spark-instrumented-optimizer/R/pkg/inst/tests/testthat/test_rdd.R
Sun Rui 39d677c8f1 [SPARK-12034][SPARKR] Eliminate warnings in SparkR test cases.
This PR:
1. Suppress all known warnings.
2. Cleanup test cases and fix some errors in test cases.
3. Fix errors in HiveContext related test cases. These test cases are actually not run previously due to a bug of creating TestHiveContext.
4. Support 'testthat' package version 0.11.0 which prefers that test cases be under 'tests/testthat'
5. Make sure the default Hadoop file system is local when running test cases.
6. Turn on warnings into errors.

Author: Sun Rui <rui.sun@intel.com>

Closes #10030 from sun-rui/SPARK-12034.
2015-12-07 10:38:17 -08:00

794 lines
27 KiB
R

#
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# 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("basic RDD functions")
# JavaSparkContext handle
sc <- sparkR.init()
# Data
nums <- 1:10
rdd <- parallelize(sc, nums, 2L)
intPairs <- list(list(1L, -1), list(2L, 100), list(2L, 1), list(1L, 200))
intRdd <- parallelize(sc, intPairs, 2L)
test_that("get number of partitions in RDD", {
expect_equal(getNumPartitions(rdd), 2)
expect_equal(getNumPartitions(intRdd), 2)
})
test_that("first on RDD", {
expect_equal(first(rdd), 1)
newrdd <- lapply(rdd, function(x) x + 1)
expect_equal(first(newrdd), 2)
})
test_that("count and length on RDD", {
expect_equal(count(rdd), 10)
expect_equal(length(rdd), 10)
})
test_that("count by values and keys", {
mods <- lapply(rdd, function(x) { x %% 3 })
actual <- countByValue(mods)
expected <- list(list(0, 3L), list(1, 4L), list(2, 3L))
expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
actual <- countByKey(intRdd)
expected <- list(list(2L, 2L), list(1L, 2L))
expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
})
test_that("lapply on RDD", {
multiples <- lapply(rdd, function(x) { 2 * x })
actual <- collect(multiples)
expect_equal(actual, as.list(nums * 2))
})
test_that("lapplyPartition on RDD", {
sums <- lapplyPartition(rdd, function(part) { sum(unlist(part)) })
actual <- collect(sums)
expect_equal(actual, list(15, 40))
})
test_that("mapPartitions on RDD", {
sums <- mapPartitions(rdd, function(part) { sum(unlist(part)) })
actual <- collect(sums)
expect_equal(actual, list(15, 40))
})
test_that("flatMap() on RDDs", {
flat <- flatMap(intRdd, function(x) { list(x, x) })
actual <- collect(flat)
expect_equal(actual, rep(intPairs, each=2))
})
test_that("filterRDD on RDD", {
filtered.rdd <- filterRDD(rdd, function(x) { x %% 2 == 0 })
actual <- collect(filtered.rdd)
expect_equal(actual, list(2, 4, 6, 8, 10))
filtered.rdd <- Filter(function(x) { x[[2]] < 0 }, intRdd)
actual <- collect(filtered.rdd)
expect_equal(actual, list(list(1L, -1)))
