
org.apache.spark.examples.ml.RFormulaExample.scala Maven / Gradle / Ivy
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SnappyData distributed data store and execution engine
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// scalastyle:off println
package org.apache.spark.examples.ml
// $example on$
import org.apache.spark.ml.feature.RFormula
// $example off$
import org.apache.spark.sql.SQLContext
import org.apache.spark.{SparkConf, SparkContext}
object RFormulaExample {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("RFormulaExample")
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
// $example on$
val dataset = sqlContext.createDataFrame(Seq(
(7, "US", 18, 1.0),
(8, "CA", 12, 0.0),
(9, "NZ", 15, 0.0)
)).toDF("id", "country", "hour", "clicked")
val formula = new RFormula()
.setFormula("clicked ~ country + hour")
.setFeaturesCol("features")
.setLabelCol("label")
val output = formula.fit(dataset).transform(dataset)
output.select("features", "label").show()
// $example off$
sc.stop()
}
}
// scalastyle:on println
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