unable to read kafka topic data using spark - apache-spark

Question

I have data like below in one of the topics which I created named "sampleTopic"
sid,Believer
Where the first argument is the username and the second argument is the song name which the user frequently listens. Now, I have started zookeeper, Kafka server, and producer with the topic name as mentioned above. I have entered the above data for that topic using CMD. Now, I want to read the topic in spark perform some aggregation, and write it back to stream. Below is my code:
package com.sparkKafka
import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession
object SparkKafkaTopic {
def main(args: Array[String]) {
val spark = SparkSession.builder().appName("SparkKafka").master("local[*]").getOrCreate()
println("hey")
val df = spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "localhost:9092")
.option("subscribe", "sampleTopic1")
.load()
val query = df.writeStream
.outputMode("append")
.format("console")
.start().awaitTermination()
}
}
However, when I execute the above code it gives :
+----+--------------------+------------+---------+------+--------------------+-------------+
| key| value| topic|partition|offset| timestamp|timestampType|
+----+--------------------+------------+---------+------+--------------------+-------------+
|null|[73 69 64 64 68 6...|sampleTopic1| 0| 4|2020-05-31 12:12:...| 0|
+----+--------------------+------------+---------+------+--------------------+-------------+
with infinite below looping messages too
20/05/31 11:56:12 INFO Fetcher: [Consumer clientId=consumer-1, groupId=spark-kafka-source-0d6807b9-fcc9-4847-abeb-f0b81ab25187--264582860-driver-0] Resetting offset for partition sampleTopic1-0 to offset 4.
20/05/31 11:56:12 INFO Fetcher: [Consumer clientId=consumer-1, groupId=spark-kafka-source-0d6807b9-fcc9-4847-abeb-f0b81ab25187--264582860-driver-0] Resetting offset for partition sampleTopic1-0 to offset 4.
20/05/31 11:56:12 INFO Fetcher: [Consumer clientId=consumer-1, groupId=spark-kafka-source-0d6807b9-fcc9-4847-abeb-f0b81ab25187--264582860-driver-0] Resetting offset for partition sampleTopic1-0 to offset 4.
20/05/31 11:56:12 INFO Fetcher: [Consumer clientId=consumer-1, groupId=spark-kafka-source-0d6807b9-fcc9-4847-abeb-f0b81ab25187--264582860-driver-0] Resetting offset for partition sampleTopic1-0 to offset 4.
20/05/31 11:56:12 INFO Fetcher: [Consumer clientId=consumer-1, groupId=spark-kafka-source-0d6807b9-fcc9-4847-abeb-f0b81ab25187--264582860-driver-0] Resetting offset for partition sampleTopic1-0 to offset 4.
20/05/31 11:56:12 INFO Fetcher: [Consumer clientId=consumer-1, groupId=spark-kafka-source-0d6807b9-fcc9-4847-abeb-f0b81ab25187--264582860-driver-0] Resetting offset for partition sampleTopic1-0 to offset 4.
I need output something like below:
As modified on the suggestion by Srinivas I got the following output:
Not sure what exactly is wrong over here. Please guide me through it.

Answer 1

Try to add spark-sql-kafka library to your build file. Check below.
build.sbt
libraryDependencies += "org.apache.spark" %% "spark-sql-kafka-0-10" % "2.3.0"
// Change to Your spark version
pom.xml
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql-kafka-0-10_2.11</artifactId>
<version>2.3.0</version> // Change to Your spark version
</dependency>
Change your code like below
package com.sparkKafka
import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.types._
import org.apache.spark.sql.functions._
case class KafkaMessage(key: String, value: String, topic: String, partition: Int, offset: Long, timestamp: String)
object SparkKafkaTopic {
def main(args: Array[String]) {
//val spark = SparkSession.builder().appName("SparkKafka").master("local[*]").getOrCreate()
println("hey")
val spark = SparkSession.builder().appName("SparkKafka").master("local[*]").getOrCreate()
import spark.implicits._
val mySchema = StructType(Array(
StructField("userName", StringType),
StructField("songName", StringType)))
val df = spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "localhost:9092")
.option("subscribe", "sampleTopic1")
.load()
val query = df
.as[KafkaMessage]
.select(split($"value", ",")(0).as("userName"),split($"value", ",")(1).as("songName"))
.writeStream
.outputMode("append")
.format("console")
.start()
.awaitTermination()
}
}
/*
+------+--------+
|userid|songname|
+------+--------+
| sid|Believer|
+------+--------+
*/
}
}

Answer 2

spark-sql-kafka jar is missing, which is having the implementation of 'kafka' datasource.
you can add the jar using config option or build fat jar which includes spark-sql-kafka jar. Please use relevant version of jar
val spark = SparkSession.builder()
.appName("SparkKafka").master("local[*]")
.config("spark.jars","/path/to/spark-sql-kafka-xxxxxx.jar")
.getOrCreate()