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[SPARK-8169] [ML] Add StopWordsRemover as a transformer
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jira: https://issues.apache.org/jira/browse/SPARK-8169

stop words: http://en.wikipedia.org/wiki/Stop_words

StopWordsRemover takes a string array column and outputs a string array column with all defined stop words removed. The transformer should also come with a standard set of stop words as default.

Currently I used a minimum stop words set since on some [case](http://nlp.stanford.edu/IR-book/html/htmledition/dropping-common-terms-stop-words-1.html), small set of stop words is preferred.
ASCII char has been tested, Yet I cannot check it in due to style check.

Further thought,
1. Maybe I should use OpenHashSet. Is it recommended?
2. Currently I leave the null in input array untouched, i.e. Array(null, null) => Array(null, null).
3. If the current stop words set looks too limited, any suggestion for replacement? We can have something similar to the one in [SKlearn](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/stop_words.py).

Author: Yuhao Yang <hhbyyh@gmail.com>

Closes #6742 from hhbyyh/stopwords and squashes the following commits:

fa959d8 [Yuhao Yang] separating udf
f190217 [Yuhao Yang] replace default list and other small fix
04403ab [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into stopwords
b3aa957 [Yuhao Yang] add stopWordsRemover
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hhbyyh authored and mengxr committed Aug 1, 2015
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/*
* 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.
*/

package org.apache.spark.ml.feature

import org.apache.spark.annotation.Experimental
import org.apache.spark.ml.Transformer
import org.apache.spark.ml.param.shared.{HasInputCol, HasOutputCol}
import org.apache.spark.ml.param.{ParamMap, BooleanParam, Param}
import org.apache.spark.ml.util.Identifiable
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.types.{StringType, StructField, ArrayType, StructType}
import org.apache.spark.sql.functions.{col, udf}

/**
* stop words list
*/
private object StopWords {

/**
* Use the same default stopwords list as scikit-learn.
* The original list can be found from "Glasgow Information Retrieval Group"
* [[http://ir.dcs.gla.ac.uk/resources/linguistic_utils/stop_words]]
*/
val EnglishStopWords = Array( "a", "about", "above", "across", "after", "afterwards", "again",
"against", "all", "almost", "alone", "along", "already", "also", "although", "always",
"am", "among", "amongst", "amoungst", "amount", "an", "and", "another",
"any", "anyhow", "anyone", "anything", "anyway", "anywhere", "are",
"around", "as", "at", "back", "be", "became", "because", "become",
"becomes", "becoming", "been", "before", "beforehand", "behind", "being",
"below", "beside", "besides", "between", "beyond", "bill", "both",
"bottom", "but", "by", "call", "can", "cannot", "cant", "co", "con",
"could", "couldnt", "cry", "de", "describe", "detail", "do", "done",
"down", "due", "during", "each", "eg", "eight", "either", "eleven", "else",
"elsewhere", "empty", "enough", "etc", "even", "ever", "every", "everyone",
"everything", "everywhere", "except", "few", "fifteen", "fify", "fill",
"find", "fire", "first", "five", "for", "former", "formerly", "forty",
"found", "four", "from", "front", "full", "further", "get", "give", "go",
"had", "has", "hasnt", "have", "he", "hence", "her", "here", "hereafter",
"hereby", "herein", "hereupon", "hers", "herself", "him", "himself", "his",
"how", "however", "hundred", "i", "ie", "if", "in", "inc", "indeed",
"interest", "into", "is", "it", "its", "itself", "keep", "last", "latter",
"latterly", "least", "less", "ltd", "made", "many", "may", "me",
"meanwhile", "might", "mill", "mine", "more", "moreover", "most", "mostly",
"move", "much", "must", "my", "myself", "name", "namely", "neither",
"never", "nevertheless", "next", "nine", "no", "nobody", "none", "noone",
"nor", "not", "nothing", "now", "nowhere", "of", "off", "often", "on",
"once", "one", "only", "onto", "or", "other", "others", "otherwise", "our",
"ours", "ourselves", "out", "over", "own", "part", "per", "perhaps",
"please", "put", "rather", "re", "same", "see", "seem", "seemed",
"seeming", "seems", "serious", "several", "she", "should", "show", "side",
"since", "sincere", "six", "sixty", "so", "some", "somehow", "someone",
"something", "sometime", "sometimes", "somewhere", "still", "such",
"system", "take", "ten", "than", "that", "the", "their", "them",
"themselves", "then", "thence", "there", "thereafter", "thereby",
"therefore", "therein", "thereupon", "these", "they", "thick", "thin",
"third", "this", "those", "though", "three", "through", "throughout",
"thru", "thus", "to", "together", "too", "top", "toward", "towards",
"twelve", "twenty", "two", "un", "under", "until", "up", "upon", "us",
"very", "via", "was", "we", "well", "were", "what", "whatever", "when",
"whence", "whenever", "where", "whereafter", "whereas", "whereby",
"wherein", "whereupon", "wherever", "whether", "which", "while", "whither",
"who", "whoever", "whole", "whom", "whose", "why", "will", "with",
"within", "without", "would", "yet", "you", "your", "yours", "yourself", "yourselves")
}

