diff options
Diffstat (limited to 'external')
5 files changed, 236 insertions, 86 deletions
diff --git a/external/flume-sink/pom.xml b/external/flume-sink/pom.xml index c1e8e65464..b345276b08 100644 --- a/external/flume-sink/pom.xml +++ b/external/flume-sink/pom.xml @@ -71,6 +71,10 @@ <scope>test</scope> </dependency> <dependency> + <groupId>org.scala-lang</groupId> + <artifactId>scala-library</artifactId> + </dependency> + <dependency> <!-- Netty explicitly added in test as it has been excluded from Flume dependency (to avoid runtime problems when running with diff --git a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkAvroCallbackHandler.scala b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkAvroCallbackHandler.scala index 7da8eb3e35..e77cf7bfa5 100644 --- a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkAvroCallbackHandler.scala +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkAvroCallbackHandler.scala @@ -19,6 +19,8 @@ package org.apache.spark.streaming.flume.sink import java.util.concurrent.{ConcurrentHashMap, Executors} import java.util.concurrent.atomic.AtomicLong +import scala.collection.JavaConversions._ + import org.apache.flume.Channel import org.apache.commons.lang.RandomStringUtils import com.google.common.util.concurrent.ThreadFactoryBuilder @@ -45,7 +47,8 @@ private[flume] class SparkAvroCallbackHandler(val threads: Int, val channel: Cha val transactionExecutorOpt = Option(Executors.newFixedThreadPool(threads, new ThreadFactoryBuilder().setDaemon(true) .setNameFormat("Spark Sink Processor Thread - %d").build())) - private val processorMap = new ConcurrentHashMap[CharSequence, TransactionProcessor]() + private val sequenceNumberToProcessor = + new ConcurrentHashMap[CharSequence, TransactionProcessor]() // This sink will not persist sequence numbers and reuses them if it gets restarted. // So it is possible to commit a transaction which may have been meant for the sink before the // restart. @@ -55,6 +58,8 @@ private[flume] class SparkAvroCallbackHandler(val threads: Int, val channel: Cha private val seqBase = RandomStringUtils.randomAlphanumeric(8) private val seqCounter = new AtomicLong(0) + @volatile private var stopped = false + /** * Returns a bunch of events to Spark over Avro RPC. * @param n Maximum number of events to return in a batch @@ -63,18 +68,33 @@ private[flume] class SparkAvroCallbackHandler(val threads: Int, val channel: Cha override def getEventBatch(n: Int): EventBatch = { logDebug("Got getEventBatch call from Spark.") val sequenceNumber = seqBase + seqCounter.incrementAndGet() - val processor = new TransactionProcessor(channel, sequenceNumber, - n, transactionTimeout, backOffInterval, this) - transactionExecutorOpt.foreach(executor => { - executor.submit(processor) - }) - // Wait until a batch is available - will be an error if error message is non-empty - val batch = processor.getEventBatch - if (!SparkSinkUtils.isErrorBatch(batch)) { - processorMap.put(sequenceNumber.toString, processor) - logDebug("Sending event batch with sequence number: " + sequenceNumber) + createProcessor(sequenceNumber, n) match { + case Some(processor) => + transactionExecutorOpt.foreach(_.submit(processor)) + // Wait until a batch is available - will be an error if error message is non-empty + val batch = processor.getEventBatch + if (SparkSinkUtils.isErrorBatch(batch)) { + // Remove the processor if it is an error batch since no ACK is sent. + removeAndGetProcessor(sequenceNumber) + logWarning("Received an error batch - no events were received from channel! ") + } + batch + case None => + new EventBatch("Spark sink has been stopped!", "", java.util.Collections.emptyList()) + } + } + + private def createProcessor(seq: String, n: Int): Option[TransactionProcessor] = { + sequenceNumberToProcessor.synchronized { + if (!stopped) { + val processor = new TransactionProcessor( + channel, seq, n, transactionTimeout, backOffInterval, this) + sequenceNumberToProcessor.put(seq, processor) + Some(processor) + } else { + None + } } - batch } /** @@ -116,7 +136,9 @@ private[flume] class SparkAvroCallbackHandler(val threads: Int, val channel: Cha * longer tracked and the caller is responsible for that txn processor. */ private[sink] def removeAndGetProcessor(sequenceNumber: CharSequence): TransactionProcessor = { - processorMap.remove(sequenceNumber.toString) // The toString is required! + sequenceNumberToProcessor.synchronized { + sequenceNumberToProcessor.remove(sequenceNumber.toString) + } } /** @@ -124,8 +146,10 @@ private[flume] class SparkAvroCallbackHandler(val threads: Int, val channel: Cha */ def shutdown() { logInfo("Shutting down Spark Avro Callback Handler") - transactionExecutorOpt.foreach(executor => { - executor.shutdownNow() - }) + sequenceNumberToProcessor.synchronized { + stopped = true + sequenceNumberToProcessor.values().foreach(_.shutdown()) + } + transactionExecutorOpt.foreach(_.shutdownNow()) } } diff --git a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/TransactionProcessor.scala b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/TransactionProcessor.scala index b9e3c786eb..13f3aa94be 100644 --- a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/TransactionProcessor.scala +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/TransactionProcessor.scala @@ -60,6 +60,8 @@ private class TransactionProcessor(val channel: Channel, val seqNum: String, // succeeded. @volatile private var batchSuccess = false + @volatile private var stopped = false + // The transaction that this processor would handle var txOpt: Option[Transaction] = None @@ -88,6 +90,11 @@ private class TransactionProcessor(val channel: Channel, val seqNum: String, batchAckLatch.countDown() } + private[flume] def shutdown(): Unit = { + logDebug("Shutting down transaction processor") + stopped = true + } + /** * Populates events into the event batch. If the batch cannot be populated, * this method will not set the events into the event batch, but it sets an error message. @@ -106,7 +113,7 @@ private class TransactionProcessor(val channel: Channel, val seqNum: String, var gotEventsInThisTxn = false var loopCounter: Int = 0 loop.breakable { - while (events.size() < maxBatchSize + while (!stopped && events.size() < maxBatchSize && loopCounter < totalAttemptsToRemoveFromChannel) { loopCounter += 1 Option(channel.take()) match { @@ -115,7 +122,7 @@ private class TransactionProcessor(val channel: Channel, val seqNum: String, ByteBuffer.wrap(event.getBody))) gotEventsInThisTxn = true case None => - if (!gotEventsInThisTxn) { + if (!gotEventsInThisTxn && !stopped) { logDebug("Sleeping for " + backOffInterval + " millis as no events were read in" + " the current transaction") TimeUnit.MILLISECONDS.sleep(backOffInterval) @@ -125,7 +132,7 @@ private class TransactionProcessor(val channel: Channel, val seqNum: String, } } } - if (!gotEventsInThisTxn) { + if (!gotEventsInThisTxn && !stopped) { val msg = "Tried several times, " + "but did not get any events from the channel!" logWarning(msg) @@ -136,6 +143,11 @@ private class TransactionProcessor(val channel: Channel, val seqNum: String, } }) } catch { + case interrupted: InterruptedException => + // Don't pollute logs if the InterruptedException came from this being stopped + if (!stopped) { + logWarning("Error while processing transaction.", interrupted) + } case e: Exception => logWarning("Error while processing transaction.", e) eventBatch.setErrorMsg(e.getMessage) diff --git a/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumeBatchFetcher.scala b/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumeBatchFetcher.scala new file mode 100644 index 0000000000..88cc2aa3bf --- /dev/null +++ b/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumeBatchFetcher.scala @@ -0,0 +1,167 @@ +/* + * 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.flume + +import scala.collection.JavaConversions._ +import scala.collection.mutable.ArrayBuffer + +import com.google.common.base.Throwables + +import org.apache.spark.Logging +import org.apache.spark.streaming.flume.sink._ + +/** + * This class implements the core functionality of [[FlumePollingReceiver]]. When started it + * pulls data from Flume, stores it to Spark and then sends an Ack or Nack. This class should be + * run via an [[java.util.concurrent.Executor]] as this implements [[Runnable]] + * + * @param receiver The receiver that owns this instance. + */ + +private[flume] class FlumeBatchFetcher(receiver: FlumePollingReceiver) extends Runnable with + Logging { + + def run(): Unit = { + while (!receiver.isStopped()) { + val connection = receiver.getConnections.poll() + val