java.io.NotSerializableException: Object of kafka010.DirectKafkaInputDStream being serialized as part of closure of RDD operation

Question

val topics = Array("kafkatopic")
val stream = KafkaUtils.createDirectStream[String, String](
  ssc,
  PreferConsistent,
  Subscribe[String, String](topics, kafkaParams)
)

stream.foreachRDD { rdd =>
  if (!rdd.isEmpty()) {
    val data = rdd.map(record => record.value)
    val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
    val sqlContext: SQLContext = SparkSession.builder.config(rdd.sparkContext.getConf).getOrCreate().sqlContext
    // json parsing and dataframe operations and after this the below code
    stream.asInstanceOf[CanCommitOffsets].commitAsync(offsetRanges)

Is there any problem with this code? Its giving the below error

    at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:628)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:628)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
    at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
    at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
    at scala.util.Try$.apply(Try.scala:192)
    at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:257)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:257)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
    at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:256)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:750)
Caused by: java.io.NotSerializableException: Object of org.apache.spark.streaming.kafka010.DirectKafkaInputDStream is being serialized  possibly as a part of closure of an RDD operation. This is because  the DStream object is being referred to from within the closure.  Please rewrite the RDD operation inside this DStream to avoid this.  This has been enforced to avoid bloating of Spark tasks  with unnecessary objects.
Serialization stack:

    at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40)
    at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46)
    at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
    at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:413)
    ... 44 more