HeartSaVioR commented on a change in pull request #25670: [SPARK-28869][CORE] Roll over event log files URL: https://github.com/apache/spark/pull/25670#discussion_r325925937
########## File path: core/src/main/scala/org/apache/spark/scheduler/EventLogFileWriters.scala ########## @@ -0,0 +1,444 @@ +/* + * 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.scheduler + +import java.io._ +import java.net.URI + +import scala.collection.mutable.Map + +import org.apache.commons.compress.utils.CountingOutputStream +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.{FileStatus, FileSystem, FSDataOutputStream, Path} +import org.apache.hadoop.fs.permission.FsPermission + +import org.apache.spark.SparkConf +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.internal.Logging +import org.apache.spark.internal.config._ +import org.apache.spark.io.CompressionCodec +import org.apache.spark.util.Utils + +/** + * The base class of writer which will write event logs into file. + * + * The following configurable parameters are available to tune the behavior of writing: + * spark.eventLog.compress - Whether to compress logged events + * spark.eventLog.compression.codec - The codec to compress logged events + * spark.eventLog.overwrite - Whether to overwrite any existing files + * spark.eventLog.buffer.kb - Buffer size to use when writing to output streams + * + * Note that descendant classes can maintain its own parameters: refer the javadoc of each class + * for more details. + * + * NOTE: CountingOutputStream being returned by "initLogFile" counts "non-compressed" bytes. + */ +abstract class EventLogFileWriter( + appId: String, + appAttemptId : Option[String], + logBaseDir: URI, + sparkConf: SparkConf, + hadoopConf: Configuration) extends Logging { + + protected val shouldCompress = sparkConf.get(EVENT_LOG_COMPRESS) + protected val shouldOverwrite = sparkConf.get(EVENT_LOG_OVERWRITE) + protected val shouldAllowECLogs = sparkConf.get(EVENT_LOG_ALLOW_EC) + protected val outputBufferSize = sparkConf.get(EVENT_LOG_OUTPUT_BUFFER_SIZE).toInt + protected val fileSystem = Utils.getHadoopFileSystem(logBaseDir, hadoopConf) + protected val compressionCodec = + if (shouldCompress) { + Some(CompressionCodec.createCodec(sparkConf, sparkConf.get(EVENT_LOG_COMPRESSION_CODEC))) + } else { + None + } + + private[scheduler] val compressionCodecName = compressionCodec.map { c => + CompressionCodec.getShortName(c.getClass.getName) + } + + protected def requireLogBaseDirAsDirectory(): Unit = { + if (!fileSystem.getFileStatus(new Path(logBaseDir)).isDirectory) { + throw new IllegalArgumentException(s"Log directory $logBaseDir is not a directory.") + } + } + + protected def initLogFile(path: Path): (Option[FSDataOutputStream], + Option[CountingOutputStream]) = { + + if (shouldOverwrite && fileSystem.delete(path, true)) { + logWarning(s"Event log $path already exists. Overwriting...") + } + + val defaultFs = FileSystem.getDefaultUri(hadoopConf).getScheme + val isDefaultLocal = defaultFs == null || defaultFs == "file" + val uri = path.toUri + + var hadoopDataStream: Option[FSDataOutputStream] = None + /* The Hadoop LocalFileSystem (r1.0.4) has known issues with syncing (HADOOP-7844). + * Therefore, for local files, use FileOutputStream instead. */ + val dstream = + if ((isDefaultLocal && uri.getScheme == null) || uri.getScheme == "file") { + new FileOutputStream(uri.getPath) + } else { + hadoopDataStream = Some(if (shouldAllowECLogs) { + fileSystem.create(path) + } else { + SparkHadoopUtil.createNonECFile(fileSystem, path) + }) + hadoopDataStream.get + } + + try { + val cstream = compressionCodec.map(_.compressedOutputStream(dstream)).getOrElse(dstream) + val bstream = new BufferedOutputStream(cstream, outputBufferSize) + val