client = connection.client + var batchReceived = false + var seq: CharSequence = null + try { + getBatch(client) match { + case Some(eventBatch) => + batchReceived = true + seq = eventBatch.getSequenceNumber + val events = toSparkFlumeEvents(eventBatch.getEvents) + if (store(events)) { + sendAck(client, seq) + } else { + sendNack(batchReceived, client, seq) + } + case None => + } + } catch { + case e: Exception => + Throwables.getRootCause(e) match { + // If the cause was an InterruptedException, then check if the receiver is stopped - + // if yes, just break out of the loop. Else send a Nack and log a warning. + // In the unlikely case, the cause was not an Exception, + // then just throw it out and exit. + case interrupted: InterruptedException => + if (!receiver.isStopped()) { + logWarning("Interrupted while receiving data from Flume", interrupted) + sendNack(batchReceived, client, seq) + } + case exception: Exception => + logWarning("Error while receiving data from Flume", exception) + sendNack(batchReceived, client, seq) + } + } finally { + receiver.getConnections.add(connection) + } + } + } + + /** + * Gets a batch of events from the specified client. This method does not handle any exceptions + * which will be propogated to the caller. + * @param client Client to get events from + * @return [[Some]] which contains the event batch if Flume sent any events back, else [[None]] + */ + private def getBatch(client: SparkFlumeProtocol.Callback): Option[EventBatch] = { + val eventBatch = client.getEventBatch(receiver.getMaxBatchSize) + if (!SparkSinkUtils.isErrorBatch(eventBatch)) { + // No error, proceed with processing data + logDebug(s"Received batch of ${eventBatch.getEvents.size} events with sequence " + + s"number: ${eventBatch.getSequenceNumber}") + Some(eventBatch) + } else { + logWarning("Did not receive events from Flume agent due to error on the Flume agent: " + + eventBatch.getErrorMsg) + None + } + } + + /** + * Store the events in the buffer to Spark. This method will not propogate any exceptions, + * but will propogate any other errors. + * @param buffer The buffer to store + * @return true if the data was stored without any exception being thrown, else false + */ + private def store(buffer: ArrayBuffer[SparkFlumeEvent]): Boolean = { + try { + receiver.store(buffer) + true + } catch { + case e: Exception => + logWarning("Error while attempting to store data received from Flume", e) + false + } + } + + /** + * Send an ack to the client for the sequence number. This method does not handle any exceptions + * which will be propagated to the caller. + * @param client client to send the ack to + * @param seq sequence number of the batch to be ack-ed. + * @return + */ + private def sendAck(client: SparkFlumeProtocol.Callback, seq: CharSequence): Unit = { + logDebug("Sending ack for sequence number: " + seq) + client.ack(seq) + logDebug("Ack sent for sequence number: " + seq) + } + + /** + * This method sends a Nack if a batch was received to the client with the given sequence + * number. Any exceptions thrown by the RPC call is simply thrown out as is - no effort is made + * to handle it. + * @param batchReceived true if a batch was received. If this is false, no nack is sent + * @param client The client to which the nack should be sent + * @param seq The sequence number of the batch that is being nack-ed. + */ + private def sendNack(batchReceived: Boolean, client: SparkFlumeProtocol.Callback, + seq: CharSequence): Unit = { + if (batchReceived) { + // Let Flume know that the events need to be pushed back into the channel. + logDebug("Sending nack for sequence number: " + seq) + client.nack(seq) // If the agent is down, even this could fail and throw + logDebug("Nack sent for sequence number: " + seq) + } + } + + /** + * Utility method to convert [[SparkSinkEvent]]s to [[SparkFlumeEvent]]s + * @param events - Events to convert to SparkFlumeEvents + * @return - The SparkFlumeEvent generated from SparkSinkEvent + */ + private def toSparkFlumeEvents(events: java.util.List[SparkSinkEvent]): + ArrayBuffer[SparkFlumeEvent] = { + // Convert each Flume event to a serializable SparkFlumeEvent + val buffer = new ArrayBuffer[SparkFlumeEvent](events.size()) + var j = 0 + while (j < events.size()) { + val event = events(j) + val