com.lucidworks.spark.example.ml

MLPipelineScala

class MLPipelineScala extends RDDProcessor

An example of building a spark.ml classification model to predict the newsgroup of articles from the 20 newsgroups data (see http://qwone.com/~jason/20Newsgroups/) hosted in a Solr collection.

Prerequisites

You must run mvn -DskipTests package in the spark-solr project, and you must download a Spark 1.6.1 binary distribution and point the environment variable $SPARK_HOME to the unpacked distribution directory.

Follow the instructions in the NewsgroupsIndexer example's scaladoc to populate a Solr collection with articles from the above-linked 20 newsgroup data.

Example invocation 

$SPARK_HOME/bin/spark-submit --master 'local[2]' --class com.lucidworks.spark.SparkApp \
target/spark-solr-2.0.0-SNAPSHOT-shaded.jar ml-pipeline-scala

To see a description of all available options, run the following:

$SPARK_HOME/bin/spark-submit --class com.lucidworks.spark.SparkApp \
target/spark-solr-2.0.0-SNAPSHOT-shaded.jar ml-pipeline-scala --help
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  1. new MLPipelineScala()

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  11. final def getClass(): Class[_]

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  12. def getName(): String

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    MLPipelineScala → RDDProcessor

  13. def getOptions(): Array[Option]

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  19. def run(conf: SparkConf, cli: CommandLine): Int

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