Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/42#discussion_r10272195
--- Diff: core/src/main/scala/org/apache/spark/util/FileLogger.scala ---
@@ -0,0 +1,158 @@
+/*
+ * 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.util
+
+import java.io._
+import java.text.SimpleDateFormat
+import java.net.URI
+import java.util.Date
+
+import org.apache.spark.Logging
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.hadoop.fs.{FSDataOutputStream, Path, FileSystem}
+
+/**
+ * A generic class for logging information to file.
+ *
+ * @param logBaseDir Path to the directory in which files are logged
+ * @param name An identifier of each FileLogger instance
+ * @param overwriteExistingFiles Whether to overwrite existing files
+ */
+class FileLogger(
+ logBaseDir: String,
+ name: String = String.valueOf(System.currentTimeMillis()),
+ overwriteExistingFiles: Boolean = true)
+ extends Logging {
+
+ private val logDir = logBaseDir.stripSuffix("/") + "/" + name
+ private val DATE_FORMAT = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss")
+ private var fileIndex = 0
+
+ // Only defined if the file system scheme uses the Hadoop API
+ private var hadoopDataStream: Option[FSDataOutputStream] = None
+ private var hadoopFileSystem: Option[FileSystem] = None
+
+ private var writer: Option[PrintWriter] = {
+ createLogDir()
+ createWriter()
+ }
+
+ /** Create a logging directory with the given path */
+ private def createLogDir() {
+ val dir = new File(logDir)
+ if (dir.exists) {
+ logWarning("Logging directory already exists: " + logDir)
+ }
+ if (!dir.exists && !dir.mkdirs()) {
+ // Logger should throw a exception rather than continue to construct
this object
+ throw new IOException("Error in creating log directory:" + logDir)
+ }
+ }
+
+ /**
+ * Create a new writer for the file identified by the given path.
+ *
+ * File systems currently supported include HDFS, S3, and the local file
system.
+ * The Hadoop LocalFileSystem (r1.0.4) has known issues with syncing
(HADOOP-7844).
+ * Therefore, for local files, use FileOutputStream instead.
+ */
+ private def createWriter(): Option[PrintWriter] = {
+ val logPath = logDir + "/" + fileIndex
+ val uri = new URI(logPath)
+
+ val dataStream = uri.getScheme match {
+ case "hdfs" | "s3" =>
+ val fs = hadoopFileSystem.getOrElse {
+ val conf = SparkHadoopUtil.get.newConfiguration()
+ hadoopFileSystem = Some(FileSystem.get(uri, conf))
+ hadoopFileSystem.get
+ }
+ val path = new Path(logPath)
+ hadoopDataStream = Some(fs.create(path, overwriteExistingFiles))
+ hadoopDataStream.get
+
+ case "file" | null =>
+ // Second parameter is whether to append
+ new FileOutputStream(logPath, !overwriteExistingFiles)
+
+ case unsupportedScheme =>
+ throw new UnsupportedOperationException("File system scheme %s is
not supported!"
+ .format(unsupportedScheme))
+ }
+
+ val bufferedStream = new BufferedOutputStream(dataStream)
--- End diff --
I'd also add the option of wrapping this stream for compression.
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