Spark SQL data type articles

4-day workshop · In-person or online

What would it take for you to trust your Databricks pipelines in production?

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.

Unit, data & integration tests
Medallion architecture & Lakeflow SDP
Max 10 participants · production-ready templates
See the full curriculum → €7,000 flat fee · cohort of up to 10
Bartosz Konieczny
Bartosz
Konieczny

Schemas

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.

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User Defined Type

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).

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