diff options
| -rw-r--r-- | R/pkg/NAMESPACE | 2 | ||||
| -rw-r--r-- | R/pkg/R/SQLContext.R | 7 | ||||
| -rw-r--r-- | R/pkg/inst/tests/testthat/test_context.R | 15 | ||||
| -rw-r--r-- | R/pkg/inst/tests/testthat/test_sparkSQL.R | 13 | ||||
| -rw-r--r-- | docs/sparkr.md | 11 |
5 files changed, 21 insertions, 27 deletions
diff --git a/R/pkg/NAMESPACE b/R/pkg/NAMESPACE index 7739e9ea86..00634c1a70 100644 --- a/R/pkg/NAMESPACE +++ b/R/pkg/NAMESPACE @@ -280,7 +280,7 @@ export("as.DataFrame", "read.text", "sql", "str", - "table", + "tableToDF", "tableNames", "tables", "uncacheTable") diff --git a/R/pkg/R/SQLContext.R b/R/pkg/R/SQLContext.R index 99679b4a77..16a2578678 100644 --- a/R/pkg/R/SQLContext.R +++ b/R/pkg/R/SQLContext.R @@ -352,6 +352,8 @@ sql <- function(sqlContext, sqlQuery) { #' @param sqlContext SQLContext to use #' @param tableName The SparkSQL Table to convert to a DataFrame. #' @return DataFrame +#' @rdname tableToDF +#' @name tableToDF #' @export #' @examples #'\dontrun{ @@ -360,15 +362,14 @@ sql <- function(sqlContext, sqlQuery) { #' path <- "path/to/file.json" #' df <- read.json(sqlContext, path) #' registerTempTable(df, "table") -#' new_df <- table(sqlContext, "table") +#' new_df <- tableToDF(sqlContext, "table") #' } -table <- function(sqlContext, tableName) { +tableToDF <- function(sqlContext, tableName) { sdf <- callJMethod(sqlContext, "table", tableName) dataFrame(sdf) } - #' Tables #' #' Returns a DataFrame containing names of tables in the given database. diff --git a/R/pkg/inst/tests/testthat/test_context.R b/R/pkg/inst/tests/testthat/test_context.R index 92dbd575c2..3b14a497b4 100644 --- a/R/pkg/inst/tests/testthat/test_context.R +++ b/R/pkg/inst/tests/testthat/test_context.R @@ -24,11 +24,11 @@ test_that("Check masked functions", { func <- lapply(masked, function(x) { capture.output(showMethods(x))[[1]] }) funcSparkROrEmpty <- grepl("\\(package SparkR\\)$|^$", func) maskedBySparkR <- masked[funcSparkROrEmpty] - expect_equal(length(maskedBySparkR), 18) - expect_equal(sort(maskedBySparkR), sort(c("describe", "cov", "filter", "lag", "na.omit", - "predict", "sd", "var", "colnames", "colnames<-", - "intersect", "rank", "rbind", "sample", "subset", - "summary", "table", "transform"))) + namesOfMasked <- c("describe", "cov", "filter", "lag", "na.omit", "predict", "sd", "var", + "colnames", "colnames<-", "intersect", "rank", "rbind", "sample", "subset", + "summary", "transform") + expect_equal(length(maskedBySparkR), length(namesOfMasked)) + expect_equal(sort(maskedBySparkR), sort(namesOfMasked)) # 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" @@ -36,8 +36,9 @@ test_that("Check masked functions", { any(grepl("=\"ANY\"", capture.output(showMethods(x)[-1]))) })) maskedCompletely <- masked[!funcHasAny] - expect_equal(length(maskedCompletely), 4) - expect_equal(sort(maskedCompletely), sort(c("cov", "filter", "sample", "table"))) + namesOfMaskedCompletely <- c("cov", "filter", "sample") + expect_equal(length(maskedCompletely), length(namesOfMaskedCompletely)) + expect_equal(sort(maskedCompletely), sort(namesOfMaskedCompletely)) }) test_that("repeatedly starting and stopping SparkR", { diff --git a/R/pkg/inst/tests/testthat/test_sparkSQL.R b/R/pkg/inst/tests/testthat/test_sparkSQL.R index 6610734cf4..14d40d5066 100644 --- a/R/pkg/inst/tests/testthat/test_sparkSQL.R +++ b/R/pkg/inst/tests/testthat/test_sparkSQL.R @@ -335,7 +335,6 @@ writeLines(mockLinesMapType, mapTypeJsonPath) test_that("Collect DataFrame with complex types", { # ArrayType df <- read.json(sqlContext, complexTypeJsonPath) - ldf <- collect(df) expect_equal(nrow(ldf), 3) expect_equal(ncol(ldf), 3) @@ -490,19 +489,15 @@ test_that("insertInto() on a registered table", { unlink(parquetPath2) }) -test_that("table() returns a new DataFrame", { +test_that("tableToDF() returns a new DataFrame", { df <- read.json(sqlContext, jsonPath) registerTempTable(df, "table1") - tabledf <- table(sqlContext, "table1") + tabledf <- tableToDF(sqlContext, "table1") expect_is(tabledf, "DataFrame") expect_equal(count(tabledf), 3) + tabledf2 <- tableToDF(sqlContext, "table1") + expect_equal(count(tabledf2), 3) dropTempTable(sqlContext, "table1") - - # nolint start - # Test base::table is working - #a <- letters[1:3] - #expect_equal(class(table(a, sample(a))), "table") - # nolint end }) test_that("toRDD() returns an RRDD", { diff --git a/docs/sparkr.md b/docs/sparkr.md index ea81532c61..73e38b8c70 100644 --- a/docs/sparkr.md +++ b/docs/sparkr.md @@ -375,13 +375,6 @@ The following functions are masked by the SparkR package: <td><code>sample</code> in <code>package:base</code></td> <td><code>base::sample(x, size, replace = FALSE, prob = NULL)</code></td> </tr> - <tr> - <td><code>table</code> in <code>package:base</code></td> - <td><code><pre>base::table(..., - exclude = if (useNA == "no") c(NA, NaN), - useNA = c("no", "ifany", "always"), - dnn = list.names(...), deparse.level = 1)</pre></code></td> - </tr> </table> Since part of SparkR is modeled on the `dplyr` package, certain functions in SparkR share the same names with those in `dplyr`. Depending on the load order of the two packages, some functions from the package loaded first are masked by those in the package loaded after. In such case, prefix such calls with the package name, for instance, `SparkR::cume_dist(x)` or `dplyr::cume_dist(x)`. @@ -394,3 +387,7 @@ You can inspect the search path in R with [`search()`](https://stat.ethz.ch/R-ma ## Upgrading From SparkR 1.5.x to 1.6 - Before Spark 1.6, the default mode for writes was `append`. It was changed in Spark 1.6.0 to `error` to match the Scala API. + +## Upgrading From SparkR 1.6.x to 2.0 + + - The method `table` has been removed and replaced by `tableToDF`. |