无法实例化 Kafka 结构化流 KafkaSourceProvider

Question

I am working on a streaming project where I have a kafka stream of ping statistics like so :

64 bytes from vas.fractalanalytics.com (192.168.30.26): icmp_seq=1 ttl=62 time=0.913 ms
64 bytes from vas.fractalanalytics.com (192.168.30.26): icmp_seq=2 ttl=62 time=0.936 ms
64 bytes from vas.fractalanalytics.com (192.168.30.26): icmp_seq=3 ttl=62 time=0.980 ms
64 bytes from vas.fractalanalytics.com (192.168.30.26): icmp_seq=4 ttl=62 time=0.889 ms

I am trying to read this as a structured stream in pyspark . I start pyspark with the following command :

 pyspark --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.0

Pyspark version is 2.4, python version is 2.7 (tried with 3.6 as well)

And I get an error as soon as I send this piece of code (followed from Structured Streaming + Kafka Integration Guide ):

df = spark.readStream.format("kafka").option("kafka.bootstrap.servers", "172.18.2.21:2181").option("subscribe", "ping-stats").load()

I run into the following error :

py4j.protocol.Py4JJavaError: An error occurred while calling o37.load.
: java.util.ServiceConfigurationError: org.apache.spark.sql.sources.DataSourceRegister: Provider org.apache.spark.sql.kafka010.KafkaSourceProvider could not be instantiated
        at java.util.ServiceLoader.fail(ServiceLoader.java:232)
        at java.util.ServiceLoader.access$100(ServiceLoader.java:185)
        at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:384)
        at java.util.ServiceLoader$LazyIterator.next(ServiceLoader.java:404)
        at java.util.ServiceLoader$1.next(ServiceLoader.java:480)
        at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:43)
        at scala.collection.Iterator$class.foreach(Iterator.scala:891)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
        at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
        at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
        at scala.collection.TraversableLike$class.filterImpl(TraversableLike.scala:247)
        at scala.collection.TraversableLike$class.filter(TraversableLike.scala:259)
        at scala.collection.AbstractTraversable.filter(Traversable.scala:104)
        at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:630)
        at org.apache.spark.sql.streaming.DataStreamReader.load(DataStreamReader.scala:161)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:498)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
        at py4j.Gateway.invoke(Gateway.java:282)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:238)
        at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoSuchMethodError: org.apache.spark.internal.Logging.$init$(Lorg/apache/spark/internal/Logging;)V
        at org.apache.spark.sql.kafka010.KafkaSourceProvider.<init>(KafkaSourceProvider.scala:44)
        at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
        at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
        at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
        at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
        at java.lang.Class.newInstance(Class.java:442)
        at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:380)
        ... 23 more

Can someone help me out with this?

Answer 1

I managed to solve this by ensuring that the spark-sql-kafka package's version matches the spark version.

In my case, I am now using --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.1 for my spark version 2.4.1 , thereafter the .format("kafka") part of the code can be resolved.

Also, v2.12 of the package (ie, org.apache.spark:spark-sql-kafka-0-10_2.12:2.4.1 ) does not seem stable at the time of writing, and using it will also cause the above error.

*EDIT: v2.12 spark-sql-kafka packages seem to only work with Spark built with Scala v2.12. Hence, for Spark v2.X versions (pre-built with Scala v2.11 by default), there's a need to instead use Spark binaries built with Scala v2.12 (eg spark-2.4.1-bin-without-hadoop-scala-2.12.tgz ) if you really want to use spark-sql-kafka v2.12 package. For Spark v3.X, they are pre-built with Scala v2.12 by default, hence you'll only see/use v2.12 of the package.

Answer 2

Im runinning Spark 2.4.4 and same issue. If I use org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.4 I am having issues to read values from Kafka. It seems that the issue is on the JSON parser since it does not match Spark Version.

Any help would be appreciated!

Answer 3

将 Spark 版本 2.3.2 与 Scala 版本 2.11.11 和依赖项 org.apache.spark:sl-kafka-0-10_2.10:2.0.2 一起使用时问题已解决

#spark-shell  -i Process.scala --master local[2]  --packages org.apache.spark:sl-kafka-0-10_2.10:2.0.2 ...