Reputation: 3350
I'm struggling to deserialise Avro serialised data coming off Kafka in Spark Streaming.
This is the file I am running through spark-submit:
package com.example.mymessage
import org.apache.avro.Schema
import org.apache.avro.generic.{GenericDatumReader, GenericRecord}
import org.apache.avro.io.DecoderFactory
import org.apache.log4j.{Level, Logger}
import org.apache.spark.{Logging, SparkConf}
import org.apache.spark.streaming._
import org.apache.spark.streaming.kafka._
object MyMessageCount extends Logging {
def main(args: Array[String]) {
if (args.length < 4) {
System.err.println("Usage: MyMessageCount <zkQuorum> <group> <topics> <numThreads>")
System.exit(1)
}
val log4jInitialized = Logger.getRootLogger.getAllAppenders.hasMoreElements
if (!log4jInitialized) {
logInfo("Setting log level to [WARN]." +
" To override add a custom log4j.properties to the classpath.")
Logger.getRootLogger.setLevel(Level.WARN)
}
val Array(zkQuorum, group, topics, numThreads) = args
val sparkConf = new SparkConf().setMaster("local[4]").setAppName("MyMessageCount")
val ssc = new StreamingContext(sparkConf, Seconds(2))
ssc.checkpoint("checkpoint")
val topicMap = topics.split(",").map((_, numThreads.toInt)).toMap
val lines = KafkaUtils.createStream(ssc, zkQuorum, group, topicMap).map(_._2)
lines.foreachRDD(rdd => {
rdd.foreach(avroRecord => {
val schemaString = "{\"type\":\"record\",\"name\":\"myrecord\",\"fields\":[{\"name\":\"string\",\"type\":\"string\"},{\"name\":\"long\",\"type\":\"long\"}]}"
val parser = new Schema.Parser()
val schema = parser.parse(schemaString)
val reader = new GenericDatumReader[GenericRecord](schema)
val decoder = DecoderFactory.get.binaryDecoder(avroRecord.toCharArray.map(_.toByte), null)
val record: GenericRecord = reader.read(null, decoder)
System.out.println(avroRecord + "," + record.toString
+ ", string= " + record.get("string")
+ ", long=" + record.get("long"))
})
})
ssc.start()
ssc.awaitTermination()
}
}
I have been using the Confluent platform to send it data locally.
If I send:
{"string":"test","long":30}
Then the above code outputs:
test<,{"string": "", "long": 0}, string= , long=0
This suggests to me that the data is coming through but for some reason the string and long values come out as values that look like defaults. How can I access the true "string" and "long" values coming into avroRecord
from Kafka?
Upvotes: 3
Views: 2646
Reputation: 3350
Using Confluent's KafkaAvroDecoder with a direct stream worked for this.
import io.confluent.kafka.serializers.KafkaAvroDecoder
...
val kafkaParams = Map[String, String]("metadata.broker.list" -> zkQuorum,
"schema.registry.url" -> schemaRegistry,
"auto.offset.reset" -> "smallest")
val topicSet = Set(topics)
val messages = KafkaUtils.createDirectStream[Object, Object, KafkaAvroDecoder, KafkaAvroDecoder](ssc, kafkaParams, topicSet).map(_._2)
val lines = messages.foreachRDD(rdd => {
rdd.foreach({ avroRecord =>
println(avroRecord)
})
})
I found a separate issue that I could only import version 1 and not more recent versions.
libraryDependencies ++= Seq(
"io.confluent" % "kafka-avro-serializer" % "1.0",
...
)
resolvers ++= Seq(
Resolver.sonatypeRepo("public"),
Resolver.url("confluent", url("http://packages.confluent.io/maven/"))
)
UPDATE The following worked to get the latest version of kafka-avro-serializer.
libraryDependencies ++= Seq(
"io.confluent" % "kafka-avro-serializer" % "3.0.0",
...
)
resolvers ++= Seq(
Resolver.sonatypeRepo("public"),
"Confluent Maven Repo" at "http://packages.confluent.io/maven/"
)
Upvotes: 3