Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/9143#discussion_r44243764
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/util/BatchedWriteAheadLog.scala
---
@@ -0,0 +1,223 @@
+/*
+ * 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.streaming.util
+
+import java.nio.ByteBuffer
+import java.util.concurrent.LinkedBlockingQueue
+import java.util.{Iterator => JIterator}
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+import scala.concurrent.{Await, Promise}
+import scala.concurrent.duration._
+import scala.util.control.NonFatal
+
+import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.util.Utils
+
+/**
+ * A wrapper for a WriteAheadLog that batches records before writing data.
Handles aggregation
+ * during writes, and de-aggregation in the `readAll` method. The end
consumer has to handle
+ * de-aggregation after the `read` method. In addition, the
`WriteAheadLogRecordHandle` returned
+ * after the write will contain the batch of records rather than
individual records.
+ *
+ * When writing a batch of records, the `time` passed to the `wrappedLog`
will be the timestamp
+ * of the latest record in the batch. This is very important in achieving
correctness. Consider the
+ * following example:
+ * We receive records with timestamps 1, 3, 5, 7. We use "log-1" as the
filename. Once we receive
+ * a clean up request for timestamp 3, we would clean up the file "log-1",
and lose data regarding
+ * 5 and 7.
+ *
+ * This means the caller can assume the same write semantics as any other
WriteAheadLog
+ * implementation despite the batching in the background - when the
write() returns, the data is
+ * written to the WAL and is durable. To take advantage of the batching,
the caller can write from
+ * multiple threads, each of which will stay blocked until the
corresponding data has been written.
+ *
+ * All other methods of the WriteAheadLog interface will be passed on to
the wrapped WriteAheadLog.
+ */
+private[util] class BatchedWriteAheadLog(val wrappedLog: WriteAheadLog,
conf: SparkConf)
+ extends WriteAheadLog with Logging {
+
+ import BatchedWriteAheadLog._
+
+ private val walWriteQueue = new LinkedBlockingQueue[Record]()
+
+ // Whether the writer thread is active
+ @volatile private var active: Boolean = true
+ private val buffer = new ArrayBuffer[Record]()
+
+ private val batchedWriterThread = startBatchedWriterThread()
+
+ /**
+ * Write a byte buffer to the log file. This method adds the byteBuffer
to a queue and blocks
+ * until the record is properly written by the parent.
+ */
+ override def write(byteBuffer: ByteBuffer, time: Long):
WriteAheadLogRecordHandle = {
+ val promise = Promise[WriteAheadLogRecordHandle]()
+ val putSuccessfully = synchronized {
+ if (active) {
+ walWriteQueue.offer(Record(byteBuffer, time, promise))
+ true
+ } else {
+ false
+ }
+ }
+ if (putSuccessfully) {
+ Await.result(promise.future,
WriteAheadLogUtils.getBatchingTimeout(conf).milliseconds)
+ } else {
+ throw new IllegalStateException("close() was called on
BatchedWriteAheadLog before " +
+ s"write request with time $time could be fulfilled.")
+ }
+ }
+
+ /**
+ * This method is not supported as the resulting ByteBuffer would
actually require de-aggregation.
+ * This method is primarily used in testing, and to ensure that it is
not used in production,
+ * we throw an UnsupportedOperationException.
+ */
+ override def read(segment: WriteAheadLogRecordHandle): ByteBuffer = {
+ throw new UnsupportedOperationException("read() is not supported for
BatchedWriteAheadLog " +
+ "as the data may require de-aggregation.")
+ }
+
+ /**
+ * Read all the existing logs from the log directory. The output of the
wrapped WriteAheadLog
+ * will be de-aggregated.
+ */
+ override def readAll(): JIterator[ByteBuffer] = {
+ wrappedLog.readAll().asScala.flatMap(deaggregate).asJava
+ }
+
+ /**
+ * Delete the log files that are older than the threshold time.
+ *
+ * This method is handled by the parent WriteAheadLog.
+ */
+ override def clean(threshTime: Long, waitForCompletion: Boolean): Unit =
{
+ wrappedLog.clean(threshTime, waitForCompletion)
+ }
+
+
+ /**
+ * Stop the batched writer thread, fulfill promises with failures and
close the wrapped WAL.
+ */
+ override def close(): Unit = {
+ logInfo(s"BatchedWriteAheadLog shutting down at time:
${System.currentTimeMillis()}.")
+ synchronized {
+ active = false
+ }
+ batchedWriterThread.interrupt()
+ batchedWriterThread.join()
+ while (!walWriteQueue.isEmpty) {
+ val Record(_, time, promise) = walWriteQueue.poll()
+ promise.failure(new IllegalStateException("close() was called on
BatchedWriteAheadLog " +
+ s"before write request with time $time could be fulfilled."))
+ }
+ wrappedLog.close()
+ }
+
+ /** Start the actual log writer on a separate thread. */
+ private def startBatchedWriterThread(): Thread = {
+ val thread = new Thread(new Runnable {
+ override def run(): Unit = {
+ while (active) {
+ try {
+ flushRecords()
+ } catch {
+ case NonFatal(e) =>
+ logWarning("Encountered exception in Batched Writer
Thread.", e)
+ }
+ }
+ logInfo("BatchedWriteAheadLog Writer thread exiting.")
+ }
+ }, "BatchedWriteAheadLog Writer")
+ thread.setDaemon(true)
+ thread.start()
+ thread
+ }
+
+ /** Write all the records in the buffer to the write ahead log. */
+ private def flushRecords(): Unit = {
+ try {
+ buffer.append(walWriteQueue.take())
+ val numBatched = walWriteQueue.drainTo(buffer.asJava) + 1
+ logDebug(s"Received $numBatched records from queue")
+ } catch {
+ case _: InterruptedException =>
+ logWarning("BatchedWriteAheadLog Writer queue interrupted.")
+ }
+ try {
+ var segment: WriteAheadLogRecordHandle = null
+ if (buffer.length > 0) {
+ logDebug(s"Batched ${buffer.length} records for Write Ahead Log
write")
+ // We take the latest record for the timestamp. Please refer to
the class Javadoc for
+ // detailed explanation
+ val time = buffer.last.time
+ segment = wrappedLog.write(aggregate(buffer), time)
+ }
+ buffer.foreach(_.promise.success(segment))
+ } catch {
+ case NonFatal(e) =>
+ logWarning(s"BatchedWriteAheadLog Writer failed to write $buffer",
e)
+ buffer.foreach(_.promise.failure(e))
+ } finally {
+ buffer.clear()
+ }
+ }
+
+ /** Method for querying the queue length during tests. */
+ private[util] def getQueueLength(): Int = walWriteQueue.size()
--- End diff --
ermm.. same problem again.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