ostream = new CountingOutputStream(bstream) + fileSystem.setPermission(path, EventLogFileWriter.LOG_FILE_PERMISSIONS) + logInfo(s"Logging events to $path") + + (hadoopDataStream, Some(ostream)) + } catch { + case e: Exception => + dstream.close() + throw e + } + } + + protected def renameFile(src: Path, dest: Path, overwrite: Boolean): Unit = { + if (fileSystem.exists(dest)) { + if (overwrite) { + logWarning(s"Event log $dest already exists. Overwriting...") + if (!fileSystem.delete(dest, true)) { + logWarning(s"Error deleting $dest") + } + } else { + throw new IOException(s"Target log file already exists ($dest)") + } + } + fileSystem.rename(src, dest) + // touch file to ensure modtime is current across those filesystems where rename() + // does not set it, -and which support setTimes(); it's a no-op on most object stores + try { + fileSystem.setTimes(dest, System.currentTimeMillis(), -1) + } catch { + case e: Exception => logDebug(s"failed to set time of $dest", e) + } + } + + // ================ methods to be override ================ + + /** starts writer instance - initialize writer for event logging */ + def start(): Unit + + /** writes JSON format of event to file */ + def writeEvent(eventJson: String, flushLogger: Boolean = false): Unit + + /** stops writer - indicating the application has been completed */ + def stop(): Unit + + /** returns representative path of log */ + def logPath: String +} + +object EventLogFileWriter { + // Suffix applied to the names of files still being written by applications. + val IN_PROGRESS = ".inprogress" + + val LOG_FILE_PERMISSIONS = new FsPermission(Integer.parseInt("770", 8).toShort) + + def createEventLogFileWriter( + appId: String, + appAttemptId: Option[String], + logBaseDir: URI, + sparkConf: SparkConf, + hadoopConf: Configuration): EventLogFileWriter = { + if (sparkConf.get(EVENT_LOG_ENABLE_ROLLING)) { + new RollingEventLogFilesWriter(appId, appAttemptId, logBaseDir, sparkConf, hadoopConf) + } else { + new SingleEventLogFileWriter(appId, appAttemptId, logBaseDir, sparkConf, hadoopConf) + } + } + + def nameForAppAndAttempt(appId: String, appAttemptId: Option[String]): String = { + val base = Utils.sanitizeDirName(appId) + if (appAttemptId.isDefined) { + base + "_" + Utils.sanitizeDirName(appAttemptId.get) + } else { + base + } + } + + def codecName(log: Path): Option[String] = { + // Compression codec is encoded as an extension, e.g. app_123.lzf + // Since we sanitize the app ID to not include periods, it is safe to split on it + val logName = log.getName.stripSuffix(IN_PROGRESS) + logName.split("\\.").tail.lastOption + } +} + +/** + * The writer to write event logs into single file. + */ +class SingleEventLogFileWriter( + appId: String, + appAttemptId : Option[String], + logBaseDir: URI, + sparkConf: SparkConf, + hadoopConf: Configuration) + extends EventLogFileWriter(appId, appAttemptId, logBaseDir, sparkConf, hadoopConf) with Logging { + + override val logPath: String = SingleEventLogFileWriter.getLogPath(logBaseDir, appId, + appAttemptId, compressionCodecName) + + private val inProgressPath = logPath + EventLogFileWriter.IN_PROGRESS + + // Only defined if the file system scheme is not local + private var hadoopDataStream: Option[FSDataOutputStream] = None + + private var writer: Option[PrintWriter] = None + + override def start(): Unit = { + requireLogBaseDirAsDirectory() + + val streams = initLogFile(new Path(inProgressPath)) + hadoopDataStream = streams._1 + if (streams._2.isDefined) { + writer = Some(new PrintWriter(streams._2.get)) Review comment: https://issues.apache.org/jira/browse/SPARK-29160 ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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