SPRKPY1080

pyspark.SparkContext

Message: The value of SparkContext is replaced with 'session' variable.

Category: Warning

Description

Spark context is stored into a variable called session that creates a Snowpark Session.

Scenario

Input

This snippet describes a SparkContext

# Input Code
from pyspark import SparkContext
from pyspark.sql import SparkSession

def example1():

    sc = SparkContext("local[*]", "TestApp")

    sc.setLogLevel("ALL")
    sc.setLogLevel("DEBUG")

Output

In this output code SMA has replaced the PySpark.SparkContext by a SparkSession , Note that SMA also add a template to replace the connection in the "connection.json" file and then load this configuration on the connection_parameter variable.

# Output Code
import logging
import sys
import json
from snowflake.snowpark import Session
from snowflake.snowpark import Session

def example1():
    jsonFile = open("connection.json")
    connection_parameter = json.load(jsonFile)
    jsonFile.close()
    #EWI: SPRKPY1080 => The value of SparkContext is replaced with 'session' variable.
    sc = Session.builder.configs(connection_parameter).getOrCreate()
    sc.update_query_tag({"origin":"sf_sit","name":"sma","version":{"major":0,"minor":0,"patch":0},"attributes":{"language":"Python"}})
    logging.basicConfig(stream = sys.stdout, level = logging.NOTSET)
    logging.basicConfig(stream = sys.stdout, level = logging.DEBUG)

Recommended fix

The configuration file "connection.json" must be updated with the required connection information:

{
  "user": "my_user",
  "password": "my_password",
  "account": "my_account",
  "role": "my_role",
  "warehouse": "my_warehouse",
  "database": "my_database",
  "schema": "my_schema"
}

Additional recommendations

• For more support, you can email us at [e-mail] or post an issue in the SMA.