/**
* :: Experimental ::
* A feature transformer that filters out stop words from input.
* Note: null values from input array are preserved unless adding null to stopWords explicitly.
* @see [[http://en.wikipedia.org/wiki/Stop_words]]
*/
@Experimental
class StopWordsRemover(override val uid: String)
extends Transformer with HasInputCol with HasOutputCol {

def this() = this(Identifiable.randomUID("stopWords"))

/** @group setParam */
def setInputCol(value: String): this.type = set(inputCol, value)

/** @group setParam */
def setOutputCol(value: String): this.type = set(outputCol, value)

/**
* the stop words set to be filtered out
* @group param
*/
val stopWords: Param[Array[String]] = new Param(this, "stopWords", "stop words")

/** @group setParam */
def setStopWords(value: Array[String]): this.type = set(stopWords, value)

/** @group getParam */
def getStopWords: Array[String] = $(stopWords)

/**
* whether to do a case sensitive comparison over the stop words
* @group param
*/
val caseSensitive: BooleanParam = new BooleanParam(this, "caseSensitive",
"whether to do case-sensitive comparison during filtering")

/** @group setParam */
def setCaseSensitive(value: Boolean): this.type = set(caseSensitive, value)

/** @group getParam */
def getCaseSensitive: Boolean = $(caseSensitive)

setDefault(stopWords -> StopWords.EnglishStopWords, caseSensitive -> false)

override def transform(dataset: DataFrame): DataFrame = {
val outputSchema = transformSchema(dataset.schema)
val t = if ($(caseSensitive)) {
val stopWordsSet = $(stopWords).toSet
udf { terms: Seq[String] =>
terms.filter(s => !stopWordsSet.contains(s))
}
} else {
val toLower = (s: String) => if (s != null) s.toLowerCase else s
val lowerStopWords = $(stopWords).map(toLower(_)).toSet
udf { terms: Seq[String] =>
terms.filter(s => !lowerStopWords.contains(toLower(s)))
}
}

val metadata = outputSchema($(outputCol)).metadata
dataset.select(col("*"), t(col($(inputCol))).as($(outputCol), metadata))
}

override def transformSchema(schema: StructType): StructType = {
val inputType = schema($(inputCol)).dataType
require(inputType.sameType(ArrayType(StringType)),
s"Input type must be ArrayType(StringType) but got $inputType.")
val outputFields = schema.fields :+
StructField($(outputCol), inputType, schema($(inputCol)).nullable)
StructType(outputFields)
}

override def copy(extra: ParamMap): StopWordsRemover = defaultCopy(extra)
}
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/*
* 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.
*/

package org.apache.spark.ml.feature

import org.apache.spark.SparkFunSuite
import org.apache.spark.mllib.util.MLlibTestSparkContext
import org.apache.spark.sql.{DataFrame, Row}

object StopWordsRemoverSuite extends SparkFunSuite {
def testStopWordsRemover(t: StopWordsRemover, dataset: DataFrame): Unit = {
t.transform(dataset)
.select("filtered", "expected")
.collect()
.foreach { case Row(tokens, wantedTokens) =>
assert(tokens === wantedTokens)
}
}
}

class StopWordsRemoverSuite extends SparkFunSuite with MLlibTestSparkContext {
import StopWordsRemoverSuite._

test("StopWordsRemover default") {
val remover = new StopWordsRemover()
.setInputCol("raw")
.setOutputCol("filtered")
val dataSet = sqlContext.createDataFrame(Seq(
(Seq("test", "test"), Seq("test", "test")),
(Seq("a", "b", "c", "d"), Seq("b", "c", "d")),
(Seq("a", "the", "an"), Seq()),
(Seq("A", "The", "AN"), Seq()),
(Seq(null), Seq(null)),
(Seq(), Seq())
)).toDF("raw", "expected")

testStopWordsRemover(remover, dataSet)
}

test("StopWordsRemover case sensitive") {
val remover = new StopWordsRemover()
.setInputCol("raw")
.setOutputCol("filtered")
.setCaseSensitive(true)
val dataSet = sqlContext.createDataFrame(Seq(
(Seq("A"), Seq("A")),
(Seq("The", "the"), Seq("The"))
)).toDF("raw", "expected")

testStopWordsRemover(remover, dataSet)
}

test("StopWordsRemover with additional words") {
val stopWords = StopWords.EnglishStopWords ++ Array("python", "scala")
val remover = new StopWordsRemover()
.setInputCol("raw")
.setOutputCol("filtered")
.setStopWords(stopWords)
val dataSet = sqlContext.createDataFrame(Seq(
(Seq("python", "scala", "a"), Seq()),
(Seq("Python", "Scala", "swift"), Seq("swift"))
)).toDF("raw", "expected")

testStopWordsRemover(remover, dataSet)
}
}

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