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Introduction to Apache Spark™ with Frameless
Brian M. Clapper<br/><i>[email protected], @brianclapper</i>
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This talk has nothing about category theory. It doesn't talk about type-level programming or type classes (even though Frameless relies heavily on both).

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Instead, this talk:

::: incremental

  • ...is a gentle introduction to Apache Spark.
  • ...compares and contrasts the standard Spark DataFrames and Datasets APIs with the Typelevel Frameless API.
  • It's oriented toward learning how to use these APIs.
  • Hopefully, at the end:
    • you'll walk away with some understanding of Spark (if you don't already know it)
    • and you'll have some idea of how Frameless compares to the native Spark APIs.

:::

This is the last slide {class="slide-title" data-background-image="images/normal-bg.png"}

This talk will be largely demo-oriented, using Databricks notebooks.

The source to these slides and to all the notebooks are in GitHub repo
github.com/bmc/spark-frameless-talk-2018

The README in that repo explains how to run the notebooks yourself, if you want to do so.