Skip to content

[SPARK-17902][R] Revive stringsAsFactors option for collect() in SparkR #19551

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 2 commits into from
Closed

[SPARK-17902][R] Revive stringsAsFactors option for collect() in SparkR #19551

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
145b60f
Revive stringsAsFactors option for collect() in SparkR
HyukjinKwon Oct 22, 2017
f9e42d5
Swap condition for better short-circuiting
HyukjinKwon Oct 23, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions R/pkg/R/DataFrame.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1191,6 +1191,9 @@ setMethod("collect",
vec <- do.call(c, col)
stopifnot(class(vec) != "list")
class(vec) <- PRIMITIVE_TYPES[[colType]]
if (is.character(vec) && stringsAsFactors) {
vec <- as.factor(vec)
}
df[[colIndex]] <- vec
} else {
df[[colIndex]] <- col
Expand Down
6 changes: 6 additions & 0 deletions R/pkg/tests/fulltests/test_sparkSQL.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -499,6 +499,12 @@ test_that("create DataFrame with different data types", {
expect_equal(collect(df), data.frame(l, stringsAsFactors = FALSE))
})

test_that("SPARK-17902: collect() with stringsAsFactors enabled", {
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Would you please verify that factor orders are identical. I wonder if expect_equal really verifies order of values in a factor.

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more. 

> # Ordered vs unordered
> or <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Lo", "Med", "Hi"), ordered=TRUE)
> or1 <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Lo", "Med", "Hi"), ordered=FALSE)
> expect_equal(or, or1)
error: `or` not equal to `or1`.
Attributes: < Component “class”: Lengths (2, 1) differ (string compare on first 1) >
Attributes: < Component “class”: 1 string mismatch >
> # level order mismatch
> or <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Hi", "Lo", "Med"))
> or1 <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Lo", "Med", "Hi"))
> expect_equal(or, or1)
error: `or` not equal to `or1`.
Attributes: < Component “levels”: 3 string mismatches >
# Data order mismatch
> or <- factor(c("Lo", "Hi", "Med", "Med", "Hi"), levels=c("Hi", "Lo", "Med"))
> or1 <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Hi", "Lo", "Med"))
> expect_equal(or, or1)
error: `or` not equal to `or1`.
4 string mismatches
> or <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Hi", "Lo", "Med"))
> or1 <- factor(c("Hi", "Med", "Med", "Hi", "Lo"), levels=c("Hi", "Lo", "Med"))
> expect_equal(or, or1)

Would this test address your concern?

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

thanks!

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

BTW: I think iris data frame all Species values are clustered together. That is why the test is passing (the new factor order ends up being identical to the existing order).

df <- suppressWarnings(collect(createDataFrame(iris), stringsAsFactors = TRUE))
expect_equal(class(iris$Species), class(df$Species))
expect_equal(iris$Species, df$Species)
})

test_that("SPARK-17811: can create DataFrame containing NA as date and time", {
df <- data.frame(
id = 1:2,
Expand Down