toJSON {SparkR} | R Documentation |
Converts a SparkDataFrame into a SparkDataFrame of JSON string.
Each row is turned into a JSON document with columns as different fields.
The returned SparkDataFrame has a single character column with the name value
## S4 method for signature 'SparkDataFrame' toJSON(x)
x |
a SparkDataFrame |
a SparkDataFrame
toJSON since 2.2.0
Other SparkDataFrame functions: SparkDataFrame-class
,
agg
, alias
,
arrange
, as.data.frame
,
attach,SparkDataFrame-method
,
broadcast
, cache
,
checkpoint
, coalesce
,
collect
, colnames
,
coltypes
,
createOrReplaceTempView
,
crossJoin
, cube
,
dapplyCollect
, dapply
,
describe
, dim
,
distinct
, dropDuplicates
,
dropna
, drop
,
dtypes
, exceptAll
,
except
, explain
,
filter
, first
,
gapplyCollect
, gapply
,
getNumPartitions
, group_by
,
head
, hint
,
histogram
, insertInto
,
intersectAll
, intersect
,
isLocal
, isStreaming
,
join
, limit
,
localCheckpoint
, merge
,
mutate
, ncol
,
nrow
, persist
,
printSchema
, randomSplit
,
rbind
, rename
,
repartitionByRange
,
repartition
, rollup
,
sample
, saveAsTable
,
schema
, selectExpr
,
select
, showDF
,
show
, storageLevel
,
str
, subset
,
summary
, take
,
unionAll
, unionByName
,
union
, unpersist
,
withColumn
, withWatermark
,
with
, write.df
,
write.jdbc
, write.json
,
write.orc
, write.parquet
,
write.stream
, write.text
## Not run:
##D sparkR.session()
##D path <- "path/to/file.parquet"
##D df <- read.parquet(path)
##D df_json <- toJSON(df)
## End(Not run)