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From yinxusen <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-13017][Docs] Replace example code in ml...
Date Sun, 21 Feb 2016 02:51:05 GMT
Github user yinxusen commented on a diff in the pull request:

    https://github.com/apache/spark/pull/11142#discussion_r53560836
  
    --- Diff: examples/src/main/scala/org/apache/spark/examples/mllib/ElementwiseProductExample.scala
---
    @@ -0,0 +1,50 @@
    +/*
    + * 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.mllib
    +
    +import org.apache.spark.SparkConf
    +// $example on$
    +import org.apache.spark.SparkContext
    +import org.apache.spark.mllib.feature.ElementwiseProduct
    +import org.apache.spark.mllib.linalg.Vectors
    +// $example off$
    +
    +object ElementwiseProductExample {
    +
    +  def main(args: Array[String]) {
    +
    +    val conf = new SparkConf().setAppName("ElementwiseProductExample")
    +    val sc = new SparkContext(conf)
    +
    +    // $example on$
    +    // Create some vector data; also works for sparse vectors
    +    val data = sc.parallelize(Array(Vectors.dense(1.0, 2.0, 3.0), Vectors.dense(4.0,
5.0, 6.0)))
    +
    +    val transformingVector = Vectors.dense(0.0, 1.0, 2.0)
    +    val transformer = new ElementwiseProduct(transformingVector)
    +
    +    // Batch transform and per-row transform give the same results:
    +    val transformedData = transformer.transform(data)
    +    val transformedData2 = data.map(x => transformer.transform(x))
    +    // $example off$
    +
    --- End diff --
    
    add outputs of `transformedData` and `transformedData2`


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