as.data.frame {SparkR} | R Documentation |
This function downloads the contents of a SparkDataFrame into an R's data.frame. Since data.frames are held in memory, ensure that you have enough memory in your system to accommodate the contents.
as.data.frame(x, row.names = NULL, optional = FALSE, ...) ## S4 method for signature 'SparkDataFrame' as.data.frame(x, row.names = NULL, optional = FALSE, ...)
x |
a SparkDataFrame. |
row.names |
|
optional |
If |
... |
additional arguments to pass to base::as.data.frame. |
A data.frame.
as.data.frame since 1.6.0
Other SparkDataFrame functions: SparkDataFrame-class
,
agg
, arrange
,
attach
, cache
,
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
, histogram
,
insertInto
, intersect
,
isLocal
, join
,
limit
, merge
,
mutate
, ncol
,
nrow
, persist
,
printSchema
, randomSplit
,
rbind
, registerTempTable
,
rename
, repartition
,
sample
, saveAsTable
,
schema
, selectExpr
,
select
, showDF
,
show
, storageLevel
,
str
, subset
,
take
, union
,
unpersist
, withColumn
,
with
, write.df
,
write.jdbc
, write.json
,
write.orc
, write.parquet
,
write.text
## Not run:
##D
##D irisDF <- createDataFrame(iris)
##D df <- as.data.frame(irisDF[irisDF$Species == "setosa", ])
## End(Not run)