Here, we're trying to use the Python UDF inside the query.
- taking the table as function input
- converting the table into dataframe
- performing modification
- converting the dataframe into table
- returning the table
How can we create spark context inside UDF in the query
CREATE FUNCTION fun1(input_table TABLE) RETURNS TABLE
LANGUAGE PYTHON
AS $$
import pandas as pd
df = spark.sql(f"SELECT * FROM {input_table}")
def fun(df):
# Convert table to DataFrame
df.write.saveAsTable("my_table")
return my_table
return fun(input_table)
$$;