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Showing content from https://spark.apache.org/docs/latest/api/R/reference/attach.html below:

Attach SparkDataFrame to R search path — attach,SparkDataFrame-method • SparkR

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 class '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

detach

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(), unpivot(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

if (FALSE) { # \dontrun{
attach(irisDf)
summary(Sepal_Width)
} # }

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