# Filter out all elements.
filtered.rdd <- filterRDD(rdd, function(x) { x > 10 })
actual <- collect(filtered.rdd)
expect_equal(actual, list())
})
test_that("lookup on RDD", {
vals <- lookup(intRdd, 1L)
expect_equal(vals, list(-1, 200))
vals <- lookup(intRdd, 3L)
expect_equal(vals, list())
})
test_that("several transformations on RDD (a benchmark on PipelinedRDD)", {
rdd2 <- rdd
for (i in 1:12)
rdd2 <- lapplyPartitionsWithIndex(
rdd2, function(partIndex, part) {
part <- as.list(unlist(part) * partIndex + i)
})
rdd2 <- lapply(rdd2, function(x) x + x)
actual <- collect(rdd2)
expected <- list(24, 24, 24, 24, 24,
168, 170, 172, 174, 176)
expect_equal(actual, expected)
})
test_that("PipelinedRDD support actions: cache(), persist(), unpersist(), checkpoint()", {
# RDD
rdd2 <- rdd
# PipelinedRDD
rdd2 <- lapplyPartitionsWithIndex(
rdd2,
function(partIndex, part) {
part <- as.list(unlist(part) * partIndex)
})
cache(rdd2)
expect_true(rdd2@env$isCached)
rdd2 <- lapply(rdd2, function(x) x)
expect_false(rdd2@env$isCached)
unpersist(rdd2)
expect_false(rdd2@env$isCached)
persist(rdd2, "MEMORY_AND_DISK")
expect_true(rdd2@env$isCached)
rdd2 <- lapply(rdd2, function(x) x)
expect_false(rdd2@env$isCached)
unpersist(rdd2)
expect_false(rdd2@env$isCached)
tempDir <- tempfile(pattern = "checkpoint")
setCheckpointDir(sc, tempDir)
checkpoint(rdd2)
expect_true(rdd2@env$isCheckpointed)
rdd2 <- lapply(rdd2, function(x) x)
expect_false(rdd2@env$isCached)
expect_false(rdd2@env$isCheckpointed)
# make sure the data is collectable
collect(rdd2)
unlink(tempDir)
})
test_that("reduce on RDD", {
sum <- reduce(rdd, "+")
expect_equal(sum, 55)
# Also test with an inline function
sumInline <- reduce(rdd, function(x, y) { x + y })
expect_equal(sumInline, 55)
})
test_that("lapply with dependency", {
fa <- 5
multiples <- lapply(rdd, function(x) { fa * x })
actual <- collect(multiples)
expect_equal(actual, as.list(nums * 5))
})
test_that("lapplyPartitionsWithIndex on RDDs", {
func <- function(partIndex, part) { list(partIndex, Reduce("+", part)) }
actual <- collect(lapplyPartitionsWithIndex(rdd, func), flatten = FALSE)
expect_equal(actual, list(list(0, 15), list(1, 40)))
pairsRDD <- parallelize(sc, list(list(1, 2), list(3, 4), list(4, 8)), 1L)
partitionByParity <- function(key) { if (key %% 2 == 1) 0 else 1 }
mkTup <- function(partIndex, part) { list(partIndex, part) }
actual <- collect(lapplyPartitionsWithIndex(
partitionBy(pairsRDD, 2L, partitionByParity),
mkTup),
FALSE)
expect_equal(actual, list(list(0, list(list(1, 2), list(3, 4))),
list(1, list(list(4, 8)))))
})
test_that("sampleRDD() on RDDs", {
expect_equal(unlist(collect(sampleRDD(rdd, FALSE, 1.0, 2014L))), nums)
})
test_that("takeSample() on RDDs", {
# ported from RDDSuite.scala, modified seeds
data <- parallelize(sc, 1:100, 2L)
for (seed in 4:5) {
s <- takeSample(data, FALSE, 20L, seed)
expect_equal(length(s), 20L)
expect_equal(length(unique(s)), 20L)
for (elem in s) {
expect_true(elem >= 1 && elem <= 100)
}
}
for (seed in 4:5) {
s <- takeSample(data, FALSE, 200L, seed)
expect_equal(length(s), 100L)
expect_equal(length(unique(s)), 100L)
for (elem in s) {
expect_true(elem >= 1 && elem <= 100)
}
}
for (seed in 4:5) {
s <- takeSample(data, TRUE, 20L, seed)
expect_equal(length(s), 20L)
for (elem in s) {
expect_true(elem >= 1 && elem <= 100)
}
}
for (seed in 4:5) {
s <- takeSample(data, TRUE, 100L, seed)
expect_equal(length(s), 100L)
# Chance of getting all distinct elements is astronomically low, so test we
# got < 100
expect_true(length(unique(s)) < 100L)
}
for (seed in 4:5) {
s <- takeSample(data, TRUE, 200L, seed)
expect_equal(length(s), 200L)
