spark CountVectorizerExample 源码
spark CountVectorizerExample 代码
文件路径：/examples/src/main/scala/org/apache/spark/examples/ml/CountVectorizerExample.scala
/*
* 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.{CountVectorizer, CountVectorizerModel}
// $example off$
import org.apache.spark.sql.SparkSession
object CountVectorizerExample {
def main(args: Array[String]): Unit = {
val spark = SparkSession
.builder
.appName("CountVectorizerExample")
.getOrCreate()
// $example on$
val df = spark.createDataFrame(Seq(
(0, Array("a", "b", "c")),
(1, Array("a", "b", "b", "c", "a"))
)).toDF("id", "words")
// fit a CountVectorizerModel from the corpus
val cvModel: CountVectorizerModel = new CountVectorizer()
.setInputCol("words")
.setOutputCol("features")
.setVocabSize(3)
.setMinDF(2)
.fit(df)
// alternatively, define CountVectorizerModel with a-priori vocabulary
val cvm = new CountVectorizerModel(Array("a", "b", "c"))
.setInputCol("words")
.setOutputCol("features")
cvModel.transform(df).show(false)
// $example off$
spark.stop()
}
}
// scalastyle:on println
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