resolve merge conflict

Signed-off-by: cindyyuanjiang <[email protected]>

core/src/main/scala/com/nvidia/spark/rapids/tool/analysis/AppSparkMetricsAnalyzer.scala

@@ -16,13 +16,16 @@
 
 package com.nvidia.spark.rapids.tool.analysis
 
+import java.util.concurrent.TimeUnit
+
 import scala.collection.mutable
 
+import com.nvidia.spark.rapids.tool.planparser.DatabricksParseHelper
 import com.nvidia.spark.rapids.tool.profiling.{IOAnalysisProfileResult, JobAggTaskMetricsProfileResult, ShuffleSkewProfileResult, SQLDurationExecutorTimeProfileResult, SQLMaxTaskInputSizes, SQLTaskAggMetricsProfileResult, StageAggTaskMetricsProfileResult, StageDiagnosticMetricsProfileResult}
 
 import org.apache.spark.sql.rapids.tool.{AppBase, ToolUtils}
 import org.apache.spark.sql.rapids.tool.profiling.ApplicationInfo
-import org.apache.spark.sql.rapids.tool.store.TaskModel
+import org.apache.spark.sql.rapids.tool.store.{AccumInfo, TaskModel}
 
 /**
  * Does analysis on the DataFrames from object of AppBase.
@@ -408,12 +411,62 @@ class AppSparkMetricsAnalyzer(app: AppBase) extends AppAnalysisBase(app) {
    */
   private def aggregateSparkMetricsByStageInternal(index: Int): Unit = {
     // TODO: this has stage attempts. we should handle different attempts
+
+    // For Photon apps, peak memory and shuffle write time need to be calculated from accumulators
+    // instead of task metrics.
+    // Approach:
+    //   1. Collect accumulators for each metric type.
+    //   2. For each stage, retrieve the relevant accumulators and calculate aggregated values.
+    // Note:
+    //  - A HashMap could be used instead of separate mutable.ArrayBuffer for each metric type,
+    //    but avoiding it for readability.
+    val photonPeakMemoryAccumInfos = mutable.ArrayBuffer[AccumInfo]()
+    val photonShuffleWriteTimeAccumInfos = mutable.ArrayBuffer[AccumInfo]()
+
+    if (app.isPhoton) {
+      app.accumManager.applyToAccumInfoMap { accumInfo =>
+        accumInfo.infoRef.name.value match {
+          case name if name.contains(
+            DatabricksParseHelper.PHOTON_METRIC_PEAK_MEMORY_LABEL) =>
+              // Collect accumulators for peak memory
+              photonPeakMemoryAccumInfos += accumInfo
+          case name if name.contains(
+            DatabricksParseHelper.PHOTON_METRIC_SHUFFLE_WRITE_TIME_LABEL) =>
+              // Collect accumulators for shuffle write time
+              photonShuffleWriteTimeAccumInfos += accumInfo
+          case _ => // Ignore other accumulators
+        }
+      }
+    }
+
     app.stageManager.getAllStages.foreach { sm =>
       // TODO: Should we only consider successful tasks?
       val tasksInStage = app.taskManager.getTasks(sm.stageInfo.stageId,
         sm.stageInfo.attemptNumber())
       // count duplicate task attempts
       val numAttempts = tasksInStage.size
+
+      val (peakMemoryMax, shuffleWriteTimeSum) = if (app.isPhoton) {
+        // For max peak memory, we need to look at the accumulators at the task level.
+        val peakMemoryValues = tasksInStage.flatMap { taskModel =>
+          photonPeakMemoryAccumInfos.flatMap { accumInfo =>
+            accumInfo.taskUpdatesMap.get(taskModel.taskId)
+          }
+        }
+        // For sum of shuffle write time, we need to look at the accumulators at the stage level.
+        val shuffleWriteValues = photonShuffleWriteTimeAccumInfos.flatMap { accumInfo =>
+          accumInfo.stageValuesMap.get(sm.stageInfo.stageId)
+        }
+        (AppSparkMetricsAnalyzer.maxWithEmptyHandling(peakMemoryValues),
+          TimeUnit.NANOSECONDS.toMillis(shuffleWriteValues.sum))
+      } else {
+        // For non-Photon apps, use the task metrics directly.
+        val peakMemoryValues = tasksInStage.map(_.peakExecutionMemory)
+        val shuffleWriteTime = tasksInStage.map(_.sw_writeTime)
+        (AppSparkMetricsAnalyzer.maxWithEmptyHandling(peakMemoryValues),
+          shuffleWriteTime.sum)
+      }
+
       val (durSum, durMax, durMin, durAvg) = AppSparkMetricsAnalyzer.getDurations(tasksInStage)
       val stageRow = StageAggTaskMetricsProfileResult(index,
         sm.stageInfo.stageId,
@@ -434,7 +487,7 @@ class AppSparkMetricsAnalyzer(app: AppBase) extends AppAnalysisBase(app) {
         tasksInStage.map(_.memoryBytesSpilled).sum,
         tasksInStage.map(_.output_bytesWritten).sum,
         tasksInStage.map(_.output_recordsWritten).sum,
-        AppSparkMetricsAnalyzer.maxWithEmptyHandling(tasksInStage.map(_.peakExecutionMemory)),
+        peakMemoryMax,
         tasksInStage.map(_.resultSerializationTime).sum,
         AppSparkMetricsAnalyzer.maxWithEmptyHandling(tasksInStage.map(_.resultSize)),
         tasksInStage.map(_.sr_fetchWaitTime).sum,
@@ -446,7 +499,7 @@ class AppSparkMetricsAnalyzer(app: AppBase) extends AppAnalysisBase(app) {
         tasksInStage.map(_.sr_totalBytesRead).sum,
         tasksInStage.map(_.sw_bytesWritten).sum,
         tasksInStage.map(_.sw_recordsWritten).sum,
-        tasksInStage.map(_.sw_writeTime).sum
+        shuffleWriteTimeSum
       )
       stageLevelSparkMetrics(index).put(sm.stageInfo.stageId, stageRow)
     }

