Tutorial: Installation


This library requires Spark 2.0+ (not tested for earlier version). The library is tested with Scala 2.11 & 2.12. If you want to use another version, feel free to contact us.

Including spark-fits in your project

You can link spark-fits to your project (either spark-shell or spark-submit) by specifying the coordinates:

# Scala 2.11
toto:~$ spark-submit --packages "com.github.astrolabsoftware:spark-fits_2.11:1.0.0" <...>

# Scala 2.12
toto:~$ spark-submit --packages "com.github.astrolabsoftware:spark-fits_2.12:1.0.0" <...>

It might not contain the latest features though (see Building from source). You can check the latest available version at the root of the project (see the maven central badge)

Building from source

If you want to contribute to the project, or have access to the latest features, you can fork and clone the project, and build it from source. This library is easily built with SBT (see the build.sbt script provided). To build a JAR file simply run

toto:~$ sbt ++${SCALA_VERSION} package

from the project root. The build configuration includes support for Scala 2.11. In addition you can build the doc using SBT:

toto:~$ sbt ++${SCALA_VERSION} doc
toto:~$ open target/scala_${SCALA_VERSION}/api/index.html

Running the test suite

To launch the test suite, just execute:

toto:~$ sbt ++${SCALA_VERSION} coverage test coverageReport

We also provide a script (test.sh) that you can execute. You should get the result on the screen, plus details of the coverage at target/scala_${SCALA_VERSION}/scoverage-report/index.html.

Using with spark-shell, pyspark or jupyter notebook

Follow the dedicated tutorial!

Batch mode and provided examples

Follow the dedicated tutorial!

We also include examples and runners (run_*.sh) in the root folder of the repo. You might have to modify those scripts with your environment.