Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/15415#discussion_r98959530 --- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala --- @@ -0,0 +1,260 @@ +/* + * 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.fpm + +import org.apache.hadoop.fs.Path + +import org.apache.spark.annotation.{Experimental, Since} +import org.apache.spark.ml.{Estimator, Model} +import org.apache.spark.ml.param._ +import org.apache.spark.ml.param.shared.{HasFeaturesCol, HasPredictionCol} +import org.apache.spark.ml.util._ +import org.apache.spark.mllib.fpm.{FPGrowth => MLlibFPGrowth, FPGrowthModel => MLlibFPGrowthModel} +import org.apache.spark.sql.{DataFrame, _} +import org.apache.spark.sql.functions._ +import org.apache.spark.sql.types.{ArrayType, StringType, StructType} + +/** + * Common params for FPGrowth and FPGrowthModel + */ +private[fpm] trait FPGrowthParams extends Params with HasFeaturesCol with HasPredictionCol { + + /** + * Validates and transforms the input schema. + * @param schema input schema + * @return output schema + */ + protected def validateAndTransformSchema(schema: StructType): StructType = { + SchemaUtils.checkColumnType(schema, $(featuresCol), new ArrayType(StringType, false)) + SchemaUtils.appendColumn(schema, $(predictionCol), new ArrayType(StringType, false)) + } + + /** + * Minimal support level of the frequent pattern. [0.0, 1.0]. Any pattern that appears + * more than (minSupport * size-of-the-dataset) times will be output + * Default: 0.3 + * @group param + */ + @Since("2.2.0") + val minSupport: DoubleParam = new DoubleParam(this, "minSupport", + "the minimal support level of the frequent pattern (Default: 0.3)", + ParamValidators.inRange(0.0, 1.0)) + setDefault(minSupport -> 0.3) + + /** @group getParam */ + @Since("2.2.0") + def getMinSupport: Double = $(minSupport) + + /** + * Number of partitions used by parallel FP-growth + * @group param + */ + @Since("2.2.0") + val numPartitions: IntParam = new IntParam(this, "numPartitions", + "Number of partitions used by parallel FP-growth", ParamValidators.gtEq[Int](1)) + + /** @group getParam */ + @Since("2.2.0") + def getNumPartitions: Int = $(numPartitions) + +} + +/** + * :: Experimental :: + * A parallel FP-growth algorithm to mine frequent itemsets. + * + * @see [[http://dx.doi.org/10.1145/1454008.1454027 Li et al., PFP: Parallel FP-Growth for Query + * Recommendation]] + */ +@Since("2.2.0") +@Experimental +class FPGrowth @Since("2.2.0") ( + @Since("2.2.0") override val uid: String) + extends Estimator[FPGrowthModel] with FPGrowthParams with DefaultParamsWritable { + + @Since("2.2.0") + def this() = this(Identifiable.randomUID("FPGrowth")) + + /** @group setParam */ + @Since("2.2.0") + def setMinSupport(value: Double): this.type = set(minSupport, value) + + /** @group setParam */ + @Since("2.2.0") + def setNumPartitions(value: Int): this.type = set(numPartitions, value) + + /** @group setParam */ + @Since("2.2.0") + def setFeaturesCol(value: String): this.type = set(featuresCol, value) + + /** @group setParam */ + @Since("2.2.0") + def setPredictionCol(value: String): this.type = set(predictionCol, value) + + def fit(dataset: Dataset[_]): FPGrowthModel = { --- End diff -- override
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