Parallel implementation of SparkML transformers and estimators.
This library extends SparkML to allow for parallel transformation of input datasets. That is to transform multiple columns in parallel using the same set of transformations one would normally need to apply in sequence.
Clone this repository and run mvn clean test
To build for a custom version of Spark/Scala, run
mvn clean compile \ -Dscala.major.version=<SCALA_MAJOR> \ -Dscala.minor.version=<SCALA_MINOR> \ -Dspark.version=<SPARK_VERSION>
e.g.
mvn clean package \
-Dscala.major.version=2.11 \
-Dscala.minor.version=2.11.8 \
-Dspark.version=2.3.0
Alternatively one can build against a limited number of pre-defined profiles. See the pom for a list of the profiles.
Example build with profiles:
mvn clean package -Pspark_2.3,scala_2.11
mvn clean package -Pspark_2.0,scala_2.10
Here is a handy table of supported build version combinations:
Apache Spark | Scala |
---|---|
2.0.x | 2.10 |
2.0.x | 2.11 |
2.1.x | 2.10 |
2.1.x | 2.11 |
2.2.x | 2.10 |
2.2.x | 2.11 |
2.3.x | 2.11 |
see the license for license information.