# Chance of getting all distinct elements is still quite low, so test we
# got < 100
expect_true(length(unique(s)) < 100L)
}
})
test_that("mapValues() on pairwise RDDs", {
multiples <- mapValues(intRdd, function(x) { x * 2 })
actual <- collect(multiples)
expected <- lapply(intPairs, function(x) {
list(x[[1]], x[[2]] * 2)
})
expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
})
test_that("flatMapValues() on pairwise RDDs", {
l <- parallelize(sc, list(list(1, c(1,2)), list(2, c(3,4))))
actual <- collect(flatMapValues(l, function(x) { x }))
expect_equal(actual, list(list(1,1), list(1,2), list(2,3), list(2,4)))
# Generate x to x+1 for every value
actual <- collect(flatMapValues(intRdd, function(x) { x: (x + 1) }))
expect_equal(actual,
list(list(1L, -1), list(1L, 0), list(2L, 100), list(2L, 101),
list(2L, 1), list(2L, 2), list(1L, 200), list(1L, 201)))
})
test_that("reduceByKeyLocally() on PairwiseRDDs", {
pairs <- parallelize(sc, list(list(1, 2), list(1.1, 3), list(1, 4)), 2L)
actual <- reduceByKeyLocally(pairs, "+")
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list(1, 6), list(1.1, 3))))
pairs <- parallelize(sc, list(list("abc", 1.2), list(1.1, 0), list("abc", 1.3),
list("bb", 5)), 4L)
actual <- reduceByKeyLocally(pairs, "+")
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list("abc", 2.5), list(1.1, 0), list("bb", 5))))
})
test_that("distinct() on RDDs", {
nums.rep2 <- rep(1:10, 2)
rdd.rep2 <- parallelize(sc, nums.rep2, 2L)
uniques <- distinct(rdd.rep2)
actual <- sort(unlist(collect(uniques)))
expect_equal(actual, nums)
})
test_that("maximum() on RDDs", {
max <- maximum(rdd)
expect_equal(max, 10)
})
test_that("minimum() on RDDs", {
min <- minimum(rdd)
expect_equal(min, 1)
})
test_that("sumRDD() on RDDs", {
sum <- sumRDD(rdd)
expect_equal(sum, 55)
})
test_that("keyBy on RDDs", {
func <- function(x) { x * x }
keys <- keyBy(rdd, func)
actual <- collect(keys)
expect_equal(actual, lapply(nums, function(x) { list(func(x), x) }))
})
test_that("repartition/coalesce on RDDs", {
rdd <- parallelize(sc, 1:20, 4L) # each partition contains 5 elements
# repartition
r1 <- repartition(rdd, 2)
expect_equal(getNumPartitions(r1), 2L)
count <- length(collectPartition(r1, 0L))
expect_true(count >= 8 && count <= 12)
r2 <- repartition(rdd, 6)
expect_equal(getNumPartitions(r2), 6L)
count <- length(collectPartition(r2, 0L))
expect_true(count >= 0 && count <= 4)
# coalesce
r3 <- coalesce(rdd, 1)
expect_equal(getNumPartitions(r3), 1L)
count <- length(collectPartition(r3, 0L))
expect_equal(count, 20)
})
test_that("sortBy() on RDDs", {
sortedRdd <- sortBy(rdd, function(x) { x * x }, ascending = FALSE)
actual <- collect(sortedRdd)
expect_equal(actual, as.list(sort(nums, decreasing = TRUE)))
rdd2 <- parallelize(sc, sort(nums, decreasing = TRUE), 2L)
sortedRdd2 <- sortBy(rdd2, function(x) { x * x })
actual <- collect(sortedRdd2)
expect_equal(actual, as.list(nums))
})
test_that("takeOrdered() on RDDs", {
l <- list(10, 1, 2, 9, 3, 4, 5, 6, 7)
rdd <- parallelize(sc, l)
actual <- takeOrdered(rdd, 6L)
expect_equal(actual, as.list(sort(unlist(l)))[1:6])
l <- list("e", "d", "c", "d", "a")
rdd <- parallelize(sc, l)
actual <- takeOrdered(rdd, 3L)
expect_equal(actual, as.list(sort(unlist(l)))[1:3])
})
test_that("top() on RDDs", {
l <- list(10, 1, 2, 9, 3, 4, 5, 6, 7)
rdd <- parallelize(sc, l)
actual <- top(rdd, 6L)
expect_equal(actual, as.list(sort(unlist(l), decreasing = TRUE))[1:6])
l <- list("e", "d", "c", "d", "a")
rdd <- parallelize(sc, l)
actual <- top(rdd, 3L)
expect_equal(actual, as.list(sort(unlist(l), decreasing = TRUE))[1:3])
})
test_that("fold() on RDDs", {
actual <- fold(rdd, 0, "+")
expect_equal(actual, Reduce("+", nums, 0))
rdd <- parallelize(sc, list())
