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author | hyukjinkwon <gurwls223@gmail.com> | 2017-03-14 19:51:25 -0700 |
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committer | Felix Cheung <felixcheung@apache.org> | 2017-03-14 19:51:25 -0700 |
commit | d1f6c64c4b763c05d6d79ae5497f298dc3835f3e (patch) | |
tree | 3212b7cef66bde23763bba7358f7560a973d8beb | |
parent | 8fb2a02e2ce6832e3d9338a7d0148dfac9fa24c2 (diff) | |
download | spark-d1f6c64c4b763c05d6d79ae5497f298dc3835f3e.tar.gz spark-d1f6c64c4b763c05d6d79ae5497f298dc3835f3e.tar.bz2 spark-d1f6c64c4b763c05d6d79ae5497f298dc3835f3e.zip |
[SPARK-19828][R] Support array type in from_json in R
## What changes were proposed in this pull request?
Since we could not directly define the array type in R, this PR proposes to support array types in R as string types that are used in `structField` as below:
```R
jsonArr <- "[{\"name\":\"Bob\"}, {\"name\":\"Alice\"}]"
df <- as.DataFrame(list(list("people" = jsonArr)))
collect(select(df, alias(from_json(df$people, "array<struct<name:string>>"), "arrcol")))
```
prints
```R
arrcol
1 Bob, Alice
```
## How was this patch tested?
Unit tests in `test_sparkSQL.R`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #17178 from HyukjinKwon/SPARK-19828.
-rw-r--r-- | R/pkg/R/functions.R | 12 | ||||
-rw-r--r-- | R/pkg/inst/tests/testthat/test_sparkSQL.R | 12 | ||||
-rw-r--r-- | sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala | 2 |
3 files changed, 23 insertions, 3 deletions
diff --git a/R/pkg/R/functions.R b/R/pkg/R/functions.R index edf2bcf8fd..9867f2d5b7 100644 --- a/R/pkg/R/functions.R +++ b/R/pkg/R/functions.R @@ -2437,6 +2437,7 @@ setMethod("date_format", signature(y = "Column", x = "character"), #' #' @param x Column containing the JSON string. #' @param schema a structType object to use as the schema to use when parsing the JSON string. +#' @param asJsonArray indicating if input string is JSON array of objects or a single object. #' @param ... additional named properties to control how the json is parsed, accepts the same #' options as the JSON data source. #' @@ -2452,11 +2453,18 @@ setMethod("date_format", signature(y = "Column", x = "character"), #'} #' @note from_json since 2.2.0 setMethod("from_json", signature(x = "Column", schema = "structType"), - function(x, schema, ...) { + function(x, schema, asJsonArray = FALSE, ...) { + if (asJsonArray) { + jschema <- callJStatic("org.apache.spark.sql.types.DataTypes", + "createArrayType", + schema$jobj) + } else { + jschema <- schema$jobj + } options <- varargsToStrEnv(...) jc <- callJStatic("org.apache.spark.sql.functions", "from_json", - x@jc, schema$jobj, options) + x@jc, jschema, options) column(jc) }) diff --git a/R/pkg/inst/tests/testthat/test_sparkSQL.R b/R/pkg/inst/tests/testthat/test_sparkSQL.R index 9735fe3201..f7081cb1d4 100644 --- a/R/pkg/inst/tests/testthat/test_sparkSQL.R +++ b/R/pkg/inst/tests/testthat/test_sparkSQL.R @@ -1364,6 +1364,18 @@ test_that("column functions", { # check for unparseable df <- as.DataFrame(list(list("a" = ""))) expect_equal(collect(select(df, from_json(df$a, schema)))[[1]][[1]], NA) + + # check if array type in string is correctly supported. + jsonArr <- "[{\"name\":\"Bob\"}, {\"name\":\"Alice\"}]" + df <- as.DataFrame(list(list("people" = jsonArr))) + schema <- structType(structField("name", "string")) + arr <- collect(select(df, alias(from_json(df$people, schema, asJsonArray = TRUE), "arrcol"))) + expect_equal(ncol(arr), 1) + expect_equal(nrow(arr), 1) + expect_is(arr[[1]][[1]], "list") + expect_equal(length(arr$arrcol[[1]]), 2) + expect_equal(arr$arrcol[[1]][[1]]$name, "Bob") + expect_equal(arr$arrcol[[1]][[2]]$name, "Alice") }) test_that("column binary mathfunctions", { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala index a4c5bf756c..c77328690d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala @@ -81,7 +81,7 @@ private[sql] object SQLUtils extends Logging { new JavaSparkContext(spark.sparkContext) } - def createStructType(fields : Seq[StructField]): StructType = { + def createStructType(fields: Seq[StructField]): StructType = { StructType(fields) } |