Convert CSV to Parquet using pySpark in Azure Synapse Analytics

If you're working with CSV files and need to convert them to Parquet format using pySpark in Azure Synapse Analytics, this video tutorial is for you. Through a step-by-step guide, you'll learn how to use pySpark to efficiently convert your CSV files to Parquet format.

Parquet format offers a range of benefits over CSV, including improved query performance, storage efficiency, and support for complex data types. With the help of pySpark in Azure Synapse Analytics, you can leverage the power of Parquet format to streamline your data processing and analysis workflows.

The tutorial dives into the nitty-gritty of the conversion process, covering topics such as loading CSV files into a PySpark dataframe, converting the data to Parquet format, and saving the output file. As you follow along, you'll gain a deeper understanding of how to work with data in Azure Synapse Analytics using pySpark.

So whether you're an experienced data analyst or just starting out, this tutorial offers a valuable resource for those looking to convert CSV files to Parquet format using PySpark in Azure Synapse Analytics.

The link to the video tutorial can be found here: https://www.youtube.com/watch?v=k280CpPKJgc