core/src/main/scala/com/nvidia/spark/rapids/tool/planparser/DatabricksParseHelper.scala

@@ -17,15 +17,19 @@
 package com.nvidia.spark.rapids.tool.planparser
 
 import java.nio.file.Paths
+import java.util.concurrent.TimeUnit
 
 import scala.util.control.NonFatal
 import scala.util.matching.Regex
 
+import com.nvidia.spark.rapids.tool.profiling.SQLAccumProfileResults
+import com.nvidia.spark.rapids.tool.views.IoMetrics
 import org.json4s.{DefaultFormats, Formats}
 import org.json4s.jackson.JsonMethods
 import org.json4s.jackson.JsonMethods.parse
 
 import org.apache.spark.internal.Logging
+import org.apache.spark.sql.rapids.tool.UnsupportedMetricNameException
 import org.apache.spark.sql.rapids.tool.util.UTF8Source
 
 // Utilities used to handle Databricks and Photon Ops
@@ -48,6 +52,13 @@ object DatabricksParseHelper extends Logging {
   val SUB_PROP_JOB_ID = "JobId"
   val SUB_PROP_RUN_NAME = "RunName"
 
+  // scalastyle:off
+  // Photon metric labels that are used as alternatives to Spark metric labels
+  val PHOTON_METRIC_CUMULATIVE_TIME_LABEL = "cumulative time"               // Alternative for "scan time"
+  val PHOTON_METRIC_PEAK_MEMORY_LABEL = "peak memory usage"                 // Alternative for "peak execution memory"
+  val PHOTON_METRIC_SHUFFLE_WRITE_TIME_LABEL = "part of shuffle file write" // Alternative for "shuffle write time"
+  // scalastyle:on
+
   private val PHOTON_PATTERN: Regex = "Photon[a-zA-Z]*".r
   private val PHOTON_OPS_MAPPING_DIR = "photonOperatorMappings"
   // TODO: Create separate mapping file for different Photon/Databricks versions
@@ -147,4 +158,21 @@ object DatabricksParseHelper extends Logging {
   def mapPhotonToSpark(inputStr: String): String = {
     PHOTON_PATTERN.replaceAllIn(inputStr, m => photonToSparkMapping.getOrElse(m.matched, m.matched))
   }
+
+  /**
+   * Checks if 'accum' is a Photon I/O metric.
+   */
+  def isPhotonIoMetric(accum: SQLAccumProfileResults): Boolean =
+    accum.name == PHOTON_METRIC_CUMULATIVE_TIME_LABEL && accum.nodeName.contains("Scan")
+
+  /**
+   * Updates the I/O metrics for Photon apps based on the accumulator values.
+   */
+  def updatePhotonIoMetric(accum: SQLAccumProfileResults, ioMetrics: IoMetrics): Unit = {
+    accum.name match {
+      case PHOTON_METRIC_CUMULATIVE_TIME_LABEL if accum.nodeName.contains("Scan") =>
+        ioMetrics.scanTime = TimeUnit.NANOSECONDS.toMillis(accum.total)
+      case _ => throw UnsupportedMetricNameException(accum.name)
+    }
+  }
 }

core/src/main/scala/com/nvidia/spark/rapids/tool/views/DataSourceView.scala

@@ -19,6 +19,7 @@ package com.nvidia.spark.rapids.tool.views
 import scala.collection.Seq
 
 import com.nvidia.spark.rapids.tool.analysis.{ProfAppIndexMapperTrait, QualAppIndexMapperTrait}
+import com.nvidia.spark.rapids.tool.planparser.DatabricksParseHelper
 import com.nvidia.spark.rapids.tool.profiling.{DataSourceProfileResult, SQLAccumProfileResults}
 import com.nvidia.spark.rapids.tool.qualification.QualSQLPlanAnalyzer
 
@@ -40,6 +41,12 @@ object IoMetrics {
   val DECODE_TIME_LABEL = "GPU decode time"
 
   val EMPTY_IO_METRICS: IoMetrics = IoMetrics(0, 0, 0, 0)
+
+  /**
+   * Get all labels for IoMetrics
+   */
+  def getAllLabels: Seq[String] = Seq(
+    BUFFER_TIME_LABEL, SCAN_TIME_LABEL, DATA_SIZE_LABEL, DECODE_TIME_LABEL)
 }
 
 trait AppDataSourceViewTrait extends ViewableTrait[DataSourceProfileResult] {
@@ -48,11 +55,13 @@ trait AppDataSourceViewTrait extends ViewableTrait[DataSourceProfileResult] {
   private def getIoMetrics(sqlAccums: Seq[SQLAccumProfileResults]): IoMetrics = {
     val finalRes = IoMetrics(0, 0, 0, 0)
     try {
-      sqlAccums.map(accum => accum.name match {
+      sqlAccums.foreach(accum => accum.name match {
         case IoMetrics.BUFFER_TIME_LABEL => finalRes.bufferTime = accum.total
         case IoMetrics.SCAN_TIME_LABEL => finalRes.scanTime = accum.total
         case IoMetrics.DATA_SIZE_LABEL => finalRes.dataSize = accum.total
         case IoMetrics.DECODE_TIME_LABEL => finalRes.decodeTime = accum.total
+        case _ if DatabricksParseHelper.isPhotonIoMetric(accum) =>
+          DatabricksParseHelper.updatePhotonIoMetric(accum, finalRes)
         case _ => throw UnsupportedMetricNameException(accum.name)
       })
     } catch {
@@ -98,11 +107,9 @@ trait AppDataSourceViewTrait extends ViewableTrait[DataSourceProfileResult] {
       index: Int,
       appSqlAccums: Seq[SQLAccumProfileResults]): Seq[DataSourceProfileResult] = {
     // Filter appSqlAccums to get only required metrics
-    val dataSourceMetrics = appSqlAccums.filter(
-      sqlAccum => sqlAccum.name.contains(IoMetrics.BUFFER_TIME_LABEL)
-        || sqlAccum.name.contains(IoMetrics.SCAN_TIME_LABEL)
-        || sqlAccum.name.contains(IoMetrics.DECODE_TIME_LABEL)
-        || sqlAccum.name.equals(IoMetrics.DATA_SIZE_LABEL))
+    val dataSourceMetrics = appSqlAccums.filter(sqlAccum =>
+      IoMetrics.getAllLabels.contains(sqlAccum.name) ||
+        app.isPhoton && DatabricksParseHelper.isPhotonIoMetric(sqlAccum))
 
