Spark (page 1)
Process data at scale with Apache Spark and PySpark. Build pipelines to batch process or stream data in real-time.
Join and Aggregate PySpark DataFrames
Perform SQL-like joins and aggregations on your PySpark DataFrames.
Working with PySpark RDDs
Working with Spark's original data structure API: Resilient Distributed Datasets.
Structured Streaming in PySpark
Become familiar with building a structured stream in PySpark using the Databricks interface.
Cleaning PySpark DataFrames
Easy DataFrame cleaning techniques ranging from dropping rows to selecting important data.
Transforming PySpark DataFrames
Apply transformations to PySpark DataFrames such as creating new columns, filtering rows, or modifying string & number values.
Learning Apache Spark with PySpark & Databricks
Get started with Apache Spark in part 1 of our series, where we leverage Databricks and PySpark.