39d677c8f1
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.
222 lines
7.7 KiB
R
222 lines
7.7 KiB
R
#
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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("partitionBy, groupByKey, reduceByKey etc.")
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# JavaSparkContext handle
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sc <- sparkR.init()
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# Data
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intPairs <- list(list(1L, -1), list(2L, 100), list(2L, 1), list(1L, 200))
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intRdd <- parallelize(sc, intPairs, 2L)
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doublePairs <- list(list(1.5, -1), list(2.5, 100), list(2.5, 1), list(1.5, 200))
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doubleRdd <- parallelize(sc, doublePairs, 2L)
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numPairs <- list(list(1L, 100), list(2L, 200), list(4L, -1), list(3L, 1),
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list(3L, 0))
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numPairsRdd <- parallelize(sc, numPairs, length(numPairs))
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strList <- list("Dexter Morgan: Blood. Sometimes it sets my teeth on edge and ",
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"Dexter Morgan: Harry and Dorris Morgan did a wonderful job ")
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strListRDD <- parallelize(sc, strList, 4)
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test_that("groupByKey for integers", {
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grouped <- groupByKey(intRdd, 2L)
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actual <- collect(grouped)
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expected <- list(list(2L, list(100, 1)), list(1L, list(-1, 200)))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("groupByKey for doubles", {
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grouped <- groupByKey(doubleRdd, 2L)
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actual <- collect(grouped)
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expected <- list(list(1.5, list(-1, 200)), list(2.5, list(100, 1)))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("reduceByKey for ints", {
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reduced <- reduceByKey(intRdd, "+", 2L)
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actual <- collect(reduced)
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expected <- list(list(2L, 101), list(1L, 199))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("reduceByKey for doubles", {
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reduced <- reduceByKey(doubleRdd, "+", 2L)
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actual <- collect(reduced)
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expected <- list(list(1.5, 199), list(2.5, 101))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("combineByKey for ints", {
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reduced <- combineByKey(intRdd, function(x) { x }, "+", "+", 2L)
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actual <- collect(reduced)
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expected <- list(list(2L, 101), list(1L, 199))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("combineByKey for doubles", {
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reduced <- combineByKey(doubleRdd, function(x) { x }, "+", "+", 2L)
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actual <- collect(reduced)
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expected <- list(list(1.5, 199), list(2.5, 101))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("combineByKey for characters", {
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stringKeyRDD <- parallelize(sc,
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list(list("max", 1L), list("min", 2L),
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list("other", 3L), list("max", 4L)), 2L)
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reduced <- combineByKey(stringKeyRDD,
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function(x) { x }, "+", "+", 2L)
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actual <- collect(reduced)
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expected <- list(list("max", 5L), list("min", 2L), list("other", 3L))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("aggregateByKey", {
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# test aggregateByKey for int keys
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rdd <- parallelize(sc, list(list(1, 1), list(1, 2), list(2, 3), list(2, 4)))
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zeroValue <- list(0, 0)
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seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
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combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
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aggregatedRDD <- aggregateByKey(rdd, zeroValue, seqOp, combOp, 2L)
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actual <- collect(aggregatedRDD)
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expected <- list(list(1, list(3, 2)), list(2, list(7, 2)))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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# test aggregateByKey for string keys
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rdd <- parallelize(sc, list(list("a", 1), list("a", 2), list("b", 3), list("b", 4)))
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zeroValue <- list(0, 0)
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seqOp <- function(x, y) { list(x[[1]] + y, x[[2]] + 1) }
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combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
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aggregatedRDD <- aggregateByKey(rdd, zeroValue, seqOp, combOp, 2L)
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actual <- collect(aggregatedRDD)
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expected <- list(list("a", list(3, 2)), list("b", list(7, 2)))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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})
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test_that("foldByKey", {
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# test foldByKey for int keys
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folded <- foldByKey(intRdd, 0, "+", 2L)
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actual <- collect(folded)
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expected <- list(list(2L, 101), list(1L, 199))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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# test foldByKey for double keys
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folded <- foldByKey(doubleRdd, 0, "+", 2L)
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actual <- collect(folded)
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expected <- list(list(1.5, 199), list(2.5, 101))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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# test foldByKey for string keys
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stringKeyPairs <- list(list("a", -1), list("b", 100), list("b", 1), list("a", 200))
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stringKeyRDD <- parallelize(sc, stringKeyPairs)
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folded <- foldByKey(stringKeyRDD, 0, "+", 2L)
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actual <- collect(folded)
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expected <- list(list("b", 101), list("a", 199))
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expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
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# test foldByKey for empty pair RDD
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rdd <- parallelize(sc, list())
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folded <- foldByKey(rdd, 0, "+", 2L)
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actual <- collect(folded)
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expected <- list()
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expect_equal(actual, expected)
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# test foldByKey for RDD with only 1 pair
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rdd <- parallelize(sc, list(list(1, 1)))
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folded <- foldByKey(rdd, 0, "+", 2L)
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actual <- collect(folded)
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expected <- list(list(1, 1))
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expect_equal(actual, expected)
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})
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test_that("partitionBy() partitions data correctly", {
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# Partition by magnitude
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partitionByMagnitude <- function(key) { if (key >= 3) 1 else 0 }
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resultRDD <- partitionBy(numPairsRdd, 2L, partitionByMagnitude)
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expected_first <- list(list(1, 100), list(2, 200)) # key < 3
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expected_second <- list(list(4, -1), list(3, 1), list(3, 0)) # key >= 3
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actual_first <- collectPartition(resultRDD, 0L)
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actual_second <- collectPartition(resultRDD, 1L)
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expect_equal(sortKeyValueList(actual_first), sortKeyValueList(expected_first))
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expect_equal(sortKeyValueList(actual_second), sortKeyValueList(expected_second))
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})
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test_that("partitionBy works with dependencies", {
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kOne <- 1
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partitionByParity <- function(key) { if (key %% 2 == kOne) 7 else 4 }
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# Partition by parity
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resultRDD <- partitionBy(numPairsRdd, numPartitions = 2L, partitionByParity)
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# keys even; 100 %% 2 == 0
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expected_first <- list(list(2, 200), list(4, -1))
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# keys odd; 3 %% 2 == 1
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expected_second <- list(list(1, 100), list(3, 1), list(3, 0))
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actual_first <- collectPartition(resultRDD, 0L)
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actual_second <- collectPartition(resultRDD, 1L)
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expect_equal(sortKeyValueList(actual_first), sortKeyValueList(expected_first))
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expect_equal(sortKeyValueList(actual_second), sortKeyValueList(expected_second))
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})
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test_that("test partitionBy with string keys", {
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words <- flatMap(strListRDD, function(line) { strsplit(line, " ")[[1]] })
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wordCount <- lapply(words, function(word) { list(word, 1L) })
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resultRDD <- partitionBy(wordCount, 2L)
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expected_first <- list(list("Dexter", 1), list("Dexter", 1))
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expected_second <- list(list("and", 1), list("and", 1))
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actual_first <- Filter(function(item) { item[[1]] == "Dexter" },
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collectPartition(resultRDD, 0L))
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actual_second <- Filter(function(item) { item[[1]] == "and" },
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collectPartition(resultRDD, 1L))
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expect_equal(sortKeyValueList(actual_first), sortKeyValueList(expected_first))
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expect_equal(sortKeyValueList(actual_second), sortKeyValueList(expected_second))
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})
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