sparkFlumeEvent = new SparkFlumeEvent() + sparkFlumeEvent.event.setBody(event.getBody) + sparkFlumeEvent.event.setHeaders(event.getHeaders) + buffer += sparkFlumeEvent + j += 1 + } + buffer + } +} diff --git a/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumePollingInputDStream.scala b/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumePollingInputDStream.scala index 148262bb67..92fa5b41be 100644 --- a/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumePollingInputDStream.scala +++ b/external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumePollingInputDStream.scala @@ -18,10 +18,9 @@ package org.apache.spark.streaming.flume import java.net.InetSocketAddress -import java.util.concurrent.{LinkedBlockingQueue, TimeUnit, Executors} +import java.util.concurrent.{LinkedBlockingQueue, Executors} import scala.collection.JavaConversions._ -import scala.collection.mutable.ArrayBuffer import scala.reflect.ClassTag import com.google.common.util.concurrent.ThreadFactoryBuilder @@ -86,61 +85,9 @@ private[streaming] class FlumePollingReceiver( connections.add(new FlumeConnection(transceiver, client)) }) for (i <- 0 until parallelism) { - logInfo("Starting Flume Polling Receiver worker threads starting..") + logInfo("Starting Flume Polling Receiver worker threads..") // Threads that pull data from Flume. - receiverExecutor.submit(new Runnable { - override def run(): Unit = { - while (true) { - val connection = connections.poll() - val client = connection.client - try { - val eventBatch = client.getEventBatch(maxBatchSize) - if (!SparkSinkUtils.isErrorBatch(eventBatch)) { - // No error, proceed with processing data - val seq = eventBatch.getSequenceNumber - val events: java.util.List[SparkSinkEvent] = eventBatch.getEvents - logDebug( - "Received batch of " + events.size() + " events with sequence number: " + seq) - try { - // Convert each Flume event to a serializable SparkFlumeEvent - val buffer = new ArrayBuffer[SparkFlumeEvent](events.size()) - var j = 0 - while (j < events.size()) { - buffer += toSparkFlumeEvent(events(j)) - j += 1 - } - store(buffer) - logDebug("Sending ack for sequence number: " + seq) - // Send an ack to Flume so that Flume discards the events from its channels. - client.ack(seq) - logDebug("Ack sent for sequence number: " + seq) - } catch { - case e: Exception => - try { - // Let Flume know that the events need to be pushed back into the channel. - logDebug("Sending nack for sequence number: " + seq) - client.nack(seq) // If the agent is down, even this could fail and throw - logDebug("Nack sent for sequence number: " + seq) - } catch { - case e: Exception => logError( - "Sending Nack also failed. A Flume agent is down.") - } - TimeUnit.SECONDS.sleep(2L) // for now just leave this as a fixed 2 seconds. - logWarning("Error while attempting to store events", e) - } - } else { - logWarning("Did not receive events from Flume agent due to error on the Flume " + - "agent: " + eventBatch.getErrorMsg) - } - } catch { - case e: Exception => - logWarning("Error while reading data from Flume", e) - } finally { - connections.add(connection) - } - } - } - }) + receiverExecutor.submit(new FlumeBatchFetcher(this)) } } @@ -153,16 +100,12 @@ private[streaming] class FlumePollingReceiver( channelFactory.releaseExternalResources() } - /** - * Utility method to convert [[SparkSinkEvent]] to [[SparkFlumeEvent]] - * @param event - Event to convert to SparkFlumeEvent - * @return - The SparkFlumeEvent generated from SparkSinkEvent - */ - private def toSparkFlumeEvent(event: SparkSinkEvent): SparkFlumeEvent = { - val sparkFlumeEvent = new SparkFlumeEvent() - sparkFlumeEvent.event.setBody(event.getBody) - sparkFlumeEvent.event.setHeaders(event.getHeaders) - sparkFlumeEvent + private[flume] def getConnections: LinkedBlockingQueue[FlumeConnection] = { + this.connections + } + + private[flume] def getMaxBatchSize: Int = { + this.maxBatchSize } } @@ -171,7 +114,7 @@ private[streaming] class FlumePollingReceiver( * @param transceiver The transceiver to use for communication with Flume * @param client The client that the callbacks are received on. */ -private class FlumeConnection(val transceiver: NettyTransceiver, +private[flume] class FlumeConnection(val transceiver: NettyTransceiver, val client: SparkFlumeProtocol.Callback) |