     val dsFromLastPlan = app.dataSourceInfo.map { ds =>
       val sqlIdtoDs = dataSourceMetrics.filter(

core/src/main/scala/org/apache/spark/sql/rapids/tool/store/AccumManager.scala

@@ -66,4 +66,11 @@ class AccumManager {
   def getMaxStageValue(id: Long): Option[Long] = {
     accumInfoMap.get(id).map(_.getMaxStageValue.get)
   }
+
+  /**
+   * Applies the function `f` to each AccumInfo in the accumInfoMap.
+   */
+  def applyToAccumInfoMap(f: AccumInfo => Unit): Unit = {
+    accumInfoMap.values.foreach(f)
+  }
 }

core/src/main/scala/org/apache/spark/sql/rapids/tool/util/RuntimeUtil.scala

@@ -17,6 +17,9 @@
 package org.apache.spark.sql.rapids.tool.util
 
 import java.io.{PrintWriter, StringWriter}
+import java.lang.management.ManagementFactory
+
+import scala.collection.convert.ImplicitConversions.`collection AsScalaIterable`
 
 import com.nvidia.spark.rapids.tool.ToolTextFileWriter
 import org.apache.hadoop.conf.Configuration
@@ -49,6 +52,12 @@ object RuntimeUtil extends Logging {
     // Add the Spark version used in runtime.
     // Note that it is different from the Spark version used in the build.
     buildProps.setProperty("runtime.spark.version", ToolUtils.sparkRuntimeVersion)
+    // Add the JVM and OS information
+    getJVMOSInfo.foreach {
+      kv => buildProps.setProperty(s"runtime.${kv._1}", kv._2)
+    }
+    // get the JVM memory arguments
+    getJVMHeapArguments.foreach(kv => buildProps.setProperty(s"runtime.${kv._1}", kv._2))
     val reportWriter = new ToolTextFileWriter(outputDir, REPORT_FILE_NAME, REPORT_LABEL, hadoopConf)
     try {
       reportWriter.writeProperties(buildProps, REPORT_LABEL)
@@ -73,6 +82,25 @@ object RuntimeUtil extends Logging {
       "os.version" -> System.getProperty("os.version")
     )
   }
-}
-
 
+  def getJVMHeapArguments: Map[String, String] = {
+    ManagementFactory.getRuntimeMXBean.getInputArguments.filter(
+      p => p.startsWith("-Xmx") || p.startsWith("-Xms") || p.startsWith("-XX:")).map {
+      sizeArg =>
+        if (sizeArg.startsWith("-Xmx")) {
+          ("jvm.arg.heap.max", sizeArg.drop(4))
+        } else if (sizeArg.startsWith("-Xms")) {
+          ("jvm.arg.heap.min", sizeArg.drop(4))
+        } else { // this is heap argument
+          // drop the first "-XX:"
+          val dropSize = if (sizeArg.startsWith("-XX:+")) 5 else 4
+          val parts = sizeArg.drop(dropSize).split("=")
+          if (parts.length == 2) {
+            (s"jvm.arg.gc.${parts(0)}", parts(1))
+          } else {
+            (s"jvm.arg.gc.${parts(0)}", "")
+          }
+        }
+    }.toMap
+  }
+}

core/src/test/resources/ProfilingExpectations/nds_q88_photon_db_13_3_job_metrics_agg_expectation.csv

