[SPARK-8085] [SPARKR] Support user-specified schema in read.df

cc davies sun-rui

Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>

Closes #6620 from shivaram/sparkr-read-schema and squashes the following commits:

16a6726 [Shivaram Venkataraman] Fix loadDF to pass schema Also add a unit test
a229877 [Shivaram Venkataraman] Use wrapper function to DataFrameReader
ee70ba8 [Shivaram Venkataraman] Support user-specified schema in read.df

R/pkg/R/SQLContext.R

@@ -452,7 +452,7 @@ dropTempTable <- function(sqlContext, tableName) {
 #' df <- read.df(sqlContext, "path/to/file.json", source = "json")
 #' }
 
-read.df <- function(sqlContext, path = NULL, source = NULL, ...) {
+read.df <- function(sqlContext, path = NULL, source = NULL, schema = NULL, ...) {
   options <- varargsToEnv(...)
   if (!is.null(path)) {
     options[['path']] <- path
@@ -462,15 +462,21 @@ read.df <- function(sqlContext, path = NULL, source = NULL, ...) {
     source <- callJMethod(sqlContext, "getConf", "spark.sql.sources.default",
                           "org.apache.spark.sql.parquet")
   }
-  sdf <- callJMethod(sqlContext, "load", source, options)
+  if (!is.null(schema)) {
+    stopifnot(class(schema) == "structType")
+    sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "loadDF", sqlContext, source,
+                       schema$jobj, options)
+  } else {
+    sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "loadDF", sqlContext, source, options)
+  }
   dataFrame(sdf)
 }
 
 #' @aliases loadDF
 #' @export
 
-loadDF <- function(sqlContext, path = NULL, source = NULL, ...) {
-  read.df(sqlContext, path, source, ...)
+loadDF <- function(sqlContext, path = NULL, source = NULL, schema = NULL, ...) {
+  read.df(sqlContext, path, source, schema, ...)
 }
 
 #' Create an external table

R/pkg/inst/tests/test_sparkSQL.R

@@ -504,6 +504,19 @@ test_that("read.df() from json file", {
   df <- read.df(sqlContext, jsonPath, "json")
   expect_true(inherits(df, "DataFrame"))
   expect_true(count(df) == 3)
+
+  # Check if we can apply a user defined schema
+  schema <- structType(structField("name", type = "string"),
+                       structField("age", type = "double"))
+
+  df1 <- read.df(sqlContext, jsonPath, "json", schema)
+  expect_true(inherits(df1, "DataFrame"))
+  expect_equal(dtypes(df1), list(c("name", "string"), c("age", "double")))
+
+  # Run the same with loadDF
+  df2 <- loadDF(sqlContext, jsonPath, "json", schema)
+  expect_true(inherits(df2, "DataFrame"))
+  expect_equal(dtypes(df2), list(c("name", "string"), c("age", "double")))
 })
 
 test_that("write.df() as parquet file", {

sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala

@@ -139,4 +139,19 @@ private[r] object SQLUtils {
       case "ignore" => SaveMode.Ignore
     }
   }
+
+  def loadDF(
+      sqlContext: SQLContext,
+      source: String,
+      options: java.util.Map[String, String]): DataFrame = {
+    sqlContext.read.format(source).options(options).load()
+  }
+
+  def loadDF(
+      sqlContext: SQLContext,
+      source: String,
+      schema: StructType,
+      options: java.util.Map[String, String]): DataFrame = {
+    sqlContext.read.format(source).schema(schema).options(options).load()
+  }
 }