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#
# Licensed to the Apache Software Foundation (ASF) under one or more
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# 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.
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# limitations under the License.
#
context("parallelize() and collect()")
# Mock data
numVector <- c(-10:97)
numList <- list(sqrt(1), sqrt(2), sqrt(3), 4 ** 10)
strVector <- c("Dexter Morgan: I suppose I should be upset, even feel",
"violated, but I'm not. No, in fact, I think this is a friendly",
"message, like \"Hey, wanna play?\" and yes, I want to play. ",
"I really, really do.")
strList <- list("Dexter Morgan: Blood. Sometimes it sets my teeth on edge, ",
"other times it helps me control the chaos.",
"Dexter Morgan: Harry and Dorris Morgan did a wonderful job ",
"raising me. But they're both dead now. I didn't kill them. Honest.")
numPairs <- list(list(1, 1), list(1, 2), list(2, 2), list(2, 3))
strPairs <- list(list(strList, strList), list(strList, strList))
# JavaSparkContext handle
sparkSession <- sparkR.session(master = sparkRTestMaster, enableHiveSupport = FALSE)
jsc <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "getJavaSparkContext", sparkSession)
# Tests
test_that("parallelize() on simple vectors and lists returns an RDD", {
numVectorRDD <- parallelize(jsc, numVector, 1)
numVectorRDD2 <- parallelize(jsc, numVector, 10)
numListRDD <- parallelize(jsc, numList, 1)
numListRDD2 <- parallelize(jsc, numList, 4)
strVectorRDD <- parallelize(jsc, strVector, 2)
strVectorRDD2 <- parallelize(jsc, strVector, 3)
strListRDD <- parallelize(jsc, strList, 4)
strListRDD2 <- parallelize(jsc, strList, 1)
rdds <- c(numVectorRDD,
numVectorRDD2,
numListRDD,
numListRDD2,
strVectorRDD,
strVectorRDD2,
strListRDD,
strListRDD2)
for (rdd in rdds) {
expect_is(rdd, "RDD")
expect_true(.hasSlot(rdd, "jrdd")
&& inherits(rdd@jrdd, "jobj")
&& isInstanceOf(rdd@jrdd, "org.apache.spark.api.java.JavaRDD"))
}
})
test_that("collect(), following a parallelize(), gives back the original collections", {
numVectorRDD <- parallelize(jsc, numVector, 10)
expect_equal(collectRDD(numVectorRDD), as.list(numVector))
numListRDD <- parallelize(jsc, numList, 1)
numListRDD2 <- parallelize(jsc, numList, 4)
expect_equal(collectRDD(numListRDD), as.list(numList))
expect_equal(collectRDD(numListRDD2), as.list(numList))
strVectorRDD <- parallelize(jsc, strVector, 2)
strVectorRDD2 <- parallelize(jsc, strVector, 3)
expect_equal(collectRDD(strVectorRDD), as.list(strVector))
expect_equal(collectRDD(strVectorRDD2), as.list(strVector))
strListRDD <- parallelize(jsc, strList, 4)
strListRDD2 <- parallelize(jsc, strList, 1)
expect_equal(collectRDD(strListRDD), as.list(strList))
expect_equal(collectRDD(strListRDD2), as.list(strList))
})
test_that("regression: collect() following a parallelize() does not drop elements", {
# 10 %/% 6 = 1, ceiling(10 / 6) = 2
collLen <- 10
numPart <- 6
expected <- runif(collLen)
actual <- collectRDD(parallelize(jsc, expected, numPart))
expect_equal(actual, as.list(expected))
})
test_that("parallelize() and collect() work for lists of pairs (pairwise data)", {
# use the pairwise logical to indicate pairwise data
numPairsRDDD1 <- parallelize(jsc, numPairs, 1)
numPairsRDDD2 <- parallelize(jsc, numPairs, 2)
numPairsRDDD3 <- parallelize(jsc, numPairs, 3)
expect_equal(collectRDD(numPairsRDDD1), numPairs)
expect_equal(collectRDD(numPairsRDDD2), numPairs)
expect_equal(collectRDD(numPairsRDDD3), numPairs)
# can also leave out the parameter name, if the params are supplied in order
strPairsRDDD1 <- parallelize(jsc, strPairs, 1)
strPairsRDDD2 <- parallelize(jsc, strPairs, 2)
expect_equal(collectRDD(strPairsRDDD1), strPairs)
expect_equal(collectRDD(strPairsRDDD2), strPairs)
})
sparkR.session.stop()