spark MatrixFactorizationModelWrapper 源码
spark MatrixFactorizationModelWrapper 代码
文件路径：/mllib/src/main/scala/org/apache/spark/mllib/api/python/MatrixFactorizationModelWrapper.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.
*/
package org.apache.spark.mllib.api.python
import org.apache.spark.api.java.JavaRDD
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.recommendation.{MatrixFactorizationModel, Rating}
import org.apache.spark.rdd.RDD
/**
* A Wrapper of MatrixFactorizationModel to provide helper method for Python.
*/
private[python] class MatrixFactorizationModelWrapper(model: MatrixFactorizationModel)
extends MatrixFactorizationModel(model.rank, model.userFeatures, model.productFeatures) {
def predict(userAndProducts: JavaRDD[Array[Any]]): RDD[Rating] =
predict(SerDe.asTupleRDD(userAndProducts.rdd))
def getUserFeatures: RDD[Array[Any]] = {
SerDe.fromTuple2RDD(userFeatures.map {
case (user, feature) => (user, Vectors.dense(feature))
}.asInstanceOf[RDD[(Any, Any)]])
}
def getProductFeatures: RDD[Array[Any]] = {
SerDe.fromTuple2RDD(productFeatures.map {
case (product, feature) => (product, Vectors.dense(feature))
}.asInstanceOf[RDD[(Any, Any)]])
}
def wrappedRecommendProductsForUsers(num: Int): RDD[Array[Any]] = {
SerDe.fromTuple2RDD(recommendProductsForUsers(num).asInstanceOf[RDD[(Any, Any)]])
}
def wrappedRecommendUsersForProducts(num: Int): RDD[Array[Any]] = {
SerDe.fromTuple2RDD(recommendUsersForProducts(num).asInstanceOf[RDD[(Any, Any)]])
}
}
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