-
Notifications
You must be signed in to change notification settings - Fork 858
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Peak Unified Memory Heuristic - (Depends on Custom SHS - Requires pea…
…kUnifiedMemory metric) (#281)
- Loading branch information
Showing
13 changed files
with
271 additions
and
14 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
133 changes: 133 additions & 0 deletions
133
app/com/linkedin/drelephant/spark/heuristics/UnifiedMemoryHeuristic.scala
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,133 @@ | ||
| /* | ||
| * Copyright 2016 LinkedIn Corp. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); you may not | ||
| * use this file except in compliance with the License. You may obtain a copy of | ||
| * the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT | ||
| * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the | ||
| * License for the specific language governing permissions and limitations under | ||
| * the License. | ||
| */ | ||
|
|
||
| package com.linkedin.drelephant.spark.heuristics | ||
|
|
||
| import com.linkedin.drelephant.analysis._ | ||
| import com.linkedin.drelephant.configurations.heuristic.HeuristicConfigurationData | ||
| import com.linkedin.drelephant.spark.data.SparkApplicationData | ||
| import com.linkedin.drelephant.spark.fetchers.statusapiv1.ExecutorSummary | ||
| import com.linkedin.drelephant.util.MemoryFormatUtils | ||
|
|
||
| import scala.collection.JavaConverters | ||
|
|
||
|
|
||
| /** | ||
| * A heuristic based on peak unified memory for the spark executors | ||
| * | ||
| * This heuristic reports the fraction of memory used/ memory allocated and if the fraction can be reduced. Also, it checks for the skew in peak unified memory and reports if the skew is too much. | ||
| */ | ||
| class UnifiedMemoryHeuristic(private val heuristicConfigurationData: HeuristicConfigurationData) | ||
| extends Heuristic[SparkApplicationData] { | ||
|
|
||
| import UnifiedMemoryHeuristic._ | ||
| import JavaConverters._ | ||
|
|
||
| override def getHeuristicConfData(): HeuristicConfigurationData = heuristicConfigurationData | ||
|
|
||
| lazy val peakUnifiedMemoryThresholdString: String = heuristicConfigurationData.getParamMap.get(PEAK_UNIFIED_MEMORY_THRESHOLD_KEY) | ||
|
|
||
| override def apply(data: SparkApplicationData): HeuristicResult = { | ||
| val evaluator = new Evaluator(this, data) | ||
|
|
||
| var resultDetails = Seq( | ||
| new HeuristicResultDetails("Unified Memory Space Allocated", MemoryFormatUtils.bytesToString(evaluator.maxMemory)), | ||
| new HeuristicResultDetails("Mean peak unified memory", MemoryFormatUtils.bytesToString(evaluator.meanUnifiedMemory)), | ||
| new HeuristicResultDetails("Max peak unified memory", MemoryFormatUtils.bytesToString(evaluator.maxUnifiedMemory)), | ||
| new HeuristicResultDetails("spark.executor.memory", MemoryFormatUtils.bytesToString(evaluator.sparkExecutorMemory)), | ||
| new HeuristicResultDetails("spark.memory.fraction", evaluator.sparkMemoryFraction.toString) | ||
| ) | ||
|
|
||
| val result = new HeuristicResult( | ||
| heuristicConfigurationData.getClassName, | ||
| heuristicConfigurationData.getHeuristicName, | ||
| evaluator.severity, | ||
| 0, | ||
| resultDetails.asJava | ||
| ) | ||
| result | ||
| } | ||
| } | ||
|
|
||
| object UnifiedMemoryHeuristic { | ||
|
|
||
| val EXECUTION_MEMORY = "executionMemory" | ||
| val STORAGE_MEMORY = "storageMemory" | ||
| val SPARK_EXECUTOR_MEMORY_KEY = "spark.executor.memory" | ||
| val SPARK_MEMORY_FRACTION_KEY = "spark.memory.fraction" | ||
| val PEAK_UNIFIED_MEMORY_THRESHOLD_KEY = "peak_unified_memory_threshold" | ||
|
|
||
| class Evaluator(unifiedMemoryHeuristic: UnifiedMemoryHeuristic, data: SparkApplicationData) { | ||
| lazy val appConfigurationProperties: Map[String, String] = | ||
| data.appConfigurationProperties | ||
|
|
||
| lazy val DEFAULT_PEAK_UNIFIED_MEMORY_THRESHOLD: SeverityThresholds = SeverityThresholds(low = 0.7 * maxMemory, moderate = 0.6 * maxMemory, severe = 0.4 * maxMemory, critical = 0.2 * maxMemory, ascending = false) | ||
|
|
||
