| 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, except,
explain, filter,
first, gapplyCollect,
gapply, getNumPartitions,
group_by, head,
hint, histogram,
insertInto, intersect,
isLocal, isStreaming,
join, limit,
localCheckpoint, merge,
mutate, ncol,
nrow, persist,
printSchema, randomSplit,
rbind, registerTempTable,
rename, 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)