| dapply {SparkR} | R Documentation |
Apply a function to each partition of a SparkDataFrame.
dapply(x, func, schema) ## S4 method for signature 'SparkDataFrame,'function',characterOrstructType' dapply(x, func, schema)
x |
A SparkDataFrame |
func |
A function to be applied to each partition of the SparkDataFrame. func should have only one parameter, to which a R data.frame corresponds to each partition will be passed. The output of func should be a R data.frame. |
schema |
The schema of the resulting SparkDataFrame after the function is applied. It must match the output of func. Since Spark 2.3, the DDL-formatted string is also supported for the schema. |
dapply since 2.0.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
colnames(),
coltypes(),
createOrReplaceTempView(),
crossJoin(),
cube(),
dapplyCollect(),
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(),
unionAll(),
unionByName(),
union(),
unpersist(),
withColumn(),
withWatermark(),
with(),
write.df(),
write.jdbc(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
## Not run:
##D df <- createDataFrame(iris)
##D df1 <- dapply(df, function(x) { x }, schema(df))
##D collect(df1)
##D
##D # filter and add a column
##D df <- createDataFrame(
##D list(list(1L, 1, "1"), list(2L, 2, "2"), list(3L, 3, "3")),
##D c("a", "b", "c"))
##D schema <- structType(structField("a", "integer"), structField("b", "double"),
##D structField("c", "string"), structField("d", "integer"))
##D df1 <- dapply(
##D df,
##D function(x) {
##D y <- x[x[1] > 1, ]
##D y <- cbind(y, y[1] + 1L)
##D },
##D schema)
##D
##D # The schema also can be specified in a DDL-formatted string.
##D schema <- "a INT, d DOUBLE, c STRING, d INT"
##D df1 <- dapply(
##D df,
##D function(x) {
##D y <- x[x[1] > 1, ]
##D y <- cbind(y, y[1] + 1L)
##D },
##D schema)
##D
##D collect(df1)
##D # the result
##D # a b c d
##D # 1 2 2 2 3
##D # 2 3 3 3 4
## End(Not run)