结构化Spark Streaming抛出java.lang.NoSuchMethodError：org.apache.spark.sql.SQLContext.internalCreateDataFrame

Question

I'm starting with Structured Spark Streaming with Kafka source and was following a simple tutorial. My Kafka server is OSS kafka. My producer source code is as follows

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;

import java.util.Properties;

public class LogGenerator {
    public static void main(String[] args) throws Exception {
        Properties prop = new Properties();
        prop.load(ClassLoader.getSystemResourceAsStream("kafka-producer.properties"));

        KafkaProducer<String, String> producer = new KafkaProducer<String, String>(prop);

        for (int i=0; i<10000; i++) {
            System.out.printf("%d ", i);
            producer.send(new ProducerRecord<>("my-log-topic", Integer.toString(i), Integer.toString(i)));
        }
    }

}

The producer writes just (0,0) through (999,999)

The structured Streaming code to read from this topic is as follows

mport org.apache.spark.sql.SparkSession

object DimaStreamer {

  //initialize configs

  val spark: SparkSession = SparkSession.builder().master("local").appName("StreamingData").getOrCreate()

  def main(args: Array[String]): Unit = {
    val dfRefundStream = spark.readStream.format("kafka")
      .option("kafka.bootstrap.servers", "0.0.0.0:9091,0.0.0.0:9092")
      .option("subscribe", "my-log-topic")

      .load()

    import org.apache.spark.sql.functions._
    dfRefundStream.printSchema()
    dfRefundStream.select(col("value")).writeStream
      .format("console")
        .queryName("inittest")
      .start()
      .awaitTermination()

  }
}

Its a maven project. The job is executed as follows with the --jars option used for passing the jars with comma separation.

spark-submit --class com.apple.arcadia.solr.batch.DimaStreamer --jars $JARSPATH target/mainproject-1.0-SNAPSHOT.jar

The job throws the following exception

19/06/13 15:10:05 INFO internals.ConsumerCoordinator: Setting newly assigned partitions [my-log-topic-1, my-log-topic-0] for group spark-kafka-source-0ce55060-09ad-430a-9916-e0063d8103fe--48657453-driver-0
19/06/13 15:10:06 INFO kafka010.KafkaSource: Initial offsets: {"my-log-topic":{"1":9878,"0":10122}}
19/06/13 15:10:06 INFO streaming.StreamExecution: Committed offsets for batch 0. Metadata OffsetSeqMetadata(0,1560463806021,Map(spark.sql.shuffle.partitions -> 200))
19/06/13 15:10:06 INFO kafka010.KafkaSource: GetBatch called with start = None, end = {"my-log-topic":{"1":9878,"0":10122}}
19/06/13 15:10:06 INFO kafka010.KafkaSource: Partitions added: Map()
19/06/13 15:10:06 INFO kafka010.KafkaSource: GetBatch generating RDD of offset range: KafkaSourceRDDOffsetRange(my-log-topic-0,10122,10122,None), KafkaSourceRDDOffsetRange(my-log-topic-1,9878,9878,None)
19/06/13 15:10:06 ERROR streaming.StreamExecution: Query inittest [id = 305e10aa-a446-4f42-a4e9-8d2372250fa8, runId = 2218049f-08a4-40bf-9b46-b7e898321b85] terminated with error
java.lang.NoSuchMethodError: org.apache.spark.sql.SQLContext.internalCreateDataFrame(Lorg/apache/spark/rdd/RDD;Lorg/apache/spark/sql/types/StructType;Z)Lorg/apache/spark/sql/Dataset;
    at org.apache.spark.sql.kafka010.KafkaSource.getBatch(KafkaSource.scala:301)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2$$anonfun$apply$7.apply(StreamExecution.scala:614)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2$$anonfun$apply$7.apply(StreamExecution.scala:610)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.Iterator$class.foreach(Iterator.scala:893)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
    at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
    at org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
    at org.apache.spark.sql.execution.streaming.StreamProgress.flatMap(StreamProgress.scala:25)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2.apply(StreamExecution.scala:610)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2.apply(StreamExecution.scala:610)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch(StreamExecution.scala:609)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(StreamExecution.scala:306)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1.apply$mcZ$sp(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:290)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:206)
Exception in thread "stream execution thread for inittest [id = 305e10aa-a446-4f42-a4e9-8d2372250fa8, runId = 2218049f-08a4-40bf-9b46-b7e898321b85]" java.lang.NoSuchMethodError: org.apache.spark.sql.SQLContext.internalCreateDataFrame(Lorg/apache/spark/rdd/RDD;Lorg/apache/spark/sql/types/StructType;Z)Lorg/apache/spark/sql/Dataset;
    at org.apache.spark.sql.kafka010.KafkaSource.getBatch(KafkaSource.scala:301)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2$$anonfun$apply$7.apply(StreamExecution.scala:614)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2$$anonfun$apply$7.apply(StreamExecution.scala:610)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.Iterator$class.foreach(Iterator.scala:893)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
    at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
    at org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
    at org.apache.spark.sql.execution.streaming.StreamProgress.flatMap(StreamProgress.scala:25)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2.apply(StreamExecution.scala:610)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2.apply(StreamExecution.scala:610)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch(StreamExecution.scala:609)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(StreamExecution.scala:306)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1.apply$mcZ$sp(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:290)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:206)
Exception in thread "main" org.apache.spark.sql.streaming.StreamingQueryException: org.apache.spark.sql.SQLContext.internalCreateDataFrame(Lorg/apache/spark/rdd/RDD;Lorg/apache/spark/sql/types/StructType;Z)Lorg/apache/spark/sql/Dataset;
=== Streaming Query ===
Identifier: inittest [id = 305e10aa-a446-4f42-a4e9-8d2372250fa8, runId = 2218049f-08a4-40bf-9b46-b7e898321b85]
Current Committed Offsets: {}
Current Available Offsets: {KafkaSource[Subscribe[my-log-topic]]: {"my-log-topic":{"1":9878,"0":10122}}}

