问题
I m running the kafka producer and consumer code for testing purpose in cdh 5.12. While I m trying to do so I m facing below error while running the consumer code.
dataSet: org.apache.spark.sql.Dataset[(String, String)] = [key: string, value: string]
query: org.apache.spark.sql.streaming.StreamingQuery = org.apache.spark.sql.execution.streaming.StreamingQueryWrapper@109a5573
2018-10-25 10:08:37 ERROR MicroBatchExecution:91 - Query [id = 70bc4f7a-cc41-470d-afd0-d46e5aebf3db, runId = 4d974468-6c6b-47e5-976b-8b9aa98114e2] terminated with error
java.lang.AbstractMethodError
at org.apache.spark.internal.Logging$class.initializeLogIfNecessary(Logging.scala:99)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.initializeLogIfNecessary(KafkaSourceProvider.scala:369)
at org.apache.spark.internal.Logging$class.log(Logging.scala:46)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.log(KafkaSourceProvider.scala:369)
at org.apache.spark.internal.Logging$class.logDebug(Logging.scala:58)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.logDebug(KafkaSourceProvider.scala:369)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$ConfigUpdater.set(KafkaSourceProvider.scala:439)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.kafkaParamsForDriver(KafkaSourceProvider.scala:394)
at org.apache.spark.sql.kafka010.KafkaSourceProvider.createSource(KafkaSourceProvider.scala:90)
at org.apache.spark.sql.execution.datasources.DataSource.createSource(DataSource.scala:277)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1$$anonfun$applyOrElse$1.apply(MicroBatchExecution.scala:80)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1$$anonfun$applyOrElse$1.apply(MicroBatchExecution.scala:77)
at scala.collection.mutable.MapLike$class.getOrElseUpdate(MapLike.scala:194)
at scala.collection.mutable.AbstractMap.getOrElseUpdate(Map.scala:80)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1.applyOrElse(MicroBatchExecution.scala:77)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1.applyOrElse(MicroBatchExecution.scala:75)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.logicalPlan$lzycompute(MicroBatchExecution.scala:75)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.logicalPlan(MicroBatchExecution.scala:61)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:265)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
Exception in thread "stream execution thread for [id = 70bc4f7a-cc41-470d-afd0-d46e5aebf3db, runId = 4d974468-6c6b-47e5-976b-8b9aa98114e2]" java.lang.AbstractMethodError
at org.apache.spark.internal.Logging$class.initializeLogIfNecessary(Logging.scala:99)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.initializeLogIfNecessary(KafkaSourceProvider.scala:369)
at org.apache.spark.internal.Logging$class.log(Logging.scala:46)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.log(KafkaSourceProvider.scala:369)
at org.apache.spark.internal.Logging$class.logDebug(Logging.scala:58)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.logDebug(KafkaSourceProvider.scala:369)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$ConfigUpdater.set(KafkaSourceProvider.scala:439)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.kafkaParamsForDriver(KafkaSourceProvider.scala:394)
at org.apache.spark.sql.kafka010.KafkaSourceProvider.createSource(KafkaSourceProvider.scala:90)
at org.apache.spark.sql.execution.datasources.DataSource.createSource(DataSource.scala:277)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1$$anonfun$applyOrElse$1.apply(MicroBatchExecution.scala:80)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1$$anonfun$applyOrElse$1.apply(MicroBatchExecution.scala:77)
at scala.collection.mutable.MapLike$class.getOrElseUpdate(MapLike.scala:194)
at scala.collection.mutable.AbstractMap.getOrElseUpdate(Map.scala:80)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1.applyOrElse(MicroBatchExecution.scala:77)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1.applyOrElse(MicroBatchExecution.scala:75)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.logicalPlan$lzycompute(MicroBatchExecution.scala:75)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.logicalPlan(MicroBatchExecution.scala:61)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:265)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
org.apache.spark.sql.streaming.StreamingQueryException: Query [id = 70bc4f7a-cc41-470d-afd0-d46e5aebf3db, runId = 4d974468-6c6b-47e5-976b-8b9aa98114e2] terminated with exception: null
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:295)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
Caused by: java.lang.AbstractMethodError
at org.apache.spark.internal.Logging$class.initializeLogIfNecessary(Logging.scala:99)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.initializeLogIfNecessary(KafkaSourceProvider.scala:369)
at org.apache.spark.internal.Logging$class.log(Logging.scala:46)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.log(KafkaSourceProvider.scala:369)
at org.apache.spark.internal.Logging$class.logDebug(Logging.scala:58)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.logDebug(KafkaSourceProvider.scala:369)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$ConfigUpdater.set(KafkaSourceProvider.scala:439)
at org.apache.spark.sql.kafka010.KafkaSourceProvider$.kafkaParamsForDriver(KafkaSourceProvider.scala:394)
at org.apache.spark.sql.kafka010.KafkaSourceProvider.createSource(KafkaSourceProvider.scala:90)
at org.apache.spark.sql.execution.datasources.DataSource.createSource(DataSource.scala:277)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1$$anonfun$applyOrElse$1.apply(MicroBatchExecution.scala:80)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1$$anonfun$applyOrElse$1.apply(MicroBatchExecution.scala:77)
at scala.collection.mutable.MapLike$class.getOrElseUpdate(MapLike.scala:194)
at scala.collection.mutable.AbstractMap.getOrElseUpdate(Map.scala:80)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1.applyOrElse(MicroBatchExecution.scala:77)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$1.applyOrElse(MicroBatchExecution.scala:75)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.logicalPlan$lzycompute(MicroBatchExecution.scala:75)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.logicalPlan(MicroBatchExecution.scala:61)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:265)
Below is the scala code I m running:
import org.apache.kafka.clients.consumer.KafkaConsumer
import org.apache.kafka.clients.producer.{KafkaProducer, ProducerRecord}
val dataFrame = spark.readStream.format("kafka").option("kafka.bootstrap.servers","host:9093,host:9093,host:9093").option("kafka.security.protocol", "SASL_SSL").option("kafka.sasl.kerberos.service.name", "kafka").option("kafka.ssl.truststore.location","/opt/cloudera/security/jks/truststore.jks").option("kafka.ssl.truststore.password", "password").option("subscribe", "SampleTopic").load()
// dataFrame.writeStream.format("console").option("truncate","false").start().awaitTermination()
dataFrame.printSchema()
val dataSet =dataFrame.selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)").as[(String, String)]
val query = dataSet.writeStream.outputMode("append").format("console").start()
query.awaitTermination()
Below is the command I m running to execute above code:
spark2-shell --files /tmp/jaas.conf,/path/to/.keytab --conf spark.executor.extraJavaOptions=-Djava.security.auth.login.config=/tmp/jaas.conf --conf spark.driver.extraJavaOptions=-Djava.security.auth.login.config=/tmp/jaas.conf --packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.2.0 -i /path/to/file.scala
Thanks
回答1:
I got a similar issue and it turns out that the problem was an incompatibility between spark version and the versions of the used packages.
For your case - according to cloudera doc cdh 5.12 comes with Spark 1.6 which in turns requires scala 2.10, while the used package org.apache.spark:spark-sql-kafka-0-10_2.11:2.2.0 is compiled with scala 2.11. You can try to use org.apache.spark:spark-streaming-kafka_2.10:1.6.1 instead.
Credits: https://community.hortonworks.com/articles/197922/spark-23-structured-streaming-integration-with-apa.html
来源：https://stackoverflow.com/questions/52993141/java-lang-abstractmethoderror-org-apache-spark-internal-loggingclass-initializ