@@ -0,0 +1,58 @@
+appIndex,jobId,numTasks,Duration,diskBytesSpilled_sum,duration_sum,duration_max,duration_min,duration_avg,executorCPUTime_sum,executorDeserializeCPUTime_sum,executorDeserializeTime_sum,executorRunTime_sum,input_bytesRead_sum,input_recordsRead_sum,jvmGCTime_sum,memoryBytesSpilled_sum,output_bytesWritten_sum,output_recordsWritten_sum,peakExecutionMemory_max,resultSerializationTime_sum,resultSize_max,sr_fetchWaitTime_sum,sr_localBlocksFetched_sum,sr_localBytesRead_sum,sr_remoteBlocksFetched_sum,sr_remoteBytesRead_sum,sr_remoteBytesReadToDisk_sum,sr_totalBytesRead_sum,sw_bytesWritten_sum,sw_recordsWritten_sum,sw_writeTime_sum
+1,48,431,237976,0,371230,1032,333,861.3,343288,1261,1286,367785,190131859,8639936081,160,0,0,0,169667947,21,15767,8,3,15657,3,15657,0,31314,18964,431,16
+1,47,432,214657,0,376777,1133,499,872.2,346230,1272,1310,373271,14007280,8639936081,144,0,0,0,159530057,11,15577,4,3,15657,3,15657,0,31314,19008,432,20
+1,46,433,191440,0,457364,3323,391,1056.3,352763,1508,2509,451358,5242628040,8639936081,1912,0,0,0,250840493,9,16203,551,3,15657,3,15657,0,31314,19052,433,16
+1,49,1,186241,0,266,266,266,266.0,86,1,1,261,0,0,0,0,0,0,138414192,0,5344,10,209,9196,222,9768,0,18964,44,1,0
+1,45,433,166081,0,415849,1448,339,960.4,349795,1302,1375,412139,2276478144,8639936081,568,0,0,0,195992906,2,15780,7,3,15657,3,15657,0,31314,19052,433,34
+1,44,431,139667,0,398973,1403,365,925.7,354119,1281,1327,395265,1075691986,8639936081,328,0,0,0,188587155,0,15767,10,3,15657,3,15657,0,31314,18964,431,17
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+1,43,432,114755,0,403652,1369,329,934.4,353325,1290,1326,399766,1395949742,8639936081,624,0,0,0,201771890,13,15767,14,3,15657,3,15657,0,31314,19008,432,16
+1,51,1,97958,0,386,386,386,386.0,60,1,1,381,0,0,0,0,0,0,138414192,0,5343,154,221,9724,210,9240,0,18964,44,1,0
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+1,52,1,71718,0,384,384,384,384.0,54,1,1,379,0,0,0,0,0,0,138414192,0,5343,170,223,9812,210,9240,0,19052,44,1,0
+1,41,431,51085,0,759623,2321,918,1762.5,394996,1460,2027,754015,26337468742,8639936081,7772,0,0,0,250648581,87,16157,170,3,15657,3,15657,0,31314,18964,431,19
+1,53,1,46297,0,136,136,136,136.0,57,1,1,131,0,0,0,0,0,0,138414192,0,5344,0,214,9416,219,9636,0,19052,44,1,0
