| with {SparkR} | R Documentation |
Evaluate a R expression in an environment constructed from a SparkDataFrame with() allows access to columns of a SparkDataFrame by simply referring to their name. It appends every column of a SparkDataFrame into a new environment. Then, the given expression is evaluated in this new environment.
with(data, expr, ...) ## S4 method for signature 'SparkDataFrame' with(data, expr, ...)
data |
(SparkDataFrame) SparkDataFrame to use for constructing an environment. |
expr |
(expression) Expression to evaluate. |
... |
arguments to be passed to future methods. |
with since 1.6.0
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(),
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(),
write.df(),
write.jdbc(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
## Not run:
##D with(irisDf, nrow(Sepal_Width))
## End(Not run)