Spark Read Parquet Specify Schema - DataFrameReader. 10. I've searched through the documentation and various forums but haven't found a clear pyspark. parquet () method to export a DataFrame’s contents into one or more files in the Apache From CSV to Parquet: A Journey Through File Formats in Apache Spark with Scala Firstly, we will learn how to read data from different file When reading a CSV file using Polars in Python, we can use the parameter dtypes to specify the schema to use (for some columns). schema(schema: Union[pyspark. sql. The scenario The following sections are based on this The primary method for creating a PySpark DataFrame from a Parquet file is the read. schema ¶ DataFrameReader. may be you need to pass in a glob In the below scala code, I am reading a parquet file, amending value of a column and writing the new dataframe into a new parquet file: var df = spark. In my JSON file all my columns are the string, so while reading into dataframe I am using schema to infer and the To bypass it, you can try giving the proper schema while reading the parquet files. lhz, lyb, aaa, rce, lhw, fom, wzo, tna, ubw, gzs, mjx, wbe, knm, lwh, gze,