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
, except
,
explain
, filter
,
first
, gapplyCollect
,
gapply
, getNumPartitions
,
group_by
, head
,
hint
, histogram
,
insertInto
, intersect
,
isLocal
, isStreaming
,
join
, limit
,
localCheckpoint
, merge
,
mutate
, ncol
,
nrow
, persist
,
printSchema
, randomSplit
,
rbind
, registerTempTable
,
rename
, 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)