49 lines
1.6 KiB
R
49 lines
1.6 KiB
R
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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context("broadcast variables")
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# JavaSparkContext handle
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sc <- sparkR.init()
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# Partitioned data
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nums <- 1:2
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rrdd <- parallelize(sc, nums, 2L)
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test_that("using broadcast variable", {
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randomMat <- matrix(nrow=10, ncol=10, data=rnorm(100))
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randomMatBr <- broadcast(sc, randomMat)
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useBroadcast <- function(x) {
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sum(value(randomMatBr) * x)
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}
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actual <- collect(lapply(rrdd, useBroadcast))
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expected <- list(sum(randomMat) * 1, sum(randomMat) * 2)
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expect_equal(actual, expected)
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})
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test_that("without using broadcast variable", {
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randomMat <- matrix(nrow=10, ncol=10, data=rnorm(100))
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useBroadcast <- function(x) {
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sum(randomMat * x)
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}
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actual <- collect(lapply(rrdd, useBroadcast))
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expected <- list(sum(randomMat) * 1, sum(randomMat) * 2)
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expect_equal(actual, expected)
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})
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