![]() ![]() I had multiple use cases in the past to flatten 100+ Jsons from different data sources. We all had to deal with the use case of flattening Json using Spark in the data engineering world at least once. JSON files are lightweight, text-based, human-readable, and can be edited using a text editor. ![]() Json is the most commonly used file type when designing a data service or data streaming integration pattern for data engineering work.Ī JSON file is a file that stores simple data structures and objects in JavaScript Object Notation (JSON) format, which is a standard data interchange format. Some of them are Parquet, Avro, ORC, CSV, JSON, XML.etc. ![]() There are several file types are available when we look at the use case of ingesting data from different sources. How to Flatten Json Files Dynamically Using Apache PySpark(Python) ![]()
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