Expressive types for Spark.
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Latest commit ce710f2 Jan 20, 2017 @adelbertc committed on GitHub Merge pull request #94 from studiodev/patch-1
Fix typo in TypedEncoder documentation


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Frameless is a proof-of-concept library for working with Spark using more expressive types. It consists of the following modules:

  • dataset for more strongly typed Datasets (supports Spark 2.0.x)
  • cats for using Spark with cats (supports Cats 0.7.x)

The Frameless project and contributors support the Typelevel Code of Conduct and want all its associated channels (e.g. GitHub, Gitter) to be a safe and friendly environment for contributing and learning.



Benefits of using TypedDataset compared to vanilla Dataset:

  • Typesafe columns referencing and expressions
  • Customizable, typesafe encoders
  • Typesafe casting and projections
  • Enhanced type signature for some built-in functions

Quick Start

Frameless is compiled against Scala 2.11.x.

Note that while Frameless is still getting off the ground, it is very possible that breaking changes will be made for at least the next few versions.

To use frameless add the following dependencies as needed:

resolvers += Resolver.sonatypeRepo("releases")

val framelessVersion = "0.2.0"

libraryDependencies ++= List(
  "io.github.adelbertc" %% "frameless-cats"      % framelessVersion,
  "io.github.adelbertc" %% "frameless-dataset"   % framelessVersion


We require at least one sign-off (thumbs-up, +1, or similar) to merge pull requests. The current maintainers (people who can merge pull requests) are:


Code is provided under the Apache 2.0 license available at, as well as in the LICENSE file. This is the same license used as Spark.