HeartSaVioR commented on a change in pull request #27085: [SPARK-29779][CORE] Compact old event log files and cleanup URL: https://github.com/apache/spark/pull/27085#discussion_r364513358
########## File path: core/src/main/scala/org/apache/spark/deploy/history/EventLogFileCompactor.scala ########## @@ -0,0 +1,224 @@ +/* + * 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.internal.config.{EVENT_LOG_COMPACTION_SCORE_THRESHOLD, EVENT_LOG_ROLLING_MAX_FILES_TO_RETAIN} +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) extends Logging { + private val maxFilesToRetain: Int = sparkConf.get(EVENT_LOG_ROLLING_MAX_FILES_TO_RETAIN) + private val compactionThresholdScore: Double = sparkConf.get(EVENT_LOG_COMPACTION_SCORE_THRESHOLD) + + /** + * 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 class 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]) Review comment: OK will leave them as public. 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