SparkR (version 2.1.2)

dapplyCollect: dapplyCollect

Description

Apply a function to each partition of a SparkDataFrame and collect the result back to R as a data.frame.

Usage

dapplyCollect(x, func)
# S4 method for SparkDataFrame,`function`
dapplyCollect(x, func)

Arguments

x

A SparkDataFrame

func

A function to be applied to each partition of the SparkDataFrame. func should have only one parameter, to which a R data.frame corresponds to each partition will be passed. The output of func should be a R data.frame.

See Also

dapply

Other SparkDataFrame functions: SparkDataFrame-class, agg, arrange, as.data.frame, attach, cache, coalesce, collect, colnames, