I have a table called MetaData and what columns are needed in the select are stored in MetaData.columns
I would like to read columns dynamically from MetaData.columns and create a view based on that.
csv_values = "col1, col2, col3, col4"
df = spark.createDataFrame([(csv_values,)], ["csv_column"])
df = df.select(split(df["csv_column"], ",").alias("array_column"))
df1 = spark.read.format("parquet").load("FilePath").select(df["*"])
This code is throwing error like below
Unexpected exception formatting exception. Falling back to standard exception
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