| lazy val executorSummaries: Seq[ExecutorSummary] = data.executorSummaries | ||
| if (executorSummaries == null) { | ||
| throw new Exception("Executors Summary is null.") | ||
| } | ||
|
|
||
| val executorList: Seq[ExecutorSummary] = executorSummaries.filterNot(_.id.equals("driver")) | ||
| if (executorList.isEmpty) { | ||
| throw new Exception("No executor information available.") | ||
| } | ||
|
|
||
| //allocated memory for the unified region | ||
| val maxMemory: Long = executorList.head.maxMemory | ||
|
|
||
| val PEAK_UNIFIED_MEMORY_THRESHOLDS: SeverityThresholds = if (unifiedMemoryHeuristic.peakUnifiedMemoryThresholdString == null) { | ||
| DEFAULT_PEAK_UNIFIED_MEMORY_THRESHOLD | ||
| } else { | ||
| SeverityThresholds.parse(unifiedMemoryHeuristic.peakUnifiedMemoryThresholdString.split(",").map(_.toDouble * maxMemory).toString, ascending = false).getOrElse(DEFAULT_PEAK_UNIFIED_MEMORY_THRESHOLD) | ||
| } | ||
|
|
||
| def getPeakUnifiedMemoryExecutorSeverity(executorSummary: ExecutorSummary): Severity = { | ||
| return PEAK_UNIFIED_MEMORY_THRESHOLDS.severityOf(executorSummary.peakUnifiedMemory.getOrElse(EXECUTION_MEMORY, 0).asInstanceOf[Number].longValue | ||
| + executorSummary.peakUnifiedMemory.getOrElse(STORAGE_MEMORY, 0).asInstanceOf[Number].longValue) | ||
| } | ||
|
|
||
| val sparkExecutorMemory: Long = (appConfigurationProperties.get(SPARK_EXECUTOR_MEMORY_KEY).map(MemoryFormatUtils.stringToBytes)).getOrElse(0L) | ||
|
|
||
| val sparkMemoryFraction: Double = appConfigurationProperties.getOrElse(SPARK_MEMORY_FRACTION_KEY, 0.6D).asInstanceOf[Number].doubleValue | ||
|
|
||
| lazy val meanUnifiedMemory: Long = (executorList.map { | ||
| executorSummary => { | ||
| executorSummary.peakUnifiedMemory.getOrElse(EXECUTION_MEMORY, 0).asInstanceOf[Number].longValue | ||
| +executorSummary.peakUnifiedMemory.getOrElse(STORAGE_MEMORY, 0).asInstanceOf[Number].longValue | ||
| } | ||
| }.sum) / executorList.size | ||
|
|
||
| lazy val maxUnifiedMemory: Long = executorList.map { | ||
| executorSummary => { | ||
| executorSummary.peakUnifiedMemory.getOrElse(EXECUTION_MEMORY, 0).asInstanceOf[Number].longValue | ||
| +executorSummary.peakUnifiedMemory.getOrElse(STORAGE_MEMORY, 0).asInstanceOf[Number].longValue | ||
| } | ||
| }.max | ||
|
|
||
| lazy val severity: Severity = { | ||
| var severityPeakUnifiedMemoryVariable: Severity = Severity.NONE | ||
| for (executorSummary <- executorList) { | ||
| var peakUnifiedMemoryExecutorSeverity: Severity = getPeakUnifiedMemoryExecutorSeverity(executorSummary) | ||
| if (peakUnifiedMemoryExecutorSeverity.getValue > severityPeakUnifiedMemoryVariable.getValue) { | ||
| severityPeakUnifiedMemoryVariable = peakUnifiedMemoryExecutorSeverity | ||
| } | ||
| } | ||
| severityPeakUnifiedMemoryVariable | ||
| } | ||
| } | ||
|
|
||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
24 changes: 24 additions & 0 deletions
24
app/views/help/spark/helpUnifiedMemoryHeuristic.scala.html
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
| @* | ||
| * Copyright 2016 LinkedIn Corp. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); you may not | ||
| * use this file except in compliance with the License. You may obtain a copy of | ||
| * the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT | ||
| * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the | ||
| * License for the specific language governing permissions and limitations under | ||
| * the License. | ||
| *@ | ||
| <p>Peak Unified Memory Heuristic identifies and flags jobs which have over allocated Unified Memory region.</p> | ||
| <h4>Peak Unified Memory</h4> | ||
| <p>If the job's Peak Unified Memory Consumption is much smaller than the allocated Unified Memory space, then we recommend decreasing the allocated Unified Memory Region for your job.</p> | ||
| <h3>Action Items</h3> | ||
| <p>The Allocated Unified Memory Region can be reduced in the following ways: </p> | ||
| <p>1. If your job's Executor Memory is already low, then reduce <i>spark.memory.fraction</i> which will reduce the amount of space allocated to the Unified Memory Region.</p> | ||