Current State: ACTIVE
Thread State: RUNNABLE

Logical Plan:
Project [value#1]
+- StreamingExecutionRelation KafkaSource[Subscribe[my-log-topic]], [key#0, value#1, topic#2, partition#3, offset#4L, timestamp#5, timestampType#6]

    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:343)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:206)
Caused by: java.lang.NoSuchMethodError: org.apache.spark.sql.SQLContext.internalCreateDataFrame(Lorg/apache/spark/rdd/RDD;Lorg/apache/spark/sql/types/StructType;Z)Lorg/apache/spark/sql/Dataset;
    at org.apache.spark.sql.kafka010.KafkaSource.getBatch(KafkaSource.scala:301)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2$$anonfun$apply$7.apply(StreamExecution.scala:614)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2$$anonfun$apply$7.apply(StreamExecution.scala:610)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.Iterator$class.foreach(Iterator.scala:893)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
    at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
    at org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
    at org.apache.spark.sql.execution.streaming.StreamProgress.flatMap(StreamProgress.scala:25)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2.apply(StreamExecution.scala:610)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch$2.apply(StreamExecution.scala:610)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch(StreamExecution.scala:609)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(StreamExecution.scala:306)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$apply$mcZ$sp$1.apply(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1.apply$mcZ$sp(StreamExecution.scala:294)
    at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:290)
    ... 1 more

Based on the exception, it seems like kafka010.KafkaSource class seems to be missing a method with signature SQLContext.internalCreateDataFrame(rdd, schema)

Upon checking the source code here[ https://github.com/apache/spark/blob/master/external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaSource.scala]

I see the method exists. Has anyone seen such an issue and resolved it? If yes, could you please help understand what the issue was

Finally, the details are the POM are

 <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.11</artifactId>
      <version>2.3.1</version>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-core_2.11</artifactId>
      <version>2.3.1</version>
      <classifier>tests</classifier>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-sql_2.11</artifactId>
      <version>2.3.1</version>
    </dependency>
      <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming-kafka-0-10 -->
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
      <version>2.3.1</version>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-sql-kafka-0-10_2.11</artifactId>
      <version>2.3.1</version>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-sql_2.11</artifactId>
      <version>2.3.1</version>
    </dependency>

Answer 1

I was able to run this as I noticed that the spark version where I'm running spark-submit was 2.2 and the libraries were all (as you can see) are 2.3.1. I changed spark-version and was able to successfully run it.