Created
December 11, 2014 11:13
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LowLevelKafkaConsumer
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import consumer.kafka.client.KafkaReceiver | |
import org.apache.spark.streaming.{Seconds, StreamingContext} | |
import org.apache.spark.{SparkContext, SparkConf} | |
/** | |
* Created by akhld on 11/12/14. | |
*/ | |
object LowLevelKafkaConsumer { | |
def main(arg: Array[String]): Unit = { | |
import org.apache.log4j.Logger | |
import org.apache.log4j.Level | |
Logger.getLogger("org").setLevel(Level.OFF) | |
Logger.getLogger("akka").setLevel(Level.OFF) | |
//Create SparkContext | |
val conf = new SparkConf() | |
.setMaster("spark://akhldz:7077") | |
.setAppName("LowLevelKafka") | |
.set("spark.executor.memory", "1g") | |
.set("spark.rdd.compress","true") | |
.set("spark.storage.memoryFraction", "1") | |
.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer") | |
.set("spark.streaming.unpersist", "true") | |
.set("spark.streaming.blockInterval", "200") | |
val sc = new SparkContext(conf) | |
sc.addJar("/home/akhld/.ivy2/cache/org.apache.spark/spark-streaming-kafka_2.10/jars/spark-streaming-kafka_2.10-1.1.0.jar") | |
sc.addJar("/home/akhld/.ivy2/cache/com.101tec/zkclient/jars/zkclient-0.3.jar") | |
sc.addJar("/home/akhld/.ivy2/cache/com.yammer.metrics/metrics-core/jars/metrics-core-2.2.0.jar") | |
sc.addJar("/home/akhld/.ivy2/cache/org.apache.kafka/kafka_2.10/jars/kafka_2.10-0.8.0.jar") | |
sc.addJar("/home/akhld/benchmark/jar/target/scala-2.10/pubmatic_2.10-1.0.jar") | |
sc.addJar("/home/akhld/benchmark/kafka-spark-consumer/target/kafka-spark-consumer-0.0.1-SNAPSHOT-jar-with-dependencies.jar") | |
val ssc = new StreamingContext(sc, Seconds(10)) | |
val topic = "partitions3" | |
val topics_map = Map(topic -> 10) | |
val zkhosts = "10.67.122.211" | |
val zkports = "2181" | |
val brokerPath = "/broker" | |
val kafkaProperties: Map[String, String] = Map("zookeeper.hosts" -> zkhosts, "zookeeper.port" -> zkports, | |
"zookeeper.broker.path" -> brokerPath , "kafka.topic" -> topic, | |
"zookeeper.consumer.connection" -> "localhost:2182", "zookeeper.consumer.path" -> "/spark-kafka", "kafka.consumer.id" -> "12345") | |
val props = new java.util.Properties() | |
kafkaProperties foreach { case (key,value) => props.put(key, value)} | |
val partitions = 3 | |
val kafkaStreams = (1 to partitions).map { i=> | |
ssc.receiverStream(new KafkaReceiver(props, i)) | |
} | |
val tmp_stream = ssc.union(kafkaStreams) | |
tmp_stream.foreachRDD(rdd => println("\n\nNumber of records in this batch : " + rdd.count())) | |
tmp_stream.print() | |
ssc.start() | |
ssc.awaitTermination() | |
} | |
} |
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