| 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)