| 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,
cache, coalesce,
collect, colnames,
coltypes,
createOrReplaceTempView,
crossJoin, dapplyCollect,
dapply, describe,
dim, distinct,
dropDuplicates, dropna,
drop, dtypes,
except, explain,
filter, first,
gapplyCollect, gapply,
getNumPartitions, head,
histogram, insertInto,
intersect, isLocal,
join, limit,
merge, mutate,
ncol, nrow,
persist, printSchema,
randomSplit, rbind,
registerTempTable, rename,
repartition, sample,
saveAsTable, schema,
selectExpr, select,
showDF, show,
storageLevel, str,
subset, take,
union, unpersist,
withColumn, with,
write.df, write.jdbc,
write.json, write.orc,
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)