A 3-day bug hunt on a 3-person team costs up to €7,200 in lost engineering time. This workshop teaches you to prevent that — unit tests, data tests, and integration tests for PySpark and Databricks Lakeflow, including Spark Declarative Pipelines.
Spark SQL - even if the SQL suffix makes automatically think about RDBMS - works well with other data sources, as even plain CSVs or JSON files. This relation would be difficult to achieve without the concept of schema.
Spark SQL schema is very flexible. It supports global data types, as booleans, integers, strings, but it also supports custom data types called User Defined Type (UDT).