actual <- fold(rdd, 0, "+")
expect_equal(actual, 0)
})
test_that("aggregateRDD() on RDDs", {
rdd <- parallelize(sc, list(1, 2, 3, 4))
zeroValue <- list(0, 0)
seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
actual <- aggregateRDD(rdd, zeroValue, seqOp, combOp)
expect_equal(actual, list(10, 4))
rdd <- parallelize(sc, list())
actual <- aggregateRDD(rdd, zeroValue, seqOp, combOp)
expect_equal(actual, list(0, 0))
})
test_that("zipWithUniqueId() on RDDs", {
rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
actual <- collect(zipWithUniqueId(rdd))
expected <- list(list("a", 0), list("b", 3), list("c", 1),
list("d", 4), list("e", 2))
expect_equal(actual, expected)
rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 1L)
actual <- collect(zipWithUniqueId(rdd))
expected <- list(list("a", 0), list("b", 1), list("c", 2),
list("d", 3), list("e", 4))
expect_equal(actual, expected)
})
test_that("zipWithIndex() on RDDs", {
rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
actual <- collect(zipWithIndex(rdd))
expected <- list(list("a", 0), list("b", 1), list("c", 2),
list("d", 3), list("e", 4))
expect_equal(actual, expected)
rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 1L)
actual <- collect(zipWithIndex(rdd))
expected <- list(list("a", 0), list("b", 1), list("c", 2),
list("d", 3), list("e", 4))
expect_equal(actual, expected)
})
test_that("glom() on RDD", {
rdd <- parallelize(sc, as.list(1:4), 2L)
actual <- collect(glom(rdd))
expect_equal(actual, list(list(1, 2), list(3, 4)))
})
test_that("keys() on RDDs", {
keys <- keys(intRdd)
actual <- collect(keys)
expect_equal(actual, lapply(intPairs, function(x) { x[[1]] }))
})
test_that("values() on RDDs", {
values <- values(intRdd)
actual <- collect(values)
expect_equal(actual, lapply(intPairs, function(x) { x[[2]] }))
})
test_that("pipeRDD() on RDDs", {
actual <- collect(pipeRDD(rdd, "more"))
expected <- as.list(as.character(1:10))
expect_equal(actual, expected)
trailed.rdd <- parallelize(sc, c("1", "", "2\n", "3\n\r\n"))
actual <- collect(pipeRDD(trailed.rdd, "sort"))
expected <- list("", "1", "2", "3")
expect_equal(actual, expected)
rev.nums <- 9:0
rev.rdd <- parallelize(sc, rev.nums, 2L)
actual <- collect(pipeRDD(rev.rdd, "sort"))
expected <- as.list(as.character(c(5:9, 0:4)))
expect_equal(actual, expected)
})
test_that("zipRDD() on RDDs", {
rdd1 <- parallelize(sc, 0:4, 2)
rdd2 <- parallelize(sc, 1000:1004, 2)
actual <- collect(zipRDD(rdd1, rdd2))
expect_equal(actual,
list(list(0, 1000), list(1, 1001), list(2, 1002), list(3, 1003), list(4, 1004)))
mockFile <- c("Spark is pretty.", "Spark is awesome.")
fileName <- tempfile(pattern="spark-test", fileext=".tmp")
writeLines(mockFile, fileName)
rdd <- textFile(sc, fileName, 1)
actual <- collect(zipRDD(rdd, rdd))
expected <- lapply(mockFile, function(x) { list(x ,x) })
expect_equal(actual, expected)
rdd1 <- parallelize(sc, 0:1, 1)
actual <- collect(zipRDD(rdd1, rdd))
expected <- lapply(0:1, function(x) { list(x, mockFile[x + 1]) })
expect_equal(actual, expected)
rdd1 <- map(rdd, function(x) { x })
actual <- collect(zipRDD(rdd, rdd1))
expected <- lapply(mockFile, function(x) { list(x, x) })
expect_equal(actual, expected)
unlink(fileName)
})
test_that("cartesian() on RDDs", {
rdd <- parallelize(sc, 1:3)
actual <- collect(cartesian(rdd, rdd))
expect_equal(sortKeyValueList(actual),
list(
list(1, 1), list(1, 2), list(1, 3),
list(2, 1), list(2, 2), list(2, 3),
list(3, 1), list(3, 2), list(3, 3)))
# test case where one RDD is empty
emptyRdd <- parallelize(sc, list())
actual <- collect(cartesian(rdd, emptyRdd))
expect_equal(actual, list())
mockFile <- c("Spark is pretty.", "Spark is awesome.")
