spark-instrumented-optimizer/R/pkg/tests/fulltests/test_context.R
Erik Krogen cf22d947fb [SPARK-32036] Replace references to blacklist/whitelist language with more appropriate terminology, excluding the blacklisting feature
### What changes were proposed in this pull request?

This PR will remove references to these "blacklist" and "whitelist" terms besides the blacklisting feature as a whole, which can be handled in a separate JIRA/PR.

This touches quite a few files, but the changes are straightforward (variable/method/etc. name changes) and most quite self-contained.

### Why are the changes needed?

As per discussion on the Spark dev list, it will be beneficial to remove references to problematic language that can alienate potential community members. One such reference is "blacklist" and "whitelist". While it seems to me that there is some valid debate as to whether these terms have racist origins, the cultural connotations are inescapable in today's world.

### Does this PR introduce _any_ user-facing change?

In the test file `HiveQueryFileTest`, a developer has the ability to specify the system property `spark.hive.whitelist` to specify a list of Hive query files that should be tested. This system property has been renamed to `spark.hive.includelist`. The old property has been kept for compatibility, but will log a warning if used. I am open to feedback from others on whether keeping a deprecated property here is unnecessary given that this is just for developers running tests.

### How was this patch tested?

Existing tests should be suitable since no behavior changes are expected as a result of this PR.

Closes #28874 from xkrogen/xkrogen-SPARK-32036-rename-blacklists.

Authored-by: Erik Krogen <ekrogen@linkedin.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
2020-07-15 11:40:55 -05:00

