Structured Spark Streaming throwing java.lang.NoSuchMethodError: org.apache.spark.sql.SQLContext.internalCreateDataFrame - apache-spark

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.