agg {SparkR} | R Documentation |
Aggregates on the entire SparkDataFrame without groups. The resulting SparkDataFrame will also contain the grouping columns.
Compute aggregates by specifying a list of columns
agg(x, ...) summarize(x, ...) ## S4 method for signature 'GroupedData' agg(x, ...) ## S4 method for signature 'GroupedData' summarize(x, ...) ## S4 method for signature 'SparkDataFrame' agg(x, ...) ## S4 method for signature 'SparkDataFrame' summarize(x, ...)
x |
a SparkDataFrame or GroupedData. |
... |
further arguments to be passed to or from other methods. |
df2 <- agg(df, <column> = <aggFunction>) df2 <- agg(df, newColName = aggFunction(column))
A SparkDataFrame.
agg since 1.4.0
summarize since 1.4.0
agg since 1.4.0
summarize since 1.4.0
Other SparkDataFrame functions: SparkDataFrame-class
,
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
, rollup
,
sample
, 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 df2 <- agg(df, age = "sum") # new column name will be created as 'SUM(age#0)'
##D df3 <- agg(df, ageSum = sum(df$age)) # Creates a new column named ageSum
##D df4 <- summarize(df, ageSum = max(df$age))
## End(Not run)