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[SPARK-7537][MLLIB] spark.mllib API updates #6280

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[SPARK-7537][MLLIB] spark.mllib API updates #6280

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88c62d0
add DeveloperApi to PMMLExportable
mengxr May 20, 2015
4c40da1
mention the factory method for RankingMetrics for Java users
mengxr May 20, 2015
94afa7a
mark all toPMML methods experimental
mengxr May 20, 2015
1bd2583
organize imports
mengxr May 20, 2015
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2 changes: 2 additions & 0 deletions mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala
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Expand Up @@ -31,6 +31,8 @@ import org.apache.spark.rdd.RDD
* ::Experimental::
* Evaluator for ranking algorithms.
*
* Java users should use [[RankingMetrics$.of]] to create a [[RankingMetrics]] instance.
*
* @param predictionAndLabels an RDD of (predicted ranking, ground truth set) pairs.
*/
@Experimental
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11 changes: 11 additions & 0 deletions mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
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Expand Up @@ -23,13 +23,16 @@ import javax.xml.transform.stream.StreamResult
import org.jpmml.model.JAXBUtil

import org.apache.spark.SparkContext
import org.apache.spark.annotation.{DeveloperApi, Experimental}
import org.apache.spark.mllib.pmml.export.PMMLModelExportFactory

/**
* :: DeveloperApi ::
* Export model to the PMML format
* Predictive Model Markup Language (PMML) is an XML-based file format
* developed by the Data Mining Group (www.dmg.org).
*/
@DeveloperApi
trait PMMLExportable {

/**
Expand All @@ -41,30 +44,38 @@ trait PMMLExportable {
}

/**
* :: Experimental ::
* Export the model to a local file in PMML format
*/
@Experimental
def toPMML(localPath: String): Unit = {
toPMML(new StreamResult(new File(localPath)))
}

/**
* :: Experimental ::
* Export the model to a directory on a distributed file system in PMML format
*/
@Experimental
def toPMML(sc: SparkContext, path: String): Unit = {
val pmml = toPMML()
sc.parallelize(Array(pmml), 1).saveAsTextFile(path)
}

/**
* :: Experimental ::
* Export the model to the OutputStream in PMML format
*/
@Experimental
def toPMML(outputStream: OutputStream): Unit = {
toPMML(new StreamResult(outputStream))
}

/**
* :: Experimental ::
* Export the model to a String in PMML format
*/
@Experimental
def toPMML(): String = {
val writer = new StringWriter
toPMML(new StreamResult(writer))
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