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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.
#
context("broadcast variables")
# JavaSparkContext handle
sc <- sparkR.init()
# Partitioned data
nums <- 1:2
rrdd <- parallelize(sc, nums, 2L)
test_that("using broadcast variable", {
randomMat <- matrix(nrow=10, ncol=10, data=rnorm(100))
randomMatBr <- broadcast(sc, randomMat)
useBroadcast <- function(x) {
sum(SparkR:::value(randomMatBr) * x)
}
actual <- collect(lapply(rrdd, useBroadcast))
expected <- list(sum(randomMat) * 1, sum(randomMat) * 2)
expect_equal(actual, expected)
})
test_that("without using broadcast variable", {
randomMat <- matrix(nrow=10, ncol=10, data=rnorm(100))
useBroadcast <- function(x) {
sum(randomMat * x)
}
actual <- collect(lapply(rrdd, useBroadcast))
expected <- list(sum(randomMat) * 1, sum(randomMat) * 2)
expect_equal(actual, expected)
})
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