diff options
Diffstat (limited to 'external/flume-sink/src')
6 files changed, 706 insertions, 0 deletions
diff --git a/external/flume-sink/src/main/avro/sparkflume.avdl b/external/flume-sink/src/main/avro/sparkflume.avdl new file mode 100644 index 0000000000..8806e863ac --- /dev/null +++ b/external/flume-sink/src/main/avro/sparkflume.avdl @@ -0,0 +1,40 @@ +/** + * 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. + */ + +@namespace("org.apache.spark.streaming.flume.sink") + +protocol SparkFlumeProtocol { + + record SparkSinkEvent { + map<string> headers; + bytes body; + } + + record EventBatch { + string errorMsg = ""; // If this is empty it is a valid message, else it represents an error + string sequenceNumber; + array<SparkSinkEvent> events; + } + + EventBatch getEventBatch (int n); + + void ack (string sequenceNumber); + + void nack (string sequenceNumber); +} diff --git a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/Logging.scala b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/Logging.scala new file mode 100644 index 0000000000..17cbc6707b --- /dev/null +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/Logging.scala @@ -0,0 +1,125 @@ +/* + * 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.sink + +import org.slf4j.{Logger, LoggerFactory} + +/** + * Copy of the org.apache.spark.Logging for being used in the Spark Sink. + * The org.apache.spark.Logging is not used so that all of Spark is not brought + * in as a dependency. + */ +private[sink] trait Logging { + // Make the log field transient so that objects with Logging can + // be serialized and used on another machine + @transient private var log_ : Logger = null + + // Method to get or create the logger for this object + protected def log: Logger = { + if (log_ == null) { + initializeIfNecessary() + var className = this.getClass.getName + // Ignore trailing $'s in the class names for Scala objects + if (className.endsWith("$")) { + className = className.substring(0, className.length - 1) + } + log_ = LoggerFactory.getLogger(className) + } + log_ + } + + // Log methods that take only a String + protected def logInfo(msg: => String) { + if (log.isInfoEnabled) log.info(msg) + } + + protected def logDebug(msg: => String) { + if (log.isDebugEnabled) log.debug(msg) + } + + protected def logTrace(msg: => String) { + if (log.isTraceEnabled) log.trace(msg) + } + + protected def logWarning(msg: => String) { + if (log.isWarnEnabled) log.warn(msg) + } + + protected def logError(msg: => String) { + if (log.isErrorEnabled) log.error(msg) + } + + // Log methods that take Throwables (Exceptions/Errors) too + protected def logInfo(msg: => String, throwable: Throwable) { + if (log.isInfoEnabled) log.info(msg, throwable) + } + + protected def logDebug(msg: => String, throwable: Throwable) { + if (log.isDebugEnabled) log.debug(msg, throwable) + } + + protected def logTrace(msg: => String, throwable: Throwable) { + if (log.isTraceEnabled) log.trace(msg, throwable) + } + + protected def logWarning(msg: => String, throwable: Throwable) { + if (log.isWarnEnabled) log.warn(msg, throwable) + } + + protected def logError(msg: => String, throwable: Throwable) { + if (log.isErrorEnabled) log.error(msg, throwable) + } + + protected def isTraceEnabled(): Boolean = { + log.isTraceEnabled + } + + private def initializeIfNecessary() { + if (!Logging.initialized) { + Logging.initLock.synchronized { + if (!Logging.initialized) { + initializeLogging() + } + } + } + } + + private def initializeLogging() { + Logging.initialized = true + + // Force a call into slf4j to initialize it. Avoids this happening from mutliple threads + // and triggering this: http://mailman.qos.ch/pipermail/slf4j-dev/2010-April/002956.html + log + } +} + +private[sink] object Logging { + @volatile private var initialized = false + val initLock = new Object() + try { + // We use reflection here to handle the case where users remove the + // slf4j-to-jul bridge order to route their logs to JUL. + val bridgeClass = Class.forName("org.slf4j.bridge.SLF4JBridgeHandler") + bridgeClass.getMethod("removeHandlersForRootLogger").invoke(null) + val installed = bridgeClass.getMethod("isInstalled").invoke(null).asInstanceOf[Boolean] + if (!installed) { + bridgeClass.getMethod("install").invoke(null) + } + } catch { + case e: ClassNotFoundException => // can't log anything yet so just fail silently + } +} 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 new file mode 100644 index 0000000000..7da8eb3e35 --- /dev/null +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkAvroCallbackHandler.scala @@ -0,0 +1,131 @@ +/* + * 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.sink + +import java.util.concurrent.{ConcurrentHashMap, Executors} +import java.util.concurrent.atomic.AtomicLong + +import org.apache.flume.Channel +import org.apache.commons.lang.RandomStringUtils +import com.google.common.util.concurrent.ThreadFactoryBuilder + +/** + * Class that implements the SparkFlumeProtocol, that is used by the Avro Netty Server to process + * requests. Each getEvents, ack and nack call is forwarded to an instance of this class. + * @param threads Number of threads to use to process requests. + * @param channel The channel that the sink pulls events from + * @param transactionTimeout Timeout in millis after which the transaction if not acked by Spark + * is rolled back. + */ +// Flume forces transactions to be thread-local. So each transaction *must* be committed, or +// rolled back from the thread it was originally created in. So each getEvents call from Spark +// creates a TransactionProcessor which runs in a new thread, in which the transaction is created +// and events are pulled off the channel. Once the events are sent to spark, +// that thread is blocked and the TransactionProcessor is saved in a map, +// until an ACK or NACK comes back or the transaction times out (after the specified timeout). +// When the response comes or a timeout is hit, the TransactionProcessor is retrieved and then +// unblocked, at which point the transaction is committed or rolled back. + +private[flume] class SparkAvroCallbackHandler(val threads: Int, val channel: Channel, + val transactionTimeout: Int, val backOffInterval: Int) extends SparkFlumeProtocol with Logging { + val transactionExecutorOpt = Option(Executors.newFixedThreadPool(threads, + new ThreadFactoryBuilder().setDaemon(true) + .setNameFormat("Spark Sink Processor Thread - %d").build())) + private val processorMap = 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. + // Since the new txn may not have the same sequence number we must guard against accidentally + // committing a new transaction. To reduce the probability of that happening a random string is + // prepended to the sequence number. Does not change for life of sink + private val seqBase = RandomStringUtils.randomAlphanumeric(8) + private val seqCounter = new AtomicLong(0) + + /** + * Returns a bunch of events to Spark over Avro RPC. + * @param n Maximum number of events to return in a batch + * @return [[EventBatch]] instance that has a sequence number and an array of at most n events + */ + 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) + } + batch + } + + /** + * Called by Spark to indicate successful commit of a batch + * @param sequenceNumber The sequence number of the event batch that was successful + */ + override def ack(sequenceNumber: CharSequence): Void = { + logDebug("Received Ack for batch with sequence number: " + sequenceNumber) + completeTransaction(sequenceNumber, success = true) + null + } + + /** + * Called by Spark to indicate failed commit of a batch + * @param sequenceNumber The sequence number of the event batch that failed + * @return + */ + override def nack(sequenceNumber: CharSequence): Void = { + completeTransaction(sequenceNumber, success = false) + logInfo("Spark failed to commit transaction. Will reattempt events.") + null + } + + /** + * Helper method to commit or rollback a transaction. + * @param sequenceNumber The sequence number of the batch that was completed + * @param success Whether the batch was successful or not. + */ + private def completeTransaction(sequenceNumber: CharSequence, success: Boolean) { + Option(removeAndGetProcessor(sequenceNumber)).foreach(processor => { + processor.batchProcessed(success) + }) + } + + /** + * Helper method to remove the TxnProcessor for a Sequence Number. Can be used to avoid a leak. + * @param sequenceNumber + * @return The transaction processor for the corresponding batch. Note that this instance is no + * 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! + } + + /** + * Shuts down the executor used to process transactions. + */ + def shutdown() { + logInfo("Shutting down Spark Avro Callback Handler") + transactionExecutorOpt.foreach(executor => { + executor.shutdownNow() + }) + } +} diff --git a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkSink.scala b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkSink.scala new file mode 100644 index 0000000000..7b735133e3 --- /dev/null +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkSink.scala @@ -0,0 +1,154 @@ +/* + * 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.sink + +import java.net.InetSocketAddress +import java.util.concurrent._ + +import org.apache.avro.ipc.NettyServer +import org.apache.avro.ipc.specific.SpecificResponder +import org.apache.flume.Context +import org.apache.flume.Sink.Status +import org.apache.flume.conf.{Configurable, ConfigurationException} +import org.apache.flume.sink.AbstractSink + +/** + * A sink that uses Avro RPC to run a server that can be polled by Spark's + * FlumePollingInputDStream. This sink has the following configuration parameters: + * + * hostname - The hostname to bind to. Default: 0.0.0.0 + * port - The port to bind to. (No default - mandatory) + * timeout - Time in seconds after which a transaction is rolled back, + * if an ACK is not received from Spark within that time + * threads - Number of threads to use to receive requests from Spark (Default: 10) + * + * This sink is unlike other Flume sinks in the sense that it does not push data, + * instead the process method in this sink simply blocks the SinkRunner the first time it is + * called. This sink starts up an Avro IPC server that uses the SparkFlumeProtocol. + * + * Each time a getEventBatch call comes, creates a transaction and reads events + * from the channel. When enough events are read, the events are sent to the Spark receiver and + * the thread itself is blocked and a reference to it saved off. + * + * When the ack for that batch is received, + * the thread which created the transaction is is retrieved and it commits the transaction with the + * channel from the same thread it was originally created in (since Flume transactions are + * thread local). If a nack is received instead, the sink rolls back the transaction. If no ack + * is received within the specified timeout, the transaction is rolled back too. If an ack comes + * after that, it is simply ignored and the events get re-sent. + * + */ + +private[flume] +class SparkSink extends AbstractSink with Logging with Configurable { + + // Size of the pool to use for holding transaction processors. + private var poolSize: Integer = SparkSinkConfig.DEFAULT_THREADS + + // Timeout for each transaction. If spark does not respond in this much time, + // rollback the transaction + private var transactionTimeout = SparkSinkConfig.DEFAULT_TRANSACTION_TIMEOUT + + // Address info to bind on + private var hostname: String = SparkSinkConfig.DEFAULT_HOSTNAME + private var port: Int = 0 + + private var backOffInterval: Int = 200 + + // Handle to the server + private var serverOpt: Option[NettyServer] = None + + // The handler that handles the callback from Avro + private var handler: Option[SparkAvroCallbackHandler] = None + + // Latch that blocks off the Flume framework from wasting 1 thread. + private val blockingLatch = new CountDownLatch(1) + + override def start() { + logInfo("Starting Spark Sink: " + getName + " on port: " + port + " and interface: " + + hostname + " with " + "pool size: " + poolSize + " and transaction timeout: " + + transactionTimeout + ".") + handler = Option(new SparkAvroCallbackHandler(poolSize, getChannel, transactionTimeout, + backOffInterval)) + val responder = new SpecificResponder(classOf[SparkFlumeProtocol], handler.get) + // Using the constructor that takes specific thread-pools requires bringing in netty + // dependencies which are being excluded in the build. In practice, + // Netty dependencies are already available on the JVM as Flume would have pulled them in. + serverOpt = Option(new NettyServer(responder, new InetSocketAddress(hostname, port))) + serverOpt.foreach(server => { + logInfo("Starting Avro server for sink: " + getName) + server.start() + }) + super.start() + } + + override def stop() { + logInfo("Stopping Spark Sink: " + getName) + handler.foreach(callbackHandler => { + callbackHandler.shutdown() + }) + serverOpt.foreach(server => { + logInfo("Stopping Avro Server for sink: " + getName) + server.close() + server.join() + }) + blockingLatch.countDown() + super.stop() + } + + override def configure(ctx: Context) { + import SparkSinkConfig._ + hostname = ctx.getString(CONF_HOSTNAME, DEFAULT_HOSTNAME) + port = Option(ctx.getInteger(CONF_PORT)). + getOrElse(throw new ConfigurationException("The port to bind to must be specified")) + poolSize = ctx.getInteger(THREADS, DEFAULT_THREADS) + transactionTimeout = ctx.getInteger(CONF_TRANSACTION_TIMEOUT, DEFAULT_TRANSACTION_TIMEOUT) + backOffInterval = ctx.getInteger(CONF_BACKOFF_INTERVAL, DEFAULT_BACKOFF_INTERVAL) + logInfo("Configured Spark Sink with hostname: " + hostname + ", port: " + port + ", " + + "poolSize: " + poolSize + ", transactionTimeout: " + transactionTimeout + ", " + + "backoffInterval: " + backOffInterval) + } + + override def process(): Status = { + // This method is called in a loop by the Flume framework - block it until the sink is + // stopped to save CPU resources. The sink runner will interrupt this thread when the sink is + // being shut down. + logInfo("Blocking Sink Runner, sink will continue to run..") + blockingLatch.await() + Status.BACKOFF + } +} + +/** + * Configuration parameters and their defaults. + */ +private[flume] +object SparkSinkConfig { + val THREADS = "threads" + val DEFAULT_THREADS = 10 + + val CONF_TRANSACTION_TIMEOUT = "timeout" + val DEFAULT_TRANSACTION_TIMEOUT = 60 + + val CONF_HOSTNAME = "hostname" + val DEFAULT_HOSTNAME = "0.0.0.0" + + val CONF_PORT = "port" + + val CONF_BACKOFF_INTERVAL = "backoffInterval" + val DEFAULT_BACKOFF_INTERVAL = 200 +} diff --git a/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkSinkUtils.scala b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkSinkUtils.scala new file mode 100644 index 0000000000..47c0e294d6 --- /dev/null +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/SparkSinkUtils.scala @@ -0,0 +1,28 @@ +/* + * 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.sink + +private[flume] object SparkSinkUtils { + /** + * This method determines if this batch represents an error or not. + * @param batch - The batch to check + * @return - true if the batch represents an error + */ + def isErrorBatch(batch: EventBatch): Boolean = { + !batch.getErrorMsg.toString.equals("") // If there is an error message, it is an error batch. + } +} 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 new file mode 100644 index 0000000000..b9e3c786eb --- /dev/null +++ b/external/flume-sink/src/main/scala/org/apache/spark/streaming/flume/sink/TransactionProcessor.scala @@ -0,0 +1,228 @@ +/* + * 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.sink + +import java.nio.ByteBuffer +import java.util +import java.util.concurrent.{Callable, CountDownLatch, TimeUnit} + +import scala.util.control.Breaks + +import org.apache.flume.{Transaction, Channel} + +// Flume forces transactions to be thread-local (horrible, I know!) +// So the sink basically spawns a new thread to pull the events out within a transaction. +// The thread fills in the event batch object that is set before the thread is scheduled. +// After filling it in, the thread waits on a condition - which is released only +// when the success message comes back for the specific sequence number for that event batch. +/** + * This class represents a transaction on the Flume channel. This class runs a separate thread + * which owns the transaction. The thread is blocked until the success call for that transaction + * comes back with an ACK or NACK. + * @param channel The channel from which to pull events + * @param seqNum The sequence number to use for the transaction. Must be unique + * @param maxBatchSize The maximum number of events to process per batch + * @param transactionTimeout Time in seconds after which a transaction must be rolled back + * without waiting for an ACK from Spark + * @param parent The parent [[SparkAvroCallbackHandler]] instance, for reporting timeouts + */ +private class TransactionProcessor(val channel: Channel, val seqNum: String, + var maxBatchSize: Int, val transactionTimeout: Int, val backOffInterval: Int, + val parent: SparkAvroCallbackHandler) extends Callable[Void] with Logging { + + // If a real batch is not returned, we always have to return an error batch. + @volatile private var eventBatch: EventBatch = new EventBatch("Unknown Error", "", + util.Collections.emptyList()) + + // Synchronization primitives + val batchGeneratedLatch = new CountDownLatch(1) + val batchAckLatch = new CountDownLatch(1) + + // Sanity check to ensure we don't loop like crazy + val totalAttemptsToRemoveFromChannel = Int.MaxValue / 2 + + // OK to use volatile, since the change would only make this true (otherwise it will be + // changed to false - we never apply a negation operation to this) - which means the transaction + // succeeded. + @volatile private var batchSuccess = false + + // The transaction that this processor would handle + var txOpt: Option[Transaction] = None + + /** + * Get an event batch from the channel. This method will block until a batch of events is + * available from the channel. If no events are available after a large number of attempts of + * polling the channel, this method will return an [[EventBatch]] with a non-empty error message + * + * @return An [[EventBatch]] instance with sequence number set to seqNum, filled with a + * maximum of maxBatchSize events + */ + def getEventBatch: EventBatch = { + batchGeneratedLatch.await() + eventBatch + } + + /** + * This method is to be called by the sink when it receives an ACK or NACK from Spark. This + * method is a no-op if it is called after transactionTimeout has expired since + * getEventBatch returned a batch of events. + * @param success True if an ACK was received and the transaction should be committed, else false. + */ + def batchProcessed(success: Boolean) { + logDebug("Batch processed for sequence number: " + seqNum) + batchSuccess = success + batchAckLatch.countDown() + } + + /** + * 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. + */ + private def populateEvents() { + try { + txOpt = Option(channel.getTransaction) + if(txOpt.isEmpty) { + eventBatch.setErrorMsg("Something went wrong. Channel was " + + "unable to create a transaction!") + } + txOpt.foreach(tx => { + tx.begin() + val events = new util.ArrayList[SparkSinkEvent](maxBatchSize) + val loop = new Breaks + var gotEventsInThisTxn = false + var loopCounter: Int = 0 + loop.breakable { + while (events.size() < maxBatchSize + && loopCounter < totalAttemptsToRemoveFromChannel) { + loopCounter += 1 + Option(channel.take()) match { + case Some(event) => + events.add(new SparkSinkEvent(toCharSequenceMap(event.getHeaders), + ByteBuffer.wrap(event.getBody))) + gotEventsInThisTxn = true + case None => + if (!gotEventsInThisTxn) { + logDebug("Sleeping for " + backOffInterval + " millis as no events were read in" + + " the current transaction") + TimeUnit.MILLISECONDS.sleep(backOffInterval) + } else { + loop.break() + } + } + } + } + if (!gotEventsInThisTxn) { + val msg = "Tried several times, " + + "but did not get any events from the channel!" + logWarning(msg) + eventBatch.setErrorMsg(msg) + } else { + // At this point, the events are available, so fill them into the event batch + eventBatch = new EventBatch("",seqNum, events) + } + }) + } catch { + case e: Exception => + logWarning("Error while processing transaction.", e) + eventBatch.setErrorMsg(e.getMessage) + try { + txOpt.foreach(tx => { + rollbackAndClose(tx, close = true) + }) + } finally { + txOpt = None + } + } finally { + batchGeneratedLatch.countDown() + } + } + + /** + * Waits for upto transactionTimeout seconds for an ACK. If an ACK comes in + * this method commits the transaction with the channel. If the ACK does not come in within + * that time or a NACK comes in, this method rolls back the transaction. + */ + private def processAckOrNack() { + batchAckLatch.await(transactionTimeout, TimeUnit.SECONDS) + txOpt.foreach(tx => { + if (batchSuccess) { + try { + logDebug("Committing transaction") + tx.commit() + } catch { + case e: Exception => + logWarning("Error while attempting to commit transaction. Transaction will be rolled " + + "back", e) + rollbackAndClose(tx, close = false) // tx will be closed later anyway + } finally { + tx.close() + } + } else { + logWarning("Spark could not commit transaction, NACK received. Rolling back transaction.") + rollbackAndClose(tx, close = true) + // This might have been due to timeout or a NACK. Either way the following call does not + // cause issues. This is required to ensure the TransactionProcessor instance is not leaked + parent.removeAndGetProcessor(seqNum) + } + }) + } + + /** + * Helper method to rollback and optionally close a transaction + * @param tx The transaction to rollback + * @param close Whether the transaction should be closed or not after rolling back + */ + private def rollbackAndClose(tx: Transaction, close: Boolean) { + try { + logWarning("Spark was unable to successfully process the events. Transaction is being " + + "rolled back.") + tx.rollback() + } catch { + case e: Exception => + logError("Error rolling back transaction. Rollback may have failed!", e) + } finally { + if (close) { + tx.close() + } + } + } + + /** + * Helper method to convert a Map[String, String] to Map[CharSequence, CharSequence] + * @param inMap The map to be converted + * @return The converted map + */ + private def toCharSequenceMap(inMap: java.util.Map[String, String]): java.util.Map[CharSequence, + CharSequence] = { + val charSeqMap = new util.HashMap[CharSequence, CharSequence](inMap.size()) + charSeqMap.putAll(inMap) + charSeqMap + } + + /** + * When the thread is started it sets as many events as the batch size or less (if enough + * events aren't available) into the eventBatch and object and lets any threads waiting on the + * [[getEventBatch]] method to proceed. Then this thread waits for acks or nacks to come in, + * or for a specified timeout and commits or rolls back the transaction. + * @return + */ + override def call(): Void = { + populateEvents() + processAckOrNack() + null + } +} |