Spark Streaming Kafka stream

Question

I'm having some issues while trying to read from kafka with spark streaming.

My code is:

val sparkConf = new SparkConf().setMaster("local[2]").setAppName("KafkaIngestor")
val ssc = new StreamingContext(sparkConf, Seconds(2))

val kafkaParams = Map[String, String](
  "zookeeper.connect" -> "localhost:2181",
  "group.id" -> "consumergroup",
  "metadata.broker.list" -> "localhost:9092",
  "zookeeper.connection.timeout.ms" -> "10000"
  //"kafka.auto.offset.reset" -> "smallest"
)

val topics = Set("test")
val stream = KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](ssc, kafkaParams, topics)

I previously started zookeeper at port 2181 and Kafka server 0.9.0.0 at port 9092. But I get the following error in the Spark driver:

Exception in thread "main" java.lang.ClassCastException: kafka.cluster.BrokerEndPoint cannot be cast to kafka.cluster.Broker
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3$$anonfun$apply$6$$anonfun$apply$7.apply(KafkaCluster.scala:90)
at scala.Option.map(Option.scala:145)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3$$anonfun$apply$6.apply(KafkaCluster.scala:90)
at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$2$$anonfun$3$$anonfun$apply$6.apply(KafkaCluster.scala:87)

Zookeeper log:

[2015-12-08 00:32:08,226] INFO Got user-level KeeperException when processing sessionid:0x1517ec89dfd0000 type:create cxid:0x34 zxid:0x1d3 txntype:-1 reqpath:n/a Error Path:/brokers/ids Error:KeeperErrorCode = NodeExists for /brokers/ids (org.apache.zookeeper.server.PrepRequestProcessor)

Any hint?

Thank you very much

Leatherback

Answer 1

The problem was related the wrong spark-streaming-kafka version.

As described in the documentation

Kafka: Spark Streaming 1.5.2 is compatible with Kafka 0.8.2.1

So, including

<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka_2.10</artifactId>
    <version>0.8.2.2</version>
</dependency>

in my pom.xml (instead of version 0.9.0.0) solved the issue.

Hope this helps

Leatherback

Answer 2

Kafka10 streaming / Spark 2.1.0 / DCOS / Mesosphere

Ugg I spent all day on this and must have read this post a dozen times. I tried spark 2.0.0, 2.0.1, Kafka 8, Kafka 10. Stay away from Kafka 8 and spark 2.0.x, and dependencies are everything. Start with below. It works.

SBT:

"org.apache.hadoop" % "hadoop-aws" % "2.7.3" excludeAll ExclusionRule(organization = "org.apache.hadoop", name = "hadoop-common"),
"org.apache.spark" %% "spark-core" % "2.1.0",
"org.apache.spark" %% "spark-sql" % "2.1.0" ,
"org.apache.spark" % "spark-streaming-kafka-0-10_2.11" % "2.1.0",
"org.apache.spark" % "spark-streaming_2.11" % "2.1.0"

Working Kafka/Spark Streaming code:

val spark = SparkSession
  .builder()
  .appName("ingest")
  .master("local[4]")
  .getOrCreate()

import spark.implicits._
val ssc = new StreamingContext(spark.sparkContext, Seconds(2))

val topics = Set("water2").toSet

val kafkaParams = Map[String, String](
  "metadata.broker.list"        -> "broker:port,broker:port",
  "bootstrap.servers"           -> "broker:port,broker:port",
  "group.id"                    -> "somegroup",
  "auto.commit.interval.ms"     -> "1000",
  "key.deserializer"            -> "org.apache.kafka.common.serialization.StringDeserializer",
  "value.deserializer"          -> "org.apache.kafka.common.serialization.StringDeserializer",
  "auto.offset.reset"           -> "earliest",
  "enable.auto.commit"          -> "true"
)

val messages = KafkaUtils.createDirectStream[String, String](ssc, PreferConsistent, Subscribe[String, String](topics, kafkaParams))

messages.foreachRDD(rdd => {
  if (rdd.count() >= 1) {
    rdd.map(record => (record.key, record.value))
      .toDS()
      .withColumnRenamed("_2", "value")
      .drop("_1")
      .show(5, false)
    println(rdd.getClass)
  }
})
ssc.start()
ssc.awaitTermination()

Please like if you see this so I can get some reputation points. :)

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