| 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, arrange,
as.data.frame,
attach,SparkDataFrame-method,
cache, checkpoint,
coalesce, collect,
colnames, coltypes,
createOrReplaceTempView,
crossJoin, 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, merge,
mutate, ncol,
nrow, persist,
printSchema, randomSplit,
rbind, registerTempTable,
rename, repartition,
sample, saveAsTable,
schema, selectExpr,
select, showDF,
show, storageLevel,
str, subset,
take, toJSON,
union, unpersist,
withColumn, 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)