Frameless

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

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.

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

Versions and dependencies

The compatible versions of Spark and cats are as follows:

Frameless Spark Cats Cats-Effect Scala
0.16.0 3.5.0 / 3.4.0 / 3.3.0 2.x 3.x 2.12 / 2.13
0.15.0 3.4.0 / 3.3.0 / 3.2.2 2.x 3.x 2.12 / 2.13
0.14.1 3.4.0 / 3.3.0 / 3.2.2 2.x 3.x 2.12 / 2.13
0.14.0 3.3.0 / 3.2.2 / 3.1.3 2.x 3.x 2.12 / 2.13
0.13.0 3.3.0 / 3.2.2 / 3.1.3 2.x 3.x 2.12 / 2.13
0.12.0 3.2.1 / 3.1.3 / 3.0.3 2.x 3.x 2.12 / 2.13
0.11.1 3.2.0 / 3.1.2 / 3.0.1 2.x 2.x 2.12 / 2.13
0.11.0* 3.2.0 / 3.1.2 / 3.0.1 2.x 2.x 2.12 / 2.13
0.10.1 3.1.0 2.x 2.x 2.12
0.9.0 3.0.0 1.x 1.x 2.12
0.8.0 2.4.0 1.x 1.x 2.11 / 2.12
0.7.0 2.3.1 1.x 1.x 2.11
0.6.1 2.3.0 1.x 0.8 2.11
0.5.2 2.2.1 1.x 0.8 2.11
0.4.1 2.2.0 1.x 0.8 2.11
0.4.0 2.2.0 1.0.0-IF 0.4 2.11

* 0.11.0 has broken Spark 3.1.2 and 3.0.1 artifacts published.

Starting 0.11 we introduced Spark cross published artifacts:

Artifact names examples:

Versions 0.5.x and 0.6.x have identical features. The first is compatible with Spark 2.2.1 and the second with 2.3.0.

The only dependency of the frameless-dataset module is on shapeless 2.3.2. Therefore, depending on frameless-dataset, has a minimal overhead on your Spark's application jar. Only the frameless-cats module depends on cats and cats-effect, so if you prefer to work just with Datasets and not with RDDs, you may choose not to depend on frameless-cats.

Frameless intentionally does not have a compile dependency on Spark. This essentially allows you to use any version of Frameless with any version of Spark. The aforementioned table simply provides the versions of Spark we officially compile and test Frameless with, but other versions may probably work as well.

Breaking changes in 0.9

Why?

Frameless introduces a new Spark API, called TypedDataset. The benefits of using TypedDataset compared to the standard Spark Dataset API are as follows:

Click here for a detailed comparison of TypedDataset with Spark's Dataset API.

Documentation

Quick Start

Since the 0.9.x release, Frameless is compiled only against Scala 2.12.x.

To use Frameless in your project add the following in your build.sbt file as needed:

val framelessVersion = "<latest version>"

resolvers ++= Seq(
  // for snapshot artifacts only
  "s01-oss-sonatype" at "https://s01.oss.sonatype.org/content/repositories/snapshots"
)

libraryDependencies ++= List(
  "org.typelevel" %% "frameless-dataset" % framelessVersion,
  "org.typelevel" %% "frameless-ml"      % framelessVersion,
  "org.typelevel" %% "frameless-cats"    % framelessVersion
)

An easy way to bootstrap a Frameless sbt project:

g8 imarios/frameless.g8
sbt new imarios/frameless.g8

Typing sbt console inside your project will bring up a shell with Frameless and all its dependencies loaded (including Spark).

Need help?

Feel free to messages us on our discord channel for any issues/questions.

Development

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:

Testing

Frameless contains several property tests. To avoid OutOfMemoryErrors, we tune the default generator sizes. The following environment variables may be set to adjust the size of generated collections in the TypedDataSet suite:

Property Default
FRAMELESSGENMIN_SIZE 0
FRAMELESSGENSIZE_RANGE 20

License

Code is provided under the Apache 2.0 license available at http://opensource.org/licenses/Apache-2.0, as well as in the LICENSE file. This is the same license used as Spark.