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/*
* 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 java.net.InetSocketAddress
import java.util.concurrent.{LinkedBlockingQueue, TimeUnit, Executors}
import scala.collection.JavaConversions._
import scala.collection.mutable.ArrayBuffer
import scala.reflect.ClassTag
import com.google.common.util.concurrent.ThreadFactoryBuilder
import org.apache.avro.ipc.NettyTransceiver
import org.apache.avro.ipc.specific.SpecificRequestor
import org.jboss.netty.channel.socket.nio.NioClientSocketChannelFactory
import org.apache.spark.Logging
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.dstream.ReceiverInputDStream
import org.apache.spark.streaming.receiver.Receiver
import org.apache.spark.streaming.flume.sink._
/**
* A [[ReceiverInputDStream]] that can be used to read data from several Flume agents running
* [[org.apache.spark.streaming.flume.sink.SparkSink]]s.
* @param _ssc Streaming context that will execute this input stream
* @param addresses List of addresses at which SparkSinks are listening
* @param maxBatchSize Maximum size of a batch
* @param parallelism Number of parallel connections to open
* @param storageLevel The storage level to use.
* @tparam T Class type of the object of this stream
*/
private[streaming] class FlumePollingInputDStream[T: ClassTag](
@transient _ssc: StreamingContext,
val addresses: Seq[InetSocketAddress],
val maxBatchSize: Int,
val parallelism: Int,
storageLevel: StorageLevel
) extends ReceiverInputDStream[SparkFlumeEvent](_ssc) {
override def getReceiver(): Receiver[SparkFlumeEvent] = {
new FlumePollingReceiver(addresses, maxBatchSize, parallelism, storageLevel)
}
}
private[streaming] class FlumePollingReceiver(
addresses: Seq[InetSocketAddress],
maxBatchSize: Int,
parallelism: Int,
storageLevel: StorageLevel
) extends Receiver[SparkFlumeEvent](storageLevel) with Logging {
lazy val channelFactoryExecutor =
Executors.newCachedThreadPool(new ThreadFactoryBuilder().setDaemon(true).
setNameFormat("Flume Receiver Channel Thread - %d").build())
lazy val channelFactory =
new NioClientSocketChannelFactory(channelFactoryExecutor, channelFactoryExecutor)
lazy val receiverExecutor = Executors.newFixedThreadPool(parallelism,
new ThreadFactoryBuilder().setDaemon(true).setNameFormat("Flume Receiver Thread - %d").build())
private lazy val connections = new LinkedBlockingQueue[FlumeConnection]()
override def onStart(): Unit = {
// Create the connections to each Flume agent.
addresses.foreach(host => {
val transceiver = new NettyTransceiver(host, channelFactory)
val client = SpecificRequestor.getClient(classOf[SparkFlumeProtocol.Callback], transceiver)
connections.add(new FlumeConnection(transceiver, client))
})
for (i <- 0 until parallelism) {
logInfo("Starting Flume Polling Receiver worker threads starting..")
// 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)
}
}
}
})
}
}
override def onStop(): Unit = {
logInfo("Shutting down Flume Polling Receiver")
receiverExecutor.shutdownNow()
connections.foreach(connection => {
connection.transceiver.close()
})
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
}
}
/**
* A wrapper around the transceiver and the Avro IPC API.
* @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,
val client: SparkFlumeProtocol.Callback)
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