Ok so I am wondering. Calling this outside of the driver
appName = config['common']['appName'] * spark_session = s.spark_session(appName)* def spark_session(appName): return SparkSession.builder \ .appName(appName) \ .enableHiveSupport() \ .getOrCreate() It says if sparkSEssion already exists then it will get it. Why is this not happening? Thanks LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* *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. On Mon, 8 Mar 2021 at 21:48, Sean Owen <sro...@gmail.com> wrote: > Yep, you can never use Spark inside Spark. > You could run N jobs in parallel from the driver using Spark, however. > > On Mon, Mar 8, 2021 at 3:14 PM Mich Talebzadeh <mich.talebza...@gmail.com> > wrote: > >> >> In structured streaming with pySpark, I need to do some work on the row >> *foreach(process_row)* >> >> below >> >> >> *def process_row(row):* >> >> ticker = row['ticker'] >> >> price = row['price'] >> >> if ticker == 'IBM': >> >> print(ticker, price) >> >> # read data from BigQuery table for analysis >> >> appName = config['common']['appName'] >> >> * spark_session = s.spark_session(appName)* >> >> dfBatchRead = s.loadTableFromBQ(*spark_session)* >> ,config['MDVariables']['targetDataset'],config['MDVariables']['targetTable']) >> >> >> *class MDStreamingRow:* >> >> def __init__(self, spark_session,spark_context): >> >> self.spark = spark_session >> >> self.sc = spark_context >> >> self.config = config >> >> >> def fetch_data(self): >> >> writeStream. \ >> >> outputMode('append'). \ >> >> option("truncate", "false"). \ >> >> * foreach(process_row). \* >> >> >> The issue I have is that spark-session is created at the driver (see >> below) and in order to load data from BigQuery table, I need to call >> spark_session in method *def process_row) as above* >> >> >> if __name__ == "__main__": >> >> appName = config['common']['appName'] >> >> * spark_session = s.spark_session(appName)* >> >> mdstreaming = MDStreamingRow(spark_session, spark_context) >> >> However, I get this error when it gets to process_row() >> >> >> raise Exception("SparkContext should only be created and accessed on the >> driver.") >> >> Exception: SparkContext should only be created and accessed on the driver. >> >> FYI, the spark_session is defined as >> >> def spark_session(appName): >> return SparkSession.builder \ >> .appName(appName) \ >> .enableHiveSupport() \ >> .getOrCreate() >> >> Do I need to create SparkSessionSingleton etc? >> >> Thanks >> >> LinkedIn * >> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* >> >> >> >> >> >> *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. >> >> >> >