| attach,SparkDataFrame-method {SparkR} | R Documentation |
The specified SparkDataFrame is attached to the R search path. This means that the SparkDataFrame is searched by R when evaluating a variable, so columns in the SparkDataFrame can be accessed by simply giving their names.
## S4 method for signature 'SparkDataFrame'
attach(
what,
pos = 2L,
name = paste(deparse(substitute(what), backtick = FALSE), collapse = " "),
warn.conflicts = TRUE
)
what |
(SparkDataFrame) The SparkDataFrame to attach |
pos |
(integer) Specify position in search() where to attach. |
name |
(character) Name to use for the attached SparkDataFrame. Names starting with package: are reserved for library. |
warn.conflicts |
(logical) If TRUE, warnings are printed about conflicts from attaching the database, unless that SparkDataFrame contains an object |
attach since 1.6.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
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(),
unionAll(),
unionByName(),
union(),
unpersist(),
withColumn(),
withWatermark(),
with(),
write.df(),
write.jdbc(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
## Not run:
##D attach(irisDf)
##D summary(Sepal_Width)
## End(Not run)