fileName <- tempfile(pattern="spark-test", fileext=".tmp")
writeLines(mockFile, fileName)
rdd <- textFile(sc, fileName)
actual <- collect(cartesian(rdd, rdd))
expected <- list(
list("Spark is awesome.", "Spark is pretty."),
list("Spark is awesome.", "Spark is awesome."),
list("Spark is pretty.", "Spark is pretty."),
list("Spark is pretty.", "Spark is awesome."))
expect_equal(sortKeyValueList(actual), expected)
rdd1 <- parallelize(sc, 0:1)
actual <- collect(cartesian(rdd1, rdd))
expect_equal(sortKeyValueList(actual),
list(
list(0, "Spark is pretty."),
list(0, "Spark is awesome."),
list(1, "Spark is pretty."),
list(1, "Spark is awesome.")))
rdd1 <- map(rdd, function(x) { x })
actual <- collect(cartesian(rdd, rdd1))
expect_equal(sortKeyValueList(actual), expected)
unlink(fileName)
})
test_that("subtract() on RDDs", {
l <- list(1, 1, 2, 2, 3, 4)
rdd1 <- parallelize(sc, l)
# subtract by itself
actual <- collect(subtract(rdd1, rdd1))
expect_equal(actual, list())
# subtract by an empty RDD
rdd2 <- parallelize(sc, list())
actual <- collect(subtract(rdd1, rdd2))
expect_equal(as.list(sort(as.vector(actual, mode="integer"))),
l)
rdd2 <- parallelize(sc, list(2, 4))
actual <- collect(subtract(rdd1, rdd2))
expect_equal(as.list(sort(as.vector(actual, mode="integer"))),
list(1, 1, 3))
l <- list("a", "a", "b", "b", "c", "d")
rdd1 <- parallelize(sc, l)
rdd2 <- parallelize(sc, list("b", "d"))
actual <- collect(subtract(rdd1, rdd2))
expect_equal(as.list(sort(as.vector(actual, mode="character"))),
list("a", "a", "c"))
})
test_that("subtractByKey() on pairwise RDDs", {
l <- list(list("a", 1), list("b", 4),
list("b", 5), list("a", 2))
rdd1 <- parallelize(sc, l)
# subtractByKey by itself
actual <- collect(subtractByKey(rdd1, rdd1))
expect_equal(actual, list())
# subtractByKey by an empty RDD
rdd2 <- parallelize(sc, list())
actual <- collect(subtractByKey(rdd1, rdd2))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(l))
rdd2 <- parallelize(sc, list(list("a", 3), list("c", 1)))
actual <- collect(subtractByKey(rdd1, rdd2))
expect_equal(actual,
list(list("b", 4), list("b", 5)))
l <- list(list(1, 1), list(2, 4),
list(2, 5), list(1, 2))
rdd1 <- parallelize(sc, l)
rdd2 <- parallelize(sc, list(list(1, 3), list(3, 1)))
actual <- collect(subtractByKey(rdd1, rdd2))
expect_equal(actual,
list(list(2, 4), list(2, 5)))
})
test_that("intersection() on RDDs", {
# intersection with self
actual <- collect(intersection(rdd, rdd))
expect_equal(sort(as.integer(actual)), nums)
# intersection with an empty RDD
emptyRdd <- parallelize(sc, list())
actual <- collect(intersection(rdd, emptyRdd))
expect_equal(actual, list())
rdd1 <- parallelize(sc, list(1, 10, 2, 3, 4, 5))
rdd2 <- parallelize(sc, list(1, 6, 2, 3, 7, 8))
actual <- collect(intersection(rdd1, rdd2))
expect_equal(sort(as.integer(actual)), 1:3)
})
test_that("join() on pairwise RDDs", {
rdd1 <- parallelize(sc, list(list(1,1), list(2,4)))
rdd2 <- parallelize(sc, list(list(1,2), list(1,3)))
actual <- collect(join(rdd1, rdd2, 2L))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list(1, list(1, 2)), list(1, list(1, 3)))))
rdd1 <- parallelize(sc, list(list("a",1), list("b",4)))
rdd2 <- parallelize(sc, list(list("a",2), list("a",3)))
actual <- collect(join(rdd1, rdd2, 2L))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list("a", list(1, 2)), list("a", list(1, 3)))))
rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
actual <- collect(join(rdd1, rdd2, 2L))
expect_equal(actual, list())
rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
actual <- collect(join(rdd1, rdd2, 2L))
expect_equal(actual, list())
})
test_that("leftOuterJoin() on pairwise RDDs", {
rdd1 <- parallelize(sc, list(list(1,1), list(2,4)))
rdd2 <- parallelize(sc, list(list(1,2), list(1,3)))
actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
expected <- list(list(1, list(1, 2)), list(1, list(1, 3)), list(2, list(4, NULL)))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list("a",1), list("b",4)))
rdd2 <- parallelize(sc, list(list("a",2), list("a",3)))
actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
expected <- list(list("b", list(4, NULL)), list("a", list(1, 2)), list("a", list(1, 3)))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
expected <- list(list(1, list(1, NULL)), list(2, list(2, NULL)))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
actual <- collect(leftOuterJoin(rdd1, rdd2, 2L))
expected <- list(list("b", list(2, NULL)), list("a", list(1, NULL)))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(expected))
})
test_that("rightOuterJoin() on pairwise RDDs", {
rdd1 <- parallelize(sc, list(list(1,2), list(1,3)))
rdd2 <- parallelize(sc, list(list(1,1), list(2,4)))
actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
expected <- list(list(1, list(2, 1)), list(1, list(3, 1)), list(2, list(NULL, 4)))
expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list("a",2), list("a",3)))
rdd2 <- parallelize(sc, list(list("a",1), list("b",4)))
actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
expected <- list(list("b", list(NULL, 4)), list("a", list(2, 1)), list("a", list(3, 1)))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list(3, list(NULL, 3)), list(4, list(NULL, 4)))))
rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
actual <- collect(rightOuterJoin(rdd1, rdd2, 2L))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list("d", list(NULL, 4)), list("c", list(NULL, 3)))))
})
test_that("fullOuterJoin() on pairwise RDDs", {
rdd1 <- parallelize(sc, list(list(1,2), list(1,3), list(3,3)))
rdd2 <- parallelize(sc, list(list(1,1), list(2,4)))
actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
expected <- list(list(1, list(2, 1)), list(1, list(3, 1)),
list(2, list(NULL, 4)), list(3, list(3, NULL)))
expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list("a",2), list("a",3), list("c", 1)))
rdd2 <- parallelize(sc, list(list("a",1), list("b",4)))
actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
expected <- list(list("b", list(NULL, 4)), list("a", list(2, 1)),
list("a", list(3, 1)), list("c", list(1, NULL)))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(expected))
rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list(1, list(1, NULL)), list(2, list(2, NULL)),
list(3, list(NULL, 3)), list(4, list(NULL, 4)))))
rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
expect_equal(sortKeyValueList(actual),
sortKeyValueList(list(list("a", list(1, NULL)), list("b", list(2, NULL)),
list("d", list(NULL, 4)), list("c", list(NULL, 3)))))
})
test_that("sortByKey() on pairwise RDDs", {
numPairsRdd <- map(rdd, function(x) { list (x, x) })
sortedRdd <- sortByKey(numPairsRdd, ascending = FALSE)
actual <- collect(sortedRdd)
numPairs <- lapply(nums, function(x) { list (x, x) })
expect_equal(actual, sortKeyValueList(numPairs, decreasing = TRUE))
rdd2 <- parallelize(sc, sort(nums, decreasing = TRUE), 2L)
numPairsRdd2 <- map(rdd2, function(x) { list (x, x) })
