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[SPARK-6571][MLLIB] use wrapper in MatrixFactorizationModel.load
This fixes `predictAll` after load. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #5243 from mengxr/SPARK-6571 and squashes the following commits: 82dcaa7 [Xiangrui Meng] use wrapper in MatrixFactorizationModel.load
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mllib/src/main/scala/org/apache/spark/mllib/api/python/MatrixFactorizationModelWrapper.scala
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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. | ||
*/ | ||
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package org.apache.spark.mllib.api.python | ||
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import org.apache.spark.api.java.JavaRDD | ||
import org.apache.spark.mllib.recommendation.{MatrixFactorizationModel, Rating} | ||
import org.apache.spark.rdd.RDD | ||
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/** | ||
* A Wrapper of MatrixFactorizationModel to provide helper method for Python. | ||
*/ | ||
private[python] class MatrixFactorizationModelWrapper(model: MatrixFactorizationModel) | ||
extends MatrixFactorizationModel(model.rank, model.userFeatures, model.productFeatures) { | ||
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def predict(userAndProducts: JavaRDD[Array[Any]]): RDD[Rating] = | ||
predict(SerDe.asTupleRDD(userAndProducts.rdd)) | ||
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def getUserFeatures: RDD[Array[Any]] = { | ||
SerDe.fromTuple2RDD(userFeatures.asInstanceOf[RDD[(Any, Any)]]) | ||
} | ||
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def getProductFeatures: RDD[Array[Any]] = { | ||
SerDe.fromTuple2RDD(productFeatures.asInstanceOf[RDD[(Any, Any)]]) | ||
} | ||
} |
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