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9.8 KiB
R

#
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context("test functions in sparkR.R")
test_that("Check masked functions", {
# Check that we are not masking any new function from base, stats, testthat unexpectedly
# NOTE: We should avoid adding entries to *namesOfMaskedCompletely* as masked functions make it
# hard for users to use base R functions. Please check when in doubt.
namesOfMaskedCompletely <- c("cov", "filter", "sample", "not")
namesOfMasked <- c("describe", "cov", "filter", "lag", "na.omit", "predict", "sd", "var",
"colnames", "colnames<-", "intersect", "rank", "rbind", "sample", "subset",
"summary", "transform", "drop", "window", "as.data.frame", "union", "not")
version <- packageVersion("base")
is33Above <- as.numeric(version$major) >= 3 && as.numeric(version$minor) >= 3
is40Above <- as.numeric(version$major) >= 4
if (is33Above || is40Above) {
namesOfMasked <- c("endsWith", "startsWith", namesOfMasked)
}
masked <- conflicts(detail = TRUE)$`package:SparkR`
expect_true("describe" %in% masked) # only when with testthat..
func <- lapply(masked, function(x) { capture.output(showMethods(x))[[1]] })
funcSparkROrEmpty <- grepl("\\(package SparkR\\)$|^$", func)
maskedBySparkR <- masked[funcSparkROrEmpty]
expect_equal(length(maskedBySparkR), length(namesOfMasked))
# make the 2 lists the same length so expect_equal will print their content
l <- max(length(maskedBySparkR), length(namesOfMasked))
length(maskedBySparkR) <- l
length(namesOfMasked) <- l
expect_equal(sort(maskedBySparkR, na.last = TRUE), sort(namesOfMasked, na.last = TRUE))
# above are those reported as masked when `library(SparkR)`
# note that many of these methods are still callable without base:: or stats:: prefix
# there should be a test for each of these, except followings, which are currently "broken"
funcHasAny <- unlist(lapply(masked, function(x) {
any(grepl("=\"ANY\"", capture.output(showMethods(x)[-1])))
}))
maskedCompletely <- masked[!funcHasAny]
expect_equal(length(maskedCompletely), length(namesOfMaskedCompletely))
l <- max(length(maskedCompletely), length(namesOfMaskedCompletely))
length(maskedCompletely) <- l
length(namesOfMaskedCompletely) <- l
expect_equal(sort(maskedCompletely, na.last = TRUE),
sort(namesOfMaskedCompletely, na.last = TRUE))
})
test_that("repeatedly starting and stopping SparkSession", {
for (i in 1:4) {
sparkR.session(master = sparkRTestMaster, enableHiveSupport = FALSE)
df <- createDataFrame(data.frame(dummy = 1:i))
expect_equal(count(df), i)
sparkR.session.stop()
}
})
test_that("rdd GC across sparkR.stop", {
sc <- sparkR.sparkContext(master = sparkRTestMaster) # sc should get id 0
rdd1 <- parallelize(sc, 1:20, 2L) # rdd1 should get id 1
rdd2 <- parallelize(sc, 1:10, 2L) # rdd2 should get id 2
sparkR.session.stop()
sc <- sparkR.sparkContext(master = sparkRTestMaster) # sc should get id 0 again
# GC rdd1 before creating rdd3 and rdd2 after
rm(rdd1)
gc()
rdd3 <- parallelize(sc, 1:20, 2L) # rdd3 should get id 1 now
rdd4 <- parallelize(sc, 1:10, 2L) # rdd4 should get id 2 now
rm(rdd2)
gc()
countRDD(rdd3)
countRDD(rdd4)
sparkR.session.stop()
expect_true(TRUE)
})
test_that("job group functions can be called", {
sc <- sparkR.sparkContext(master = sparkRTestMaster)
setJobGroup("groupId", "job description", TRUE)
cancelJobGroup("groupId")
clearJobGroup()
sparkR.session.stop()
expect_true(TRUE)
})
test_that("job description and local properties can be set and got", {
sc <- sparkR.sparkContext(master = sparkRTestMaster)
setJobDescription("job description")
expect_equal(getLocalProperty("spark.job.description"), "job description")
setJobDescription(1234)
expect_equal(getLocalProperty("spark.job.description"), "1234")
setJobDescription(NULL)
expect_equal(getLocalProperty("spark.job.description"), NULL)
setJobDescription(NA)
expect_equal(getLocalProperty("spark.job.description"), NULL)
setLocalProperty("spark.scheduler.pool", "poolA")
expect_equal(getLocalProperty("spark.scheduler.pool"), "poolA")
setLocalProperty("spark.scheduler.pool", NULL)
expect_equal(getLocalProperty("spark.scheduler.pool"), NULL)
setLocalProperty("spark.scheduler.pool", NA)
expect_equal(getLocalProperty("spark.scheduler.pool"), NULL)
setLocalProperty(4321, 1234)
expect_equal(getLocalProperty(4321), "1234")
setLocalProperty(4321, NULL)
expect_equal(getLocalProperty(4321), NULL)
setLocalProperty(4321, NA)
expect_equal(getLocalProperty(4321), NULL)
expect_error(setLocalProperty(NULL, "should fail"), "key should not be NULL or NA")
expect_error(getLocalProperty(NULL), "key should not be NULL or NA")
expect_error(setLocalProperty(NA, "should fail"), "key should not be NULL or NA")
expect_error(getLocalProperty(NA), "key should not be NULL or NA")
sparkR.session.stop()
})
test_that("utility function can be called", {
sparkR.sparkContext(master = sparkRTestMaster)
setLogLevel("ERROR")
sparkR.session.stop()
expect_true(TRUE)
})
test_that("getClientModeSparkSubmitOpts() returns spark-submit args from allowList", {
e <- new.env()
e[["spark.driver.memory"]] <- "512m"
ops <- getClientModeSparkSubmitOpts("sparkrmain", e)
expect_equal("--driver-memory \"512m\" sparkrmain", ops)
e[["spark.driver.memory"]] <- "5g"
e[["spark.driver.extraClassPath"]] <- "/opt/class_path" # nolint
e[["spark.driver.extraJavaOptions"]] <- "-XX:+UseCompressedOops -XX:+UseCompressedStrings"
e[["spark.driver.extraLibraryPath"]] <- "/usr/local/hadoop/lib" # nolint
e[["random"]] <- "skipthis"
ops2 <- getClientModeSparkSubmitOpts("sparkr-shell", e)
# nolint start
expect_equal(ops2, paste0("--driver-class-path \"/opt/class_path\" --driver-java-options \"",
"-XX:+UseCompressedOops -XX:+UseCompressedStrings\" --driver-library-path \"",
"/usr/local/hadoop/lib\" --driver-memory \"5g\" sparkr-shell"))
# nolint end
e[["spark.driver.extraClassPath"]] <- "/" # too short
ops3 <- getClientModeSparkSubmitOpts("--driver-memory 4g sparkr-shell2", e)
# nolint start
expect_equal(ops3, paste0("--driver-java-options \"-XX:+UseCompressedOops ",
"-XX:+UseCompressedStrings\" --driver-library-path \"/usr/local/hadoop/lib\"",
" --driver-memory 4g sparkr-shell2"))
# nolint end
})
test_that("sparkJars sparkPackages as comma-separated strings", {
expect_warning(processSparkJars(" a, b "))
jars <- suppressWarnings(processSparkJars(" a, b "))
expect_equal(lapply(jars, basename), list("a", "b"))
jars <- suppressWarnings(processSparkJars(" abc ,, def "))
expect_equal(lapply(jars, basename), list("abc", "def"))
jars <- suppressWarnings(processSparkJars(c(" abc ,, def ", "", "xyz", " ", "a,b")))
expect_equal(lapply(jars, basename), list("abc", "def", "xyz", "a", "b"))
p <- processSparkPackages(c("ghi", "lmn"))
expect_equal(p, c("ghi", "lmn"))
# check normalizePath
f <- dir()[[1]]
expect_warning(processSparkJars(f), NA)
expect_match(processSparkJars(f), f)
})
test_that("spark.lapply should perform simple transforms", {
sparkR.sparkContext(master = sparkRTestMaster)
doubled <- spark.lapply(1:10, function(x) { 2 * x })
expect_equal(doubled, as.list(2 * 1:10))
sparkR.session.stop()
})
test_that("add and get file to be downloaded with Spark job on every node", {
sparkR.sparkContext(master = sparkRTestMaster)
# Test add file.
path <- tempfile(pattern = "hello", fileext = ".txt")
filename <- basename(path)
words <- "Hello World!"
writeLines(words, path)
spark.addFile(path)
download_path <- spark.getSparkFiles(filename)
expect_equal(readLines(download_path), words)
# Test spark.getSparkFiles works well on executors.
seq <- seq(from = 1, to = 10, length.out = 5)
f <- function(seq) { spark.getSparkFiles(filename) }
results <- spark.lapply(seq, f)
for (i in 1:5) { expect_equal(basename(results[[i]]), filename) }
unlink(path)
# Test add directory recursively.
path <- paste0(tempdir(), "/", "recursive_dir")
dir.create(path)
dir_name <- basename(path)
path1 <- paste0(path, "/", "hello.txt")
file.create(path1)
sub_path <- paste0(path, "/", "sub_hello")
dir.create(sub_path)
path2 <- paste0(sub_path, "/", "sub_hello.txt")
file.create(path2)
words <- "Hello World!"
sub_words <- "Sub Hello World!"
writeLines(words, path1)
writeLines(sub_words, path2)
spark.addFile(path, recursive = TRUE)
download_path1 <- spark.getSparkFiles(paste0(dir_name, "/", "hello.txt"))
expect_equal(readLines(download_path1), words)
download_path2 <- spark.getSparkFiles(paste0(dir_name, "/", "sub_hello/sub_hello.txt"))
expect_equal(readLines(download_path2), sub_words)
unlink(path, recursive = TRUE)
sparkR.session.stop()
})
test_that("SPARK-25234: parallelize should not have integer overflow", {
sc <- sparkR.sparkContext(master = sparkRTestMaster)
# 47000 * 47000 exceeds integer range
parallelize(sc, 1:47000, 47000)
sparkR.session.stop()
expect_true(TRUE)
})