| <p>2. If your job's Executor Memory is high, then we recommend reducing the <i>spark.executor.memory</i> itself which will lower the Allocated Unified Memory space.</p> | ||
| <p>Note:</p> | ||
| <p><i>spark.memory.fraction</i>: This is the fraction of JVM Used Memory (Executor memory - Reserved memory) dedicated to the unified memory region (execution + storage). It basically partitions user memory from execution and storage memory.</p> |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
83 changes: 83 additions & 0 deletions
83
test/com/linkedin/drelephant/spark/heuristics/UnifiedMemoryHeuristicTest.scala
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,83 @@ | ||
| package com.linkedin.drelephant.spark.heuristics | ||
|
|
||
| import com.linkedin.drelephant.analysis.{ApplicationType, Severity} | ||
| import com.linkedin.drelephant.configurations.heuristic.HeuristicConfigurationData | ||
| import com.linkedin.drelephant.spark.data.{SparkApplicationData, SparkRestDerivedData} | ||
| import com.linkedin.drelephant.spark.fetchers.statusapiv1.{ApplicationInfoImpl, ExecutorSummaryImpl} | ||
| import org.scalatest.{FunSpec, Matchers} | ||
|
|
||
| import scala.collection.JavaConverters | ||
|
|
||
| class UnifiedMemoryHeuristicTest extends FunSpec with Matchers { | ||
|
|
||
| import UnifiedMemoryHeuristicTest._ | ||
|
|
||
| val heuristicConfigurationData = newFakeHeuristicConfigurationData() | ||
|
|
||
| val memoryFractionHeuristic = new UnifiedMemoryHeuristic(heuristicConfigurationData) | ||
|
|
||
| val executorData = Seq( | ||
| newDummyExecutorData("1", 400000, Map("executionMemory" -> 300000, "storageMemory" -> 94567)), | ||
| newDummyExecutorData("2", 400000, Map("executionMemory" -> 200000, "storageMemory" -> 34568)), | ||
| newDummyExecutorData("3", 400000, Map("executionMemory" -> 300000, "storageMemory" -> 34569)), | ||
| newDummyExecutorData("4", 400000, Map("executionMemory" -> 20000, "storageMemory" -> 3456)), | ||
| newDummyExecutorData("5", 400000, Map("executionMemory" -> 200000, "storageMemory" -> 34564)), | ||
| newDummyExecutorData("6", 400000, Map("executionMemory" -> 300000, "storageMemory" -> 94561)) | ||
| ) | ||
| describe(".apply") { | ||
| val data = newFakeSparkApplicationData(executorData) | ||
| val heuristicResult = memoryFractionHeuristic.apply(data) | ||
| val heuristicResultDetails = heuristicResult.getHeuristicResultDetails | ||
|
|
||
| it("has severity") { | ||
| heuristicResult.getSeverity should be(Severity.CRITICAL) | ||
| } | ||
| } | ||
| } | ||
|
|
||
| object UnifiedMemoryHeuristicTest { | ||
|
|
||
| import JavaConverters._ | ||
|
|
||
| def newFakeHeuristicConfigurationData(params: Map[String, String] = Map.empty): HeuristicConfigurationData = | ||
| new HeuristicConfigurationData("heuristic", "class", "view", new ApplicationType("type"), params.asJava) | ||
|
|
||
| def newDummyExecutorData( | ||
| id: String, | ||
| maxMemory: Long, | ||
| peakUnifiedMemory: Map[String, Long] | ||
| ): ExecutorSummaryImpl = new ExecutorSummaryImpl( | ||
| id, | ||
| hostPort = "", | ||
| rddBlocks = 0, | ||
| memoryUsed = 0, | ||
| diskUsed = 0, | ||
| activeTasks = 0, | ||
| failedTasks = 0, | ||
| completedTasks = 0, | ||
| totalTasks = 0, | ||
| totalDuration = 0, | ||
| totalInputBytes = 0, | ||
| totalShuffleRead = 0, | ||
| totalShuffleWrite = 0, | ||
| maxMemory, | ||
| totalGCTime = 0, | ||
| totalMemoryBytesSpilled = 0, | ||
| executorLogs = Map.empty, | ||
| peakJvmUsedMemory = Map.empty, | ||
| peakUnifiedMemory | ||
| ) | ||
|
|
||
| def newFakeSparkApplicationData(executorSummaries: Seq[ExecutorSummaryImpl]): SparkApplicationData = { | ||
| val appId = "application_1" | ||
| val restDerivedData = SparkRestDerivedData( | ||
| new ApplicationInfoImpl(appId, name = "app", Seq.empty), | ||
| jobDatas = Seq.empty, | ||
| stageDatas = Seq.empty, | ||
| executorSummaries = executorSummaries, | ||
| stagesWithFailedTasks = Seq.empty | ||
| ) | ||
|
|
||
| SparkApplicationData(appId, restDerivedData, logDerivedData = None) | ||
| } | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters