Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/2991#discussion_r20197017
--- Diff:
external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaReceiver.scala
---
@@ -0,0 +1,135 @@
+/*
+ * 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.kafka
+
+import java.util.Properties
+import java.util.concurrent.Executors
+
+import scala.collection.Map
+import scala.reflect.{classTag, ClassTag}
+
+import kafka.consumer._
+import kafka.serializer.Decoder
+import kafka.utils.VerifiableProperties
+import kafka.utils.ZKStringSerializer
+import org.I0Itec.zkclient._
+
+import org.apache.spark.Logging
+import org.apache.spark.storage.StorageLevel
+import org.apache.spark.streaming.receiver.Receiver
+
+private[streaming]
+class KafkaReceiver[
+ K: ClassTag,
+ V: ClassTag,
+ U <: Decoder[_]: ClassTag,
+ T <: Decoder[_]: ClassTag](
+ kafkaParams: Map[String, String],
+ topics: Map[String, Int],
+ storageLevel: StorageLevel
+ ) extends Receiver[Any](storageLevel) with Logging {
+
+ // Connection to Kafka
+ var consumerConnector: ConsumerConnector = null
+
+ def onStop() {
+ if (consumerConnector != null) {
+ consumerConnector.shutdown()
+ }
+ }
+
+ def onStart() {
+
+ logInfo("Starting Kafka Consumer Stream with group: " +
kafkaParams("group.id"))
+
+ // Kafka connection properties
+ val props = new Properties()
+ kafkaParams.foreach(param => props.put(param._1, param._2))
+
+ val zkConnect = kafkaParams("zookeeper.connect")
+ // Create the connection to the cluster
+ logInfo("Connecting to Zookeeper: " + zkConnect)
+ val consumerConfig = new ConsumerConfig(props)
+ consumerConnector = Consumer.create(consumerConfig)
+ logInfo("Connected to " + zkConnect)
+
+ // When auto.offset.reset is defined, it is our responsibility to try
and whack the
+ // consumer group zk node.
+ if (kafkaParams.contains("auto.offset.reset")) {
+ tryZookeeperConsumerGroupCleanup(zkConnect, kafkaParams("group.id"))
+ }
+
+ val keyDecoder =
classTag[U].runtimeClass.getConstructor(classOf[VerifiableProperties])
+ .newInstance(consumerConfig.props)
+ .asInstanceOf[Decoder[K]]
+ val valueDecoder =
classTag[T].runtimeClass.getConstructor(classOf[VerifiableProperties])
+ .newInstance(consumerConfig.props)
+ .asInstanceOf[Decoder[V]]
+
+ // Create Threads for each Topic/Message Stream we are listening
+ val topicMessageStreams = consumerConnector.createMessageStreams(
+ topics, keyDecoder, valueDecoder)
+
+ val executorPool = Executors.newFixedThreadPool(topics.values.sum)
+ try {
+ // Start the messages handler for each partition
+ topicMessageStreams.values.foreach { streams =>
+ streams.foreach { stream => executorPool.submit(new
MessageHandler(stream)) }
+ }
+ } finally {
+ executorPool.shutdown() // Just causes threads to terminate after
work is done
+ }
+ }
+
+ // Handles Kafka Messages
+ private class MessageHandler[K: ClassTag, V: ClassTag](stream:
KafkaStream[K, V])
+ extends Runnable {
+ def run() {
+ logInfo("Starting MessageHandler.")
+ try {
+ for (msgAndMetadata <- stream) {
--- End diff --
Can you replace this with a while loop? Scala's for loops are less
efficient that plain old while loop.
http://dynamicsofprogramming.blogspot.co.uk/2013/01/loop-performance-and-local-variables-in.html
Not sure how much performance different it is, but better to use while loop
any ways
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