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