rollup {SparkR} | R Documentation |
Create a multi-dimensional rollup for the SparkDataFrame using the specified columns.
rollup(x, ...) ## S4 method for signature 'SparkDataFrame' rollup(x, ...)
x |
a SparkDataFrame. |
... |
character name(s) or Column(s) to group on. |
If grouping expression is missing rollup
creates a single global aggregate and is
equivalent to direct application of agg.
A GroupedData.
rollup since 2.3.0
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
, sample
,
saveAsTable
, schema
,
selectExpr
, select
,
showDF
, show
,
storageLevel
, str
,
subset
, summary
,
take
, toJSON
,
unionAll
, unionByName
,
union
, unpersist
,
withColumn
, withWatermark
,
with
, write.df
,
write.jdbc
, write.json
,
write.orc
, write.parquet
,
write.stream
, write.text
## Not run:
##D df <- createDataFrame(mtcars)
##D mean(rollup(df, "cyl", "gear", "am"), "mpg")
##D
##D # Following calls are equivalent
##D agg(rollup(df), mean(df$mpg))
##D agg(df, mean(df$mpg))
## End(Not run)