1# 2# Licensed to the Apache Software Foundation (ASF) under one or more 3# contributor license agreements. See the NOTICE file distributed with 4# this work for additional information regarding copyright ownership. 5# The ASF licenses this file to You under the Apache License, Version 2.0 6# (the "License"); you may not use this file except in compliance with 7# the License. You may obtain a copy of the License at 8# 9# http://www.apache.org/licenses/LICENSE-2.0 10# 11# Unless required by applicable law or agreed to in writing, software 12# distributed under the License is distributed on an "AS IS" BASIS, 13# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14# See the License for the specific language governing permissions and 15# limitations under the License. 16# 17 18# To run this example use 19# ./bin/spark-submit examples/src/main/r/ml/als.R 20 21# Load SparkR library into your R session 22library(SparkR) 23 24# Initialize SparkSession 25sparkR.session(appName = "SparkR-ML-als-example") 26 27# $example on$ 28# Load training data 29data <- list(list(0, 0, 4.0), list(0, 1, 2.0), list(1, 1, 3.0), 30 list(1, 2, 4.0), list(2, 1, 1.0), list(2, 2, 5.0)) 31df <- createDataFrame(data, c("userId", "movieId", "rating")) 32training <- df 33test <- df 34 35# Fit a recommendation model using ALS with spark.als 36model <- spark.als(training, maxIter = 5, regParam = 0.01, userCol = "userId", 37 itemCol = "movieId", ratingCol = "rating") 38 39# Model summary 40summary(model) 41 42# Prediction 43predictions <- predict(model, test) 44showDF(predictions) 45# $example off$ 46