group_by {SparkR} | R Documentation |
Groups the SparkDataFrame using the specified columns, so we can run aggregation on them.
group_by(x, ...) groupBy(x, ...) ## S4 method for signature 'SparkDataFrame' groupBy(x, ...) ## S4 method for signature 'SparkDataFrame' group_by(x, ...)
x |
a SparkDataFrame |
a GroupedData
GroupedData
Other SparkDataFrame functions: SparkDataFrame-class
,
[[
, agg
,
arrange
, as.data.frame
,
attach
, cache
,
collect
, colnames
,
coltypes
, columns
,
count
, dapply
,
describe
, dim
,
distinct
, dropDuplicates
,
dropna
, drop
,
dtypes
, except
,
explain
, filter
,
first
, head
,
histogram
, insertInto
,
intersect
, isLocal
,
join
, limit
,
merge
, mutate
,
ncol
, persist
,
printSchema
,
registerTempTable
, rename
,
repartition
, sample
,
saveAsTable
, selectExpr
,
select
, showDF
,
show
, str
,
take
, unionAll
,
unpersist
, withColumn
,
write.df
, write.jdbc
,
write.json
, write.parquet
,
write.text
## Not run:
##D # Compute the average for all numeric columns grouped by department.
##D avg(groupBy(df, "department"))
##D
##D # Compute the max age and average salary, grouped by department and gender.
##D agg(groupBy(df, "department", "gender"), salary="avg", "age" -> "max")
## End(Not run)