| write.df {SparkR} | R Documentation |
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.
write.df(df, path = NULL, ...) saveDF(df, path, source = NULL, mode = "error", ...) write.df(df, path = NULL, ...) ## S4 method for signature 'SparkDataFrame' write.df(df, path = NULL, source = NULL, mode = "error", ...) ## S4 method for signature 'SparkDataFrame,character' saveDF(df, path, source = NULL, mode = "error", ...)
df |
a SparkDataFrame. |
path |
a name for the table. |
... |
additional argument(s) passed to the method. |
source |
a name for external data source. |
mode |
one of 'append', 'overwrite', 'error', 'ignore' save mode (it is 'error' by default) |
Additionally, mode is used to specify the behavior of the save operation when data already exists in the data source. There are four modes:
append: Contents of this SparkDataFrame are expected to be appended to existing data.
overwrite: Existing data is expected to be overwritten by the contents of this SparkDataFrame.
error: An exception is expected to be thrown.
ignore: The save operation is expected to not save the contents of the SparkDataFrame and to not change the existing data.
write.df since 1.4.0
saveDF since 1.4.0
Other SparkDataFrame functions: SparkDataFrame-class,
agg, arrange,
as.data.frame,
attach,SparkDataFrame-method,
cache, checkpoint,
coalesce, collect,
colnames, coltypes,
createOrReplaceTempView,
crossJoin, dapplyCollect,
dapply, describe,
dim, distinct,
dropDuplicates, dropna,
drop, dtypes,
except, explain,
filter, first,
gapplyCollect, gapply,
getNumPartitions, group_by,
head, hint,
histogram, insertInto,
intersect, isLocal,
isStreaming, join,
limit, merge,
mutate, ncol,
nrow, persist,
printSchema, randomSplit,
rbind, registerTempTable,
rename, repartition,
sample, saveAsTable,
schema, selectExpr,
select, showDF,
show, storageLevel,
str, subset,
take, toJSON,
union, unpersist,
withColumn, with,
write.jdbc, write.json,
write.orc, write.parquet,
write.stream, write.text
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D write.df(df, "myfile", "parquet", "overwrite")
##D saveDF(df, parquetPath2, "parquet", mode = saveMode, mergeSchema = mergeSchema)
## End(Not run)