Save the contents of SparkDataFrame as a JSON file
write.json.RdSave the contents of a SparkDataFrame as a JSON file ( JSON Lines text format or newline-delimited JSON). Files written out with this method can be read back in as a SparkDataFrame using read.json().
Usage
write.json(x, path, ...)
# S4 method for SparkDataFrame,character
write.json(x, path, mode = "error", ...)Arguments
- x
A SparkDataFrame
- path
The directory where the file is saved
- ...
additional argument(s) passed to the method. You can find the JSON-specific options for writing JSON files in https://spark.apache.org/docs/latest/sql-data-sources-json.html#data-source-optionData Source Option in the version you use.
- mode
one of 'append', 'overwrite', 'error', 'errorifexists', 'ignore' save mode (it is 'error' by default)
See also
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(),
toJSON(),
unionAll(),
unionByName(),
union(),
unpersist(),
unpivot(),
withColumn(),
withWatermark(),
with(),
write.df(),
write.jdbc(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
Examples
if (FALSE) {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
write.json(df, "/tmp/sparkr-tmp/")
}