sample {SparkR} | R Documentation |
Return a sampled subset of this SparkDataFrame using a random seed. Note: this is not guaranteed to provide exactly the fraction specified of the total count of of the given SparkDataFrame.
sample(x, withReplacement = FALSE, fraction, seed) sample_frac(x, withReplacement = FALSE, fraction, seed) ## S4 method for signature 'SparkDataFrame' sample(x, withReplacement = FALSE, fraction, seed) ## S4 method for signature 'SparkDataFrame' sample_frac(x, withReplacement = FALSE, fraction, seed)
x |
A SparkDataFrame |
withReplacement |
Sampling with replacement or not |
fraction |
The (rough) sample target fraction |
seed |
Randomness seed value. Default is a random seed. |
sample since 1.4.0
sample_frac since 1.4.0
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
, except
,
explain
, filter
,
first
, gapplyCollect
,
gapply
, getNumPartitions
,
group_by
, head
,
hint
, histogram
,
insertInto
, intersect
,
isLocal
, isStreaming
,
join
, limit
,
localCheckpoint
, merge
,
mutate
, ncol
,
nrow
, persist
,
printSchema
, randomSplit
,
rbind
, registerTempTable
,
rename
, repartition
,
rollup
, saveAsTable
,
schema
, selectExpr
,
select
, showDF
,
show
, storageLevel
,
str
, subset
,
summary
, take
,
toJSON
, 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.json"
##D df <- read.json(path)
##D collect(sample(df, fraction = 0.5))
##D collect(sample(df, FALSE, 0.5))
##D collect(sample(df, TRUE, 0.5, seed = 3))
## End(Not run)