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| author | hyukjinkwon <gurwls223@gmail.com> | 2017-04-17 09:04:24 -0700 |
|---|---|---|
| committer | Felix Cheung <felixcheung@apache.org> | 2017-04-17 09:04:24 -0700 |
| commit | 24f09b39c7b947e52fda952676d5114c2540e732 (patch) | |
| tree | c44e855041a0cea70c4fccc05627945acfce2a56 | |
| parent | 86d251c58591278a7c88745a1049e7a41db11964 (diff) | |
| download | spark-24f09b39c7b947e52fda952676d5114c2540e732.tar.gz spark-24f09b39c7b947e52fda952676d5114c2540e732.tar.bz2 spark-24f09b39c7b947e52fda952676d5114c2540e732.zip | |
[SPARK-19828][R][FOLLOWUP] Rename asJsonArray to as.json.array in from_json function in R
## What changes were proposed in this pull request?
This was suggested to be `as.json.array` at the first place in the PR to SPARK-19828 but we could not do this as the lint check emits an error for multiple dots in the variable names.
After SPARK-20278, now we are able to use `multiple.dots.in.names`. `asJsonArray` in `from_json` function is still able to be changed as 2.2 is not released yet.
So, this PR proposes to rename `asJsonArray` to `as.json.array`.
## How was this patch tested?
Jenkins tests, local tests with `./R/run-tests.sh` and manual `./dev/lint-r`. Existing tests should cover this.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #17653 from HyukjinKwon/SPARK-19828-followup.
| -rw-r--r-- | R/pkg/R/functions.R | 8 | ||||
| -rw-r--r-- | R/pkg/inst/tests/testthat/test_sparkSQL.R | 2 |
2 files changed, 5 insertions, 5 deletions
diff --git a/R/pkg/R/functions.R b/R/pkg/R/functions.R index 449476dec5..c311921fb3 100644 --- a/R/pkg/R/functions.R +++ b/R/pkg/R/functions.R @@ -2438,12 +2438,12 @@ setMethod("date_format", signature(y = "Column", x = "character"), #' from_json #' #' Parses a column containing a JSON string into a Column of \code{structType} with the specified -#' \code{schema} or array of \code{structType} if \code{asJsonArray} is set to \code{TRUE}. +#' \code{schema} or array of \code{structType} if \code{as.json.array} is set to \code{TRUE}. #' If the string is unparseable, the Column will contains the value NA. #' #' @param x Column containing the JSON string. #' @param schema a structType object to use as the schema to use when parsing the JSON string. -#' @param asJsonArray indicating if input string is JSON array of objects or a single object. +#' @param as.json.array indicating if input string is JSON array of objects or a single object. #' @param ... additional named properties to control how the json is parsed, accepts the same #' options as the JSON data source. #' @@ -2459,8 +2459,8 @@ setMethod("date_format", signature(y = "Column", x = "character"), #'} #' @note from_json since 2.2.0 setMethod("from_json", signature(x = "Column", schema = "structType"), - function(x, schema, asJsonArray = FALSE, ...) { - if (asJsonArray) { + function(x, schema, as.json.array = FALSE, ...) { + if (as.json.array) { jschema <- callJStatic("org.apache.spark.sql.types.DataTypes", "createArrayType", schema$jobj) diff --git a/R/pkg/inst/tests/testthat/test_sparkSQL.R b/R/pkg/inst/tests/testthat/test_sparkSQL.R index 3fbb618ddf..6a6c9a809a 100644 --- a/R/pkg/inst/tests/testthat/test_sparkSQL.R +++ b/R/pkg/inst/tests/testthat/test_sparkSQL.R @@ -1454,7 +1454,7 @@ test_that("column functions", { jsonArr <- "[{\"name\":\"Bob\"}, {\"name\":\"Alice\"}]" df <- as.DataFrame(list(list("people" = jsonArr))) schema <- structType(structField("name", "string")) - arr <- collect(select(df, alias(from_json(df$people, schema, asJsonArray = TRUE), "arrcol"))) + arr <- collect(select(df, alias(from_json(df$people, schema, as.json.array = TRUE), "arrcol"))) expect_equal(ncol(arr), 1) expect_equal(nrow(arr), 1) expect_is(arr[[1]][[1]], "list") |