Distributed DataFrame: Productivity = Power x Simplicity For Big Data Scientists & Engineers
DDF aims to make Big Data easy yet powerful, by bringing together the best ideas from R Data Science, RDBMS/SQL, and Big Data distributed processing.
It exposes high-level abstractions like RDBMS tables, SQL queries, data cleansing and transformations, machine-learning algorithms, even collaboration and authentication, etc., while hiding all the complexities of parallel distributed processing and data handling.
DDF is a general abstraction that can be implemented on multiple execution and data engines. We are providing a native implementation on Apache Spark, as it is today the most expressive in its DAG parallelization and also most powerful in its in-memory distributed dataset abstraction (RDD). With this release, DDF provides native Spark support for R, Python, Java, Scala.
An aim of the DDF project is to shine a focus of Big Data conversations on top-down, user-focussed simplicity and power, where "users" include business analysts, data scientists, and high-level Big Data engineers.
| Directory | Description |
|---|---|
| bin | useful helper scripts |
| exe | DDF execution/launch scripts and executables |
| conf | DDF configuration files |
| R | DDF in R |
| python | DDF in python |
| core | DDF core API |
| spark | DDF Spark implementation |
| examples | DDF example API-user code |
| project | Scala build config files |
First clone or fork a copy of DDF, e.g.:
$ git clone https://github.com/ddf-project/DDF
Now set up the neccessary environment variables (MAVEN_OPTS, JAVA_TOOL_OPTIONS) for the build.
$ cd DDF
$ bin/set-env.sh
If you don't want to set up the environment variables every time, please add the commands into ~/.bashrc or ~/.bash_profile.
If you don't have sbt and want to install, run the following command
$ bin/get-sbt.sh
This command will install a local sbt under bin/sbt
(Optional) The following regenerates Eclipse .project and .classpath files:
$ bin/make-eclipse-projects.sh
$ mvn clean install -DskipTests
Or if you want to just build separate modules, you can go into module directories and build, for example,
$ (cd core ; mvn clean install -DskipTests)
$ (cd spark ; mvn clean install -DskipTests)
Or if you are more familar with the sbt tool,
sbt (bin/sbt) clean compile publishLocal
mvn test
Or if you want to run test for individual modules,
$ (cd core ; mvn test)
$ (cd spark ; mvn test)
Or if you are more familar with the sbt tool,
sbt (bin/sbt) test