+1,54,1,23051,0,340,340,340,340.0,36,1,1,334,0,0,0,0,0,0,138414192,0,5343,223,215,9460,217,9548,0,19008,44,1,0
+1,31,1,6979,0,6738,6738,6738,6738.0,5104,128,688,6035,349526,86400,53,0,0,0,155563380,1,10759,0,0,0,0,0,0,0,7239,1800,0
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+1,38,1,6855,0,6743,6743,6743,6743.0,187,256,688,6035,349526,86400,53,0,0,0,155563380,1,9927,0,0,0,0,0,0,0,7239,1800,0
+1,0,1,6033,0,5699,5699,5699,5699.0,422,948,1114,4382,0,0,37,0,0,0,0,8,2794,0,0,0,0,0,0,0,0,0,0
+1,13,200,5707,0,87661,966,349,438.3,9821,427,951,84265,0,0,144,0,0,0,0,9,6258,0,0,0,0,0,0,0,0,0,0
+1,23,200,5479,0,84240,490,355,421.2,5290,200,214,82784,0,0,136,0,0,0,0,0,6214,0,0,0,0,0,0,0,0,0,0
+1,21,200,5271,0,80904,485,353,404.5,6004,203,220,79384,0,0,136,0,0,0,0,1,6302,0,0,0,0,0,0,0,0,0,0
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+1,39,1,4488,0,4322,4322,4322,4322.0,112,124,392,3907,349526,86400,39,0,0,0,155563380,1,9926,0,0,0,0,0,0,0,7239,1800,0
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+1,40,1,4476,0,4327,4327,4327,4327.0,98,147,394,3907,349526,86400,39,0,0,0,155563380,1,9895,0,0,0,0,0,0,0,7239,1800,0
+1,56,1,1055,0,1022,1022,1022,1022.0,758,77,95,901,0,0,0,0,0,0,134218344,6,10091,5,218,9592,220,9680,0,19272,0,0,0
+1,19,200,803,0,11895,145,38,59.5,943,209,252,10017,0,0,56,0,0,0,0,22,2739,0,0,0,0,0,0,0,0,0,0
+1,26,1,316,0,312,312,312,312.0,2,1,1,306,0,0,0,0,0,0,0,0,3777,0,0,0,0,0,0,0,0,0,0
+1,2,1,280,0,267,267,267,267.0,6,4,4,124,0,0,0,0,0,0,0,1,3342,0,0,0,0,0,0,0,0,0,0
+1,11,1,264,0,254,254,254,254.0,5,3,3,241,0,0,0,0,0,0,0,0,2913,0,0,0,0,0,0,0,0,0,0
+1,7,1,240,0,227,227,227,227.0,5,4,4,213,0,0,114,0,0,0,0,0,2206,0,0,0,0,0,0,0,0,0,0
+1,1,1,209,0,173,173,173,173.0,28,5,6,152,0,0,0,0,0,0,0,0,2506,0,0,0,0,0,0,0,0,0,0
+1,5,1,179,0,165,165,165,165.0,4,4,4,151,0,0,0,0,0,0,0,0,2475,0,0,0,0,0,0,0,0,0,0
+1,14,1,151,0,143,143,143,143.0,3,1,1,132,0,0,0,0,0,0,0,1,3120,0,0,0,0,0,0,0,0,0,0
+1,4,1,147,0,139,139,139,139.0,22,5,6,121,0,0,0,0,0,0,0,0,2334,0,0,0,0,0,0,0,0,0,0
+1,20,1,141,0,137,137,137,137.0,1,1,1,130,0,0,0,0,0,0,0,0,2170,0,0,0,0,0,0,0,0,0,0
+1,28,1,140,0,136,136,136,136.0,2,1,1,130,0,0,0,0,0,0,0,0,3784,0,0,0,0,0,0,0,0,0,0
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core/src/test/resources/ProfilingExpectations/nds_q88_photon_db_13_3_sql_metrics_agg_expectation.csv

