Many thanks Muru. That was a great help!
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On Mon, 22 Feb 2021 at 22:46, muru <[email protected]> wrote:
> You should include commons-pool2-2.9.0.jar and remove
> spark-streaming-kafka-0-10_2.12-3.0.1.jar (unnecessary jar).
>
> On Mon, Feb 22, 2021 at 12:42 PM Mich Talebzadeh <
> [email protected]> wrote:
>
>> Hi,
>>
>> Trying to make PySpark with PyCharm work with Structured Streaming
>>
>> spark-3.0.1-bin-hadoop3.2
>> kafka_2.12-1.1.0
>>
>> Basic code
>>
>> from __future__ import print_function
>> from src.config import config, hive_url
>> import sys
>> from sparkutils import sparkstuff as s
>>
>> class MDStreaming:
>> def __init__(self, spark_session,spark_context):
>> self.spark = spark_session
>> self.sc = spark_context
>> self.config = config
>>
>> def startStreaming(self):
>> self.sc.setLogLevel("ERROR")
>> try:
>> kafkaReaderWithHeaders = self.spark \
>> .readStream \
>> .format("kafka") \
>> .option("kafka.bootstrap.servers",
>> config['MDVariables']['bootstrapServers'],) \
>> .option("schema.registry.url",
>> config['MDVariables']['schemaRegistryURL']) \
>> .option("group.id", config['common']['appName']) \
>> .option("zookeeper.connection.timeout.ms",
>> config['MDVariables']['zookeeperConnectionTimeoutMs']) \
>> .option("rebalance.backoff.ms",
>> config['MDVariables']['rebalanceBackoffMS']) \
>> .option("zookeeper.session.timeout.ms",
>> config['MDVariables']['zookeeperSessionTimeOutMs']) \
>> .option("auto.commit.interval.ms",
>> config['MDVariables']['autoCommitIntervalMS']) \
>> .option("subscribe", config['MDVariables']['topic']) \
>> .option("failOnDataLoss", "false") \
>> .option("includeHeaders", "true") \
>> .option("startingOffsets", "earliest") \
>> .load()
>> except Exception as e:
>> print(f"""{e}, quitting""")
>> sys.exit(1)
>>
>> kafkaReaderWithHeaders.selectExpr("CAST(key AS STRING)",
>> "CAST(value AS STRING)", "headers") \
>> .writeStream \
>> .format("console") \
>> .option("truncate","false") \
>> .start() \
>> .awaitTermination()
>> kafkaReaderWithHeaders.printSchema()
>>
>> if __name__ == "__main__":
>> appName = config['common']['appName']
>> spark_session = s.spark_session(appName)
>> spark_context = s.sparkcontext()
>> mdstreaming = MDStreaming(spark_session, spark_context)
>> mdstreaming.startStreaming()
>>
>> I have used the following jars in $SYBASE_HOME/jars
>>
>> spark-sql-kafka-0-10_2.12-3.0.1.jar
>> kafka-clients-2.7.0.jar
>> spark-streaming-kafka-0-10_2.12-3.0.1.jar
>> spark-token-provider-kafka-0-10_2.12-3.0.1.jar
>>
>> and also in $SPARK_HOME/conf/spark-defaults.conf
>>
>> spark.driver.extraClassPath $SPARK_HOME/jars/*.jar
>> spark.executor.extraClassPath $SPARK_HOME/jars/*.jar
>>
>>
>> The error is this:
>>
>> 2021-02-22 16:40:38,886 ERROR executor.Executor: Exception in task 3.0 in
>> stage 0.0 (TID 3)
>> *java.lang.NoClassDefFoundError: Could not initialize class
>> org.apache.spark.sql.kafka010.consumer.KafkaDataConsumer$*
>> at
>> org.apache.spark.sql.kafka010.KafkaBatchPartitionReader.<init>(KafkaBatchPartitionReader.scala:52)
>> at
>> org.apache.spark.sql.kafka010.KafkaBatchReaderFactory$.createReader(KafkaBatchPartitionReader.scala:40)
>> at
>> org.apache.spark.sql.execution.datasources.v2.DataSourceRDD.compute(DataSourceRDD.scala:60)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
>> at org.apache.spark.scheduler.Task.run(Task.scala:127)
>> at
>> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
>> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>> at java.lang.Thread.run(Thread.java:748)
>>
>> pyspark.sql.utils.StreamingQueryException: Writing job aborted.
>> === Streaming Query ===
>> Identifier: [id = 0706dcd1-01de-4d7f-a362-81257b45e38c, runId =
>> d61d9807-6f6c-4de1-a60f-8ae31c8a3c36]
>> Current Committed Offsets: {}
>> Current Available Offsets: {KafkaV2[Subscribe[md]]:
>> {"md":{"8":1905351,"2":1907338,"5":1905175,"4":1904978,"7":1907880,"1":1903797,"3":1906072,"6":1904936,"0":1903896}}}
>>
>> Current State: ACTIVE
>> Thread State: RUNNABLE
>>
>> Logical Plan:
>> WriteToMicroBatchDataSource ConsoleWriter[numRows=20, truncate=false]
>> +- Project [cast(key#8 as string) AS key#24, cast(value#9 as string) AS
>> value#25, headers#15]
>> +- StreamingDataSourceV2Relation [key#8, value#9, topic#10,
>> partition#11, offset#12L, timestamp#13, timestampType#14, headers#15],
>> org.apache.spark.sql.kafka010.KafkaSourceProvider$KafkaScan@1cf1e26d,
>> KafkaV2[Subscribe[md]]
>>
>> Process finished with exit code 1
>>
>> The thing is that the class is in the jar file below in $SPARK_HOME/jars
>>
>>
>> find $SPARK_HOME/jars/ -name "*.jar" | xargs grep
>> org.apache.spark.sql.kafka010.consumer.KafkaDataConsumer
>>
>>
>> Binary file jars/spark-sql-kafka-0-10_2.12-3.0.1.jar matches
>>
>> Appreciate any feedback.
>>
>>
>> Thanks
>>
>>
>> Mich
>>
>>
>>
>>
>>
>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>> any loss, damage or destruction of data or any other property which may
>> arise from relying on this email's technical content is explicitly
>> disclaimed. The author will in no case be liable for any monetary damages
>> arising from such loss, damage or destruction.
>>
>>
>>
>>
>>
