ml-registry (homepage)

Enabling continuous delivery and improvement of Spark pipeline models through devops methodology and ML governance

@aamend / (1)

Enabling continuous delivery and improvement of Spark pipeline models through devops methodology and ML governance

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How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages com.aamend.spark:ml-registry:1.1

sbt

In your sbt build file, add:

libraryDependencies += "com.aamend.spark" % "ml-registry" % "1.1"

Maven

In your pom.xml, add: 
<dependencies>
  <!-- list of dependencies -->
  <dependency>
    <groupId>com.aamend.spark</groupId>
    <artifactId>ml-registry</artifactId>
    <version>1.1</version>
  </dependency>
</dependencies>

Releases

Version: 1.1 ( 738952 | zip | jar ) / Date: 2019-10-17 / License: Apache-2.0 / Scala version: 2.11

Version: 1.0 ( c76c44 | zip | jar ) / Date: 2019-10-07 / License: Apache-2.0 / Scala version: 2.11