| 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)