@@ -0,0 +1,2 @@
+appIndex,appID,sqlID,description,numTasks,Duration,executorCPUTime,executorRunTime,executorCPURatio,diskBytesSpilled_sum,duration_sum,duration_max,duration_min,duration_avg,executorCPUTime_sum,executorDeserializeCPUTime_sum,executorDeserializeTime_sum,executorRunTime_sum,input_bytesRead_sum,input_recordsRead_sum,jvmGCTime_sum,memoryBytesSpilled_sum,output_bytesWritten_sum,output_recordsWritten_sum,peakExecutionMemory_max,resultSerializationTime_sum,resultSize_max,sr_fetchWaitTime_sum,sr_localBlocksFetched_sum,sr_localBytesRead_sum,sr_remoteBlocksFetched_sum,sr_remoteBytesRead_sum,sr_remoteBytesReadToDisk_sum,sr_totalBytesRead_sum,sw_bytesWritten_sum,sw_recordsWritten_sum,sw_writeTime_sum
+1,"app-20240919162642-0000",26,"query88",3472,250542,2883837,3818106,75.53,0,3858136,6743,54,1111.2,2883837,12349,18186,3818106,52997115316,69120188398,16100,0,0,0,250840493,181,16203,1394,1759,201596,1750,201200,0,402796,218614,19946,154