sortedRdd2 <- sortByKey(numPairsRdd2)
actual <- collect(sortedRdd2)
expect_equal(actual, numPairs)
# sort by string keys
l <- list(list("a", 1), list("b", 2), list("1", 3), list("d", 4), list("2", 5))
rdd3 <- parallelize(sc, l, 2L)
sortedRdd3 <- sortByKey(rdd3)
actual <- collect(sortedRdd3)
expect_equal(actual, list(list("1", 3), list("2", 5), list("a", 1), list("b", 2), list("d", 4)))
# test on the boundary cases
# boundary case 1: the RDD to be sorted has only 1 partition
rdd4 <- parallelize(sc, l, 1L)
sortedRdd4 <- sortByKey(rdd4)
actual <- collect(sortedRdd4)
expect_equal(actual, list(list("1", 3), list("2", 5), list("a", 1), list("b", 2), list("d", 4)))
# boundary case 2: the sorted RDD has only 1 partition
rdd5 <- parallelize(sc, l, 2L)
sortedRdd5 <- sortByKey(rdd5, numPartitions = 1L)
actual <- collect(sortedRdd5)
expect_equal(actual, list(list("1", 3), list("2", 5), list("a", 1), list("b", 2), list("d", 4)))
# boundary case 3: the RDD to be sorted has only 1 element
l2 <- list(list("a", 1))
rdd6 <- parallelize(sc, l2, 2L)
sortedRdd6 <- sortByKey(rdd6)
actual <- collect(sortedRdd6)
expect_equal(actual, l2)
# boundary case 4: the RDD to be sorted has 0 element
l3 <- list()
rdd7 <- parallelize(sc, l3, 2L)
sortedRdd7 <- sortByKey(rdd7)
actual <- collect(sortedRdd7)
expect_equal(actual, l3)
})
test_that("collectAsMap() on a pairwise RDD", {
rdd <- parallelize(sc, list(list(1, 2), list(3, 4)))
vals <- collectAsMap(rdd)
expect_equal(vals, list(`1` = 2, `3` = 4))
rdd <- parallelize(sc, list(list("a", 1), list("b", 2)))
vals <- collectAsMap(rdd)
expect_equal(vals, list(a = 1, b = 2))
rdd <- parallelize(sc, list(list(1.1, 2.2), list(1.2, 2.4)))
vals <- collectAsMap(rdd)
expect_equal(vals, list(`1.1` = 2.2, `1.2` = 2.4))
rdd <- parallelize(sc, list(list(1, "a"), list(2, "b")))
vals <- collectAsMap(rdd)
expect_equal(vals, list(`1` = "a", `2` = "b"))
})
test_that("show()", {
rdd <- parallelize(sc, list(1:10))
expect_output(show(rdd), "ParallelCollectionRDD\\[\\d+\\] at parallelize at RRDD\\.scala:\\d+")
})
test_that("sampleByKey() on pairwise RDDs", {
rdd <- parallelize(sc, 1:2000)
pairsRDD <- lapply(rdd, function(x) { if (x %% 2 == 0) list("a", x) else list("b", x) })
fractions <- list(a = 0.2, b = 0.1)
sample <- sampleByKey(pairsRDD, FALSE, fractions, 1618L)
expect_equal(100 < length(lookup(sample, "a")) && 300 > length(lookup(sample, "a")), TRUE)
expect_equal(50 < length(lookup(sample, "b")) && 150 > length(lookup(sample, "b")), TRUE)
expect_equal(lookup(sample, "a")[which.min(lookup(sample, "a"))] >= 0, TRUE)
expect_equal(lookup(sample, "a")[which.max(lookup(sample, "a"))] <= 2000, TRUE)
expect_equal(lookup(sample, "b")[which.min(lookup(sample, "b"))] >= 0, TRUE)
expect_equal(lookup(sample, "b")[which.max(lookup(sample, "b"))] <= 2000, TRUE)
rdd <- parallelize(sc, 1:2000)
pairsRDD <- lapply(rdd, function(x) { if (x %% 2 == 0) list(2, x) else list(3, x) })
fractions <- list(`2` = 0.2, `3` = 0.1)
sample <- sampleByKey(pairsRDD, TRUE, fractions, 1618L)
expect_equal(100 < length(lookup(sample, 2)) && 300 > length(lookup(sample, 2)), TRUE)
expect_equal(50 < length(lookup(sample, 3)) && 150 > length(lookup(sample, 3)), TRUE)
expect_equal(lookup(sample, 2)[which.min(lookup(sample, 2))] >= 0, TRUE)
expect_equal(lookup(sample, 2)[which.max(lookup(sample, 2))] <= 2000, TRUE)
expect_equal(lookup(sample, 3)[which.min(lookup(sample, 3))] >= 0, TRUE)
expect_equal(lookup(sample, 3)[which.max(lookup(sample, 3))] <= 2000, TRUE)
})