I use spark 2.4.0 using python. and read data from the kafka_2.11-2.0.0 (binary not source). I m using spark-submit --jars sspark-streaming-kafka-0-8-assembly_2.11-2.4.0.jar script.py an error message appears in the error report, if any one can help , thanks :)
19/03/25 13:48:53 ERROR Utils: Uncaught exception in thread stdout writer for python
java.lang.NoSuchMethodError: net.jpountz.lz4.LZ4BlockInputStream.<init>(Ljava/io/InputStream;Z)V
at org.apache.spark.io.LZ4CompressionCodec.compressedInputStream(CompressionCodec.scala:122)
at org.apache.spark.serializer.SerializerManager.wrapForCompression(SerializerManager.scala:163)
at org.apache.spark.serializer.SerializerManager.wrapStream(SerializerManager.scala:124)
at org.apache.spark.shuffle.BlockStoreShuffleReader$$anonfun$3.apply(BlockStoreShuffleReader.scala:50)
at org.apache.spark.shuffle.BlockStoreShuffleReader$$anonfun$3.apply(BlockStoreShuffleReader.scala:50)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:453)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:64)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:30)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:557)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:345)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:194)
Exception in thread "stdout writer for python" java.lang.NoSuchMethodError: net.jpountz.lz4.LZ4BlockInputStream.<init>(Ljava/io/InputStream;Z)V
at org.apache.spark.io.LZ4CompressionCodec.compressedInputStream(CompressionCodec.scala:122)
at org.apache.spark.serializer.SerializerManager.wrapForCompression(SerializerManager.scala:163)
at org.apache.spark.serializer.SerializerManager.wrapStream(SerializerManager.scala:124)
at org.apache.spark.shuffle.BlockStoreShuffleReader$$anonfun$3.apply(BlockStoreShuffleReader.scala:50)
at org.apache.spark.shuffle.BlockStoreShuffleReader$$anonfun$3.apply(BlockStoreShuffleReader.scala:50)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:453)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:64)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:30)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.api.python.PythonRunner$$anon$2.writeIteratorToStream(PythonRunner.scala:557)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:345)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:194)
The pom.xml of the jar file : spark-streaming-kafka-0-8-assembly_2.11-2.4.0.jar :
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-parent_2.11</artifactId>
<version>2.4.0</version>
<relativePath>../../pom.xml</relativePath>
</parent>
<artifactId>spark-streaming-kafka-0-8-assembly_2.11</artifactId>
<packaging>jar</packaging>
<name>Spark Project External Kafka Assembly</name>
<url>http://spark.apache.org/</url>
<properties>
<sbt.project.name>streaming-kafka-0-8-assembly</sbt.project.name>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-8_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<scope>provided</scope>
</dependency>
<!--
Demote already included in the Spark assembly.
-->
<dependency>
<groupId>commons-codec</groupId>
<artifactId>commons-codec</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>commons-lang</groupId>
<artifactId>commons-lang</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>com.google.protobuf</groupId>
<artifactId>protobuf-java</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.lz4</groupId>
<artifactId>lz4-java</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.avro</groupId>
<artifactId>avro-mapred</artifactId>
<classifier>${avro.mapred.classifier}</classifier>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.curator</groupId>
<artifactId>curator-recipes</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.zookeeper</groupId>
<artifactId>zookeeper</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.xerial.snappy</groupId>
<artifactId>snappy-java</artifactId>
<scope>provided</scope>
</dependency>
<dependency>
</dependencies>
<build>
<outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
<testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<configuration>
<shadedArtifactAttached>false</shadedArtifactAttached>
<artifactSet>
<includes>
<include>*:*</include>
</includes>
</artifactSet>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
<resource>reference.conf</resource>
</transformer>
<transformer implementation="org.apache.maven.plugins.shade.resource.DontIncludeResourceTransformer">
<resource>log4j.properties</resource>
</transformer>
<transformer implementation="org.apache.maven.plugins.shade.resource.ApacheLicenseResourceTransformer"/>
<transformer implementation="org.apache.maven.plugins.shade.resource.ApacheNoticeResourceTransformer"/>
</transformers>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
the spark-kafka WorldCount script proposed in the examples of spark streaming
from __future__ import print_function
import sys
# from pyspark.mllib.classification import SVMModel, LogisticRegressionModel
from pyspark import SparkContext
from pyspark import SparkConf
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils
if __name__ == "__main__":
if len(sys.argv) != 3:
print("Usage: kafka_wordcount.py <zk> <topic>", file=sys.stderr)
exit(-1)
sc = SparkContext(appName="PythonStreamingKafkaWordCount")
ssc = StreamingContext(sc, 1)
conf = SparkConf()
conf.set("spark.executor.memory", "12G")
conf.set("spark.executor.heartbeatInterval", "10s")
# conf.set("spark.io.compression.codec", "snappy")
zkQuorum, topic = sys.argv[1:]
kvs = KafkaUtils.createStream(ssc, zkQuorum, "consumer-group_id", {topic: 1})
lines = kvs.map(lambda x: x[1])
lines.pprint()
mots = lines.flatMap(lambda line: line.split(" "))
nbr = mots.map(lambda word: (word, 1))
nbr.pprint()
counts = nbr.reduceByKey(lambda x, y: x + y)
counts.pprint()
ssc.start()
print("\n\n\n spark-streaming commance !! \n\n\n")
ssc.awaitTermination()
print("Usage: kafka_wordcount.py <zk> <topic>", file=sys.stderr)statement could comment it out and try to execute the job again?