spark EventLogFileCompactor 源码

spark EventLogFileCompactor 代码

文件路径：/core/src/main/scala/org/apache/spark/deploy/history/EventLogFileCompactor.scala

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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 org.apache.spark.deploy.history

import java.io.IOException
import java.net.URI
import java.util.ServiceLoader

import scala.collection.JavaConverters._

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.{FileStatus, FileSystem, Path}

import org.apache.spark.SparkConf
import org.apache.spark.deploy.history.EventFilter.FilterStatistics
import org.apache.spark.internal.Logging
import org.apache.spark.scheduler.ReplayListenerBus
import org.apache.spark.util.Utils

/**
 * This class compacts the old event log files into one compact file, via two phases reading:
 *
 * 1) Initialize available [[EventFilterBuilder]] instances, and replay the old event log files with
 * builders, so that these builders can gather the information to create [[EventFilter]] instances.
 * 2) Initialize [[EventFilter]] instances from [[EventFilterBuilder]] instances, and replay the
 * old event log files with filters. Rewrite the events to the compact file which the filters decide
 * to accept.
 *
 * This class will calculate the score based on statistic from [[EventFilter]] instances, which
 * represents approximate rate of filtered-out events. Score is being calculated via applying
 * heuristic; task events tend to take most size in event log.
 */
class EventLogFileCompactor(
    sparkConf: SparkConf,
    hadoopConf: Configuration,
    fs: FileSystem,
    maxFilesToRetain: Int,
    compactionThresholdScore: Double) extends Logging {

  require(maxFilesToRetain > 0, "Max event log files to retain should be higher than 0.")

  /**
   * Compacts the old event log files into one compact file, and clean old event log files being
   * compacted away.
   *
   * This method assumes caller will provide the sorted list of files which are sorted by
   * the index of event log file, with at most one compact file placed first if it exists.
   *
   * When compacting the files, the range of compaction for given file list is determined as:
   * (first ~ the file where there're `maxFilesToRetain` files on the right side)
   *
   * This method skips compaction for some circumstances described below:
   * - not enough files on the range of compaction
   * - score is lower than the threshold of compaction (meaning compaction won't help much)
   *
   * If this method returns the compaction result as SUCCESS, caller needs to re-read the list
   * of event log files, as new compact file is available as well as old event log files are
   * removed.
   */
  def compact(eventLogFiles: Seq[FileStatus]): CompactionResult = {
    assertPrecondition(eventLogFiles)

    if (eventLogFiles.length < maxFilesToRetain) {
      return CompactionResult(CompactionResultCode.NOT_ENOUGH_FILES, None)
    }

    val filesToCompact = findFilesToCompact(eventLogFiles)
    if (filesToCompact.isEmpty) {
      CompactionResult(CompactionResultCode.NOT_ENOUGH_FILES, None)
    } else {
      val builders = initializeBuilders(fs, filesToCompact.map(_.getPath))

      val filters = builders.map(_.createFilter())
      val minScore = filters.flatMap(_.statistics()).map(calculateScore).min

      if (minScore < compactionThresholdScore) {
        CompactionResult(CompactionResultCode.LOW_SCORE_FOR_COMPACTION, None)
      } else {
        rewrite(filters, filesToCompact)
        cleanupCompactedFiles(filesToCompact)
        CompactionResult(CompactionResultCode.SUCCESS, Some(
          RollingEventLogFilesWriter.getEventLogFileIndex(filesToCompact.last.getPath.getName)))
      }
    }
  }

  private def assertPrecondition(eventLogFiles: Seq[FileStatus]): Unit = {
    val idxCompactedFiles = eventLogFiles.zipWithIndex.filter { case (file, _) =>
      EventLogFileWriter.isCompacted(file.getPath)
    }
    require(idxCompactedFiles.size < 2 && idxCompactedFiles.headOption.forall(_._2 == 0),
      "The number of compact files should be at most 1, and should be placed first if exists.")
  }

  /**
   * Loads all available EventFilterBuilders in classloader via ServiceLoader, and initializes
   * them via replaying events in given files.
   */
  private def initializeBuilders(fs: FileSystem, files: Seq[Path]): Seq[EventFilterBuilder] = {
    val bus = new ReplayListenerBus()

    val builders = ServiceLoader.load(classOf[EventFilterBuilder],
      Utils.getContextOrSparkClassLoader).asScala.toSeq
    builders.foreach(bus.addListener)

    files.foreach { log =>
      Utils.tryWithResource(EventLogFileReader.openEventLog(log, fs)) { in =>
        bus.replay(in, log.getName)
      }
    }

    builders
  }

  private def calculateScore(stats: FilterStatistics): Double = {
    // For now it's simply measuring how many task events will be filtered out (rejected)
    // but it can be sophisticated later once we get more heuristic information and found
    // the case where this simple calculation doesn't work.
    (stats.totalTasks - stats.liveTasks) * 1.0 / stats.totalTasks
  }

  /**
   * This method rewrites the event log files into one compact file: the compact file will only
   * contain the events which pass the filters. Events will be dropped only when all filters
   * decide to reject the event or don't mind about the event. Otherwise, the original line for
   * the event is written to the compact file as it is.
   */
  private[history] def rewrite(
      filters: Seq[EventFilter],
      eventLogFiles: Seq[FileStatus]): String = {
    require(eventLogFiles.nonEmpty)

    val lastIndexEventLogPath = eventLogFiles.last.getPath
    val logWriter = new CompactedEventLogFileWriter(lastIndexEventLogPath, "dummy", None,
      lastIndexEventLogPath.getParent.toUri, sparkConf, hadoopConf)

    logWriter.start()
    eventLogFiles.foreach { file =>
      EventFilter.applyFilterToFile(fs, filters, file.getPath,
        onAccepted = (line, _) => logWriter.writeEvent(line, flushLogger = true),
        onRejected = (_, _) => {},
        onUnidentified = line => logWriter.writeEvent(line, flushLogger = true)
      )
    }
    logWriter.stop()

    logWriter.logPath
  }

  private def cleanupCompactedFiles(files: Seq[FileStatus]): Unit = {
    files.foreach { file =>
      var deleted = false
      try {
        deleted = fs.delete(file.getPath, true)
      } catch {
        case _: IOException =>
      }
      if (!deleted) {
        logWarning(s"Failed to remove ${file.getPath} / skip removing.")
      }
    }
  }

  private def findFilesToCompact(eventLogFiles: Seq[FileStatus]): Seq[FileStatus] = {
    val numNormalEventLogFiles = {
      if (EventLogFileWriter.isCompacted(eventLogFiles.head.getPath)) {
        eventLogFiles.length - 1
      } else {
        eventLogFiles.length
      }
    }

    // This avoids compacting only compact file.
    if (numNormalEventLogFiles > maxFilesToRetain) {
      eventLogFiles.dropRight(maxFilesToRetain)
    } else {
      Seq.empty
    }
  }
}

/**
 * Describes the result of compaction.
 *
 * @param code The result of compaction.
 * @param compactIndex The index of compact file if the compaction is successful.
 *                     Otherwise it will be None.
 */
case class CompactionResult(code: CompactionResultCode.Value, compactIndex: Option[Long])

object CompactionResultCode extends Enumeration {
  val SUCCESS, NOT_ENOUGH_FILES, LOW_SCORE_FOR_COMPACTION = Value
}

/**
 * This class helps to write compact file; to avoid reimplementing everything, it extends
 * [[SingleEventLogFileWriter]], but only `originalFilePath` is used to determine the
 * path of compact file.
 */
private class CompactedEventLogFileWriter(
    originalFilePath: Path,
    appId: String,
    appAttemptId: Option[String],
    logBaseDir: URI,
    sparkConf: SparkConf,
    hadoopConf: Configuration)
  extends SingleEventLogFileWriter(appId, appAttemptId, logBaseDir, sparkConf, hadoopConf) {

  override val logPath: String = originalFilePath.toUri.toString + EventLogFileWriter.COMPACTED
}

相关信息

spark 源码目录

相关文章

spark ApplicationCache 源码

spark ApplicationHistoryProvider 源码

spark BasicEventFilterBuilder 源码

spark EventFilter 源码

spark EventLogFileReaders 源码

spark EventLogFileWriters 源码

spark FsHistoryProvider 源码

spark HistoryAppStatusStore 源码

spark HistoryPage 源码

spark HistoryServer 源码