Runtimes and environments

 The Spark open source ecosystem includes multiple versions of the Spark runtime, which determines the version of Apache Spark, Delta Lake, Python, and other core software components that are installed. Additionally, within a runtime you can install and use a wide selection of code libraries for common (and sometimes very specialized) tasks. Since a great deal of Spark processing is performed using PySpark, the huge range of Python libraries ensures that whatever the task you need to perform, there's probably a library to help.

In some cases, organizations may need to define multiple environments to support a diverse range of data processing tasks. Each environment defines a specific runtime version as well as the libraries that must be installed to perform specific operations. Data engineers and scientists can then select which environment they want to use with a Spark pool for a particular task.


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