rollup

Create a multi-dimensional rollup for the SparkDataFrame using the specified columns.

Usage

rollup(x, ...)

# S4 method for class 'SparkDataFrame'
rollup(x, ...)

Arguments

x

a SparkDataFrame.

...

character name(s) or Column(s) to group on.

Value

A GroupedData.

Details

If grouping expression is missing rollup creates a single global aggregate and is equivalent to direct application of agg.

Note

rollup since 2.3.0

See also

agg, cube, groupBy

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), arrange(), as.data.frame(), attach,SparkDataFrame-method, broadcast(), cache(), checkpoint(), coalesce(), collect(), colnames(), coltypes(), createOrReplaceTempView(), crossJoin(), cube(), dapply(), dapplyCollect(), describe(), dim(), distinct(), drop(), dropDuplicates(), dropna(), dtypes(), except(), exceptAll(), explain(), filter(), first(), gapply(), gapplyCollect(), getNumPartitions(), group_by(), head(), hint(), histogram(), insertInto(), intersect(), intersectAll(), isLocal(), isStreaming(), join(), limit(), localCheckpoint(), merge(), mutate(), ncol(), nrow(), persist(), printSchema(), randomSplit(), rbind(), rename(), repartition(), repartitionByRange(), sample(), saveAsTable(), schema(), select(), selectExpr(), show(), showDF(), storageLevel(), str(), subset(), summary(), take(), toJSON(), union(), unionAll(), unionByName(), unpersist(), unpivot(), with(), withColumn(), withWatermark(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

if (FALSE) { # \dontrun{
df <- createDataFrame(mtcars)
mean(rollup(df, "cyl", "gear", "am"), "mpg")

# Following calls are equivalent
agg(rollup(df), mean(df$mpg))
agg(df, mean(df$mpg))
} # }