuPercent, numOutputRows)
     }
-    (0, Some(df))
+    (0, dfOpt)
   }
 
 }

rapids-4-spark-tools/src/main/scala/org/apache/spark/sql/rapids/tool/profiling/ApplicationInfo.scala

@@ -693,7 +693,7 @@ class ApplicationInfo(
     s"""select
        |first(appName) as `App Name`,
        |'$appId' as `App ID`,
-       |ROUND((sum(sqlQualDuration) * 100) / first(app.duration), 2) as Rank,
+       |ROUND((sum(sqlQualDuration) * 100) / first(app.duration), 2) as Score,
        |concat_ws(",", collect_list(problematic)) as `Potential Problems`,
        |sum(sqlQualDuration) as `SQL Dataframe Duration`,
        |first(app.duration) as `App Duration`
@@ -720,7 +720,7 @@ class ApplicationInfo(
   def qualificationDurationSumSQL: String = {
     s"""select first(appName) as `App Name`,
        |first(appID) as `App ID`,
-       |ROUND((sum(dfDuration) * 100) / first(appDuration), 2) as Rank,
+       |ROUND((sum(dfDuration) * 100) / first(appDuration), 2) as Score,
        |concat_ws(",", collect_list(potentialProblems)) as `Potential Problems`,
        |sum(dfDuration) as `SQL Dataframe Duration`,
        |first(appDuration) as `App Duration`,

rapids-4-spark-tools/src/main/scala/org/apache/spark/sql/rapids/tool/profiling/EventsProcessor.scala

@@ -34,9 +34,6 @@ object EventsProcessor extends Logging {
     event match {
       case _: SparkListenerLogStart =>
         doSparkListenerLogStart(app, event.asInstanceOf[SparkListenerLogStart])
-      case _: SparkListenerResourceProfileAdded =>
-        doSparkListenerResourceProfileAdded(app,
-          event.asInstanceOf[SparkListenerResourceProfileAdded])
       case _: SparkListenerBlockManagerAdded =>
         doSparkListenerBlockManagerAdded(app,
           event.asInstanceOf[SparkListenerBlockManagerAdded])
@@ -94,7 +91,33 @@ object EventsProcessor extends Logging {
       case _: SparkListenerSQLAdaptiveSQLMetricUpdates =>
         doSparkListenerSQLAdaptiveSQLMetricUpdates(app,
           event.asInstanceOf[SparkListenerSQLAdaptiveSQLMetricUpdates])
-      case _ => doOtherEvent(app, event)
+      case _ => 
+        val wasResourceProfileAddedEvent = doSparkListenerResourceProfileAddedReflect(app, event)
+        if (!wasResourceProfileAddedEvent) doOtherEvent(app, event)
+    }
+  }
+
+  def doSparkListenerResourceProfileAddedReflect(
+      app: ApplicationInfo,
+      event: SparkListenerEvent): Boolean = {
+    val rpAddedClass = "org.apache.spark.scheduler.SparkListenerResourceProfileAdded"
+    if (event.getClass.getName.equals(rpAddedClass)) {
+      try {
+        event match {
+          case _: SparkListenerResourceProfileAdded =>
+            doSparkListenerResourceProfileAdded(app,
+              event.asInstanceOf[SparkListenerResourceProfileAdded])
+            true
+          case _ => false
+        }
+      } catch {
+        case _: ClassNotFoundException =>
+          logWarning("Error trying to parse SparkListenerResourceProfileAdded, Spark" +
+            " version likely older than 3.1.X, unable to parse it properly.")
+          false
+      }
+    } else {
+      false
     }
   }
 

rapids-4-spark-tools/src/test/scala/com/nvidia/spark/rapids/tool/profiling/ApplicationInfoSuite.scala

@@ -23,7 +23,7 @@ import org.scalatest.FunSuite
 import scala.collection.mutable.ArrayBuffer
 
 import org.apache.spark.internal.Logging
-import org.apache.spark.sql.{DataFrame, SparkSession}
+import org.apache.spark.sql.{DataFrame, SparkSession, TrampolineUtil}
 import org.apache.spark.sql.rapids.tool.profiling._
 
 class ApplicationInfoSuite extends FunSuite with Logging {
@@ -80,6 +80,42 @@ class ApplicationInfoSuite extends FunSuite with Logging {
     assert(cuDFJar.size == 1, "CUDF jar check")
   }
 
+  test("test sql and resourceprofile eventlog") {
+    val eventLog = s"$logDir/rp_sql_eventlog"
+    TrampolineUtil.withTempDir { tempDir =>
+      val appArgs = new ProfileArgs(Array(
+        "--output-directory",
+        tempDir.getAbsolutePath,
+        eventLog))
+      val exit = ProfileMain.mainInternal(sparkSession, appArgs)
+      assert(exit == 0)
+    }
+  }
+
+  test("malformed json eventlog") {
+    val eventLog = s"$logDir/malformed_json_eventlog"
+    TrampolineUtil.withTempDir { tempDir =>
+      val appArgs = new ProfileArgs(Array(
+        "--output-directory",
+        tempDir.getAbsolutePath,
+        eventLog))
+      val exit = ProfileMain.mainInternal(sparkSession, appArgs)
+      assert(exit == 1)
+    }
+  }
+
+  test("test no sql eventlog") {
+    val eventLog = s"$logDir/rp_nosql_eventlog"
+    TrampolineUtil.withTempDir { tempDir =>
+      val appArgs = new ProfileArgs(Array(
+        "--output-directory",
+        tempDir.getAbsolutePath,
+        eventLog))
+      val exit = ProfileMain.mainInternal(sparkSession, appArgs)
+      assert(exit == 0)
+    }
+  }
+
   test("test printSQLPlanMetrics") {
     var apps: ArrayBuffer[ApplicationInfo] = ArrayBuffer[ApplicationInfo]()
     val appArgs =

rapids-4-spark-tools/src/test/scala/com/nvidia/spark/rapids/tool/qualification/QualificationSuite.scala

@@ -68,6 +68,13 @@ class QualificationSuite extends FunSuite with BeforeAndAfterEach with Logging {
     }
   }
 
+  test("skip malformed json eventlog") {
+    val profileLogDir = ToolTestUtils.getTestResourcePath("spark-events-profiling")
+    val badEventLog = s"$profileLogDir/malformed_json_eventlog"
+    val logFiles = Array(s"$logDir/nds_q86_test", badEventLog)
+    runQualificationTest(logFiles, "nds_q86_test_expectation.csv")
+  }
+
   test("test udf event logs") {
     val logFiles = Array(
       s"$logDir/dataset_eventlog",