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author | Oscar D. Lara Yejas <odlaraye@oscars-mbp.usca.ibm.com> | 2016-04-27 15:47:54 -0700 |
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committer | Shivaram Venkataraman <shivaram@cs.berkeley.edu> | 2016-04-27 15:47:54 -0700 |
commit | e4bfb4aa7382cb9c5e4eb7e2211551d5da716a61 (patch) | |
tree | 58d4303824aca6fec6f9f6311f2dcf7a3cb1bd4e /R/pkg/inst/tests | |
parent | 37575115b98fdc9ebadb2ebcbcd9907a3af1076c (diff) | |
download | spark-e4bfb4aa7382cb9c5e4eb7e2211551d5da716a61.tar.gz spark-e4bfb4aa7382cb9c5e4eb7e2211551d5da716a61.tar.bz2 spark-e4bfb4aa7382cb9c5e4eb7e2211551d5da716a61.zip |
[SPARK-13436][SPARKR] Added parameter drop to subsetting operator [
Added parameter drop to subsetting operator [. This is useful to get a Column from a DataFrame, given its name. R supports it.
In R:
```
> name <- "Sepal_Length"
> class(iris[, name])
[1] "numeric"
```
Currently, in SparkR:
```
> name <- "Sepal_Length"
> class(irisDF[, name])
[1] "DataFrame"
```
Previous code returns a DataFrame, which is inconsistent with R's behavior. SparkR should return a Column instead. Currently, in order for the user to return a Column given a column name as a character variable would be through `eval(parse(x))`, where x is the string `"irisDF$Sepal_Length"`. That itself is pretty hacky. `SparkR:::getColumn() `is another choice, but I don't see why this method should be externalized. Instead, following R's way to do things, the proposed implementation allows this:
```
> name <- "Sepal_Length"
> class(irisDF[, name, drop=T])
[1] "Column"
> class(irisDF[, name, drop=F])
[1] "DataFrame"
```
This is consistent with R:
```
> name <- "Sepal_Length"
> class(iris[, name])
[1] "numeric"
> class(iris[, name, drop=F])
[1] "data.frame"
```
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.usca.ibm.com>
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.attlocal.net>
Closes #11318 from olarayej/SPARK-13436.
Diffstat (limited to 'R/pkg/inst/tests')
-rw-r--r-- | R/pkg/inst/tests/testthat/test_sparkSQL.R | 24 |
1 files changed, 16 insertions, 8 deletions
diff --git a/R/pkg/inst/tests/testthat/test_sparkSQL.R b/R/pkg/inst/tests/testthat/test_sparkSQL.R index 336068035e..95d6cb8875 100644 --- a/R/pkg/inst/tests/testthat/test_sparkSQL.R +++ b/R/pkg/inst/tests/testthat/test_sparkSQL.R @@ -822,9 +822,10 @@ test_that("select operators", { expect_is(df[[2]], "Column") expect_is(df[["age"]], "Column") - expect_is(df[, 1], "SparkDataFrame") - expect_equal(columns(df[, 1]), c("name")) - expect_equal(columns(df[, "age"]), c("age")) + expect_is(df[, 1, drop = F], "SparkDataFrame") + expect_equal(columns(df[, 1, drop = F]), c("name")) + expect_equal(columns(df[, "age", drop = F]), c("age")) + df2 <- df[, c("age", "name")] expect_is(df2, "SparkDataFrame") expect_equal(columns(df2), c("age", "name")) @@ -835,6 +836,13 @@ test_that("select operators", { df$age2 <- df$age * 2 expect_equal(columns(df), c("name", "age", "age2")) expect_equal(count(where(df, df$age2 == df$age * 2)), 2) + + # Test parameter drop + expect_equal(class(df[, 1]) == "SparkDataFrame", T) + expect_equal(class(df[, 1, drop = T]) == "Column", T) + expect_equal(class(df[, 1, drop = F]) == "SparkDataFrame", T) + expect_equal(class(df[df$age > 4, 2, drop = T]) == "Column", T) + expect_equal(class(df[df$age > 4, 2, drop = F]) == "SparkDataFrame", T) }) test_that("select with column", { @@ -889,13 +897,13 @@ test_that("subsetting", { expect_equal(columns(filtered), c("name", "age")) expect_equal(collect(filtered)$name, "Andy") - df2 <- df[df$age == 19, 1] + df2 <- df[df$age == 19, 1, drop = F] expect_is(df2, "SparkDataFrame") expect_equal(count(df2), 1) expect_equal(columns(df2), c("name")) expect_equal(collect(df2)$name, "Justin") - df3 <- df[df$age > 20, 2] + df3 <- df[df$age > 20, 2, drop = F] expect_equal(count(df3), 1) expect_equal(columns(df3), c("age")) @@ -911,7 +919,7 @@ test_that("subsetting", { expect_equal(count(df6), 1) expect_equal(columns(df6), c("name", "age")) - df7 <- subset(df, select = "name") + df7 <- subset(df, select = "name", drop = F) expect_equal(count(df7), 3) expect_equal(columns(df7), c("name")) @@ -1888,7 +1896,7 @@ test_that("attach() on a DataFrame", { stat2 <- summary(age) expect_equal(collect(stat2)[5, "age"], "30") detach("df") - stat3 <- summary(df[, "age"]) + stat3 <- summary(df[, "age", drop = F]) expect_equal(collect(stat3)[5, "age"], "30") expect_error(age) }) @@ -1928,7 +1936,7 @@ test_that("Method coltypes() to get and set R's data types of a DataFrame", { df1 <- select(df, cast(df$age, "integer")) coltypes(df) <- c("character", "integer") expect_equal(dtypes(df), list(c("name", "string"), c("age", "int"))) - value <- collect(df[, 2])[[3, 1]] + value <- collect(df[, 2, drop = F])[[3, 1]] expect_equal(value, collect(df1)[[3, 1]]) expect_equal(value, 22) |