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 SparkDataFrame
attach(what, pos = 2L,
name = deparse(substitute(what), backtick = FALSE), warn.conflicts = TRUE)(SparkDataFrame) The SparkDataFrame to attach
(integer) Specify position in search() where to attach.
(character) Name to use for the attached SparkDataFrame. Names starting with package: are reserved for library.
(logical) If TRUE, warnings are printed about conflicts from attaching the database, unless that SparkDataFrame contains an object
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, 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, with,
write.df, write.jdbc,
write.json, write.orc,
write.parquet, write.stream,
write.text
# NOT RUN {
attach(irisDf)
summary(Sepal_Width)
# }
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