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. |
... |
variable(s) (character names(s) or Column(s)) to group on. |
A GroupedData.
groupBy since 1.4.0
group_by since 1.4.0
Other SparkDataFrame functions: SparkDataFrame-class
,
agg
, arrange
,
as.data.frame
,
attach,SparkDataFrame-method
,
cache
, checkpoint
,
coalesce
, collect
,
colnames
, coltypes
,
createOrReplaceTempView
,
crossJoin
, dapplyCollect
,
dapply
, describe
,
dim
, distinct
,
dropDuplicates
, dropna
,
drop
, dtypes
,
except
, explain
,
filter
, first
,
gapplyCollect
, gapply
,
getNumPartitions
, head
,
hint
, histogram
,
insertInto
, intersect
,
isLocal
, isStreaming
,
join
, limit
,
merge
, mutate
,
ncol
, nrow
,
persist
, printSchema
,
randomSplit
, rbind
,
registerTempTable
, rename
,
repartition
, sample
,
saveAsTable
, schema
,
selectExpr
, select
,
showDF
, show
,
storageLevel
, str
,
subset
, take
,
toJSON
, union
,
unpersist
, withColumn
,
with
, write.df
,
write.jdbc
, write.json
,
write.orc
, write.parquet
,
write.stream
, 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)