Spark Structured Streaming with PySpark throwing error in execution

[Mich Talebzadeh]

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





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