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how to read columns dynamically using pyspark

New Contributor

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 =["csv_column"], ",").alias("array_column"))

df1 ="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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