Load a SparkDataFrame

Returns the dataset in a data source as a SparkDataFrame

Usage

read.df(path = NULL, source = NULL, schema = NULL, na.strings = "NA", ...)

loadDF(path = NULL, source = NULL, schema = NULL, ...)

Arguments

path: The path of files to load
source: The name of external data source
schema: The data schema defined in structType or a DDL-formatted string.
na.strings: Default string value for NA when source is "csv"
...: additional external data source specific named properties.

Value

SparkDataFrame

Details

The data source is specified by the source and a set of options(...). If source is not specified, the default data source configured by "spark.sql.sources.default" will be used.
Similar to R read.csv, when source is "csv", by default, a value of "NA" will be interpreted as NA.

Note

read.df since 1.4.0

loadDF since 1.6.0

Examples

if (FALSE) { # \dontrun{
sparkR.session()
df1 <- read.df("path/to/file.json", source = "json")
schema <- structType(structField("name", "string"),
                     structField("info", "map<string,double>"))
df2 <- read.df(mapTypeJsonPath, "json", schema, multiLine = TRUE)
df3 <- loadDF("data/test_table", "parquet", mergeSchema = "true")
stringSchema <- "name STRING, info MAP<STRING, DOUBLE>"
df4 <- read.df(mapTypeJsonPath, "json", stringSchema, multiLine = TRUE)
} # }