This is probably pretty  straight forward but somehow is does not look that
way



On Spark Structured Streaming,  "foreachBatch" performs custom write logic
on each micro-batch through a call function. Example,

foreachBatch(sendToSink) expects 2 parameters, first: micro-batch as
DataFrame or Dataset and second: unique id for each batch



In my case I simultaneously read two topics through two separate functions



   1. foreachBatch(sendToSink). \
   2. foreachBatch(sendToControl). \

This is  the code

def sendToSink(df, batchId):
    if(len(df.take(1))) > 0:
        print(f"""From sendToSink, md, batchId is {batchId}, at
{datetime.now()} """)
        #df.show(100,False)
        df. persist()
        # write to BigQuery batch table
        #s.writeTableToBQ(df, "append",
config['MDVariables']['targetDataset'],config['MDVariables']['targetTable'])
        df.unpersist()
        #print(f"""wrote to DB""")
       else:
        print("DataFrame md is empty")

def sendToControl(dfnewtopic, batchId2):
    if(len(dfnewtopic.take(1))) > 0:
        print(f"""From sendToControl, newtopic batchId is {batchId2}""")
        dfnewtopic.show(100,False)
        queue = dfnewtopic.first()[2]
        status = dfnewtopic.first()[3]
        print(f"""testing queue is {queue}, and status is {status}""")
        if((queue == config['MDVariables']['topic']) & (status == 'false')):
          spark_session = s.spark_session(config['common']['appName'])
          active = spark_session.streams.active
          for e in active:
             name = e.name
             if(name == config['MDVariables']['topic']):
                print(f"""\n==> Request terminating streaming process for
topic {name} at {datetime.now()}\n """)
                e.stop()
    else:
        print("DataFrame newtopic is empty")


The problem I have is to share batchID from the first function in the
second function sendToControl(dfnewtopic, batchId2) so I can print it out.


Defining a global did not work.. So it sounds like I am missing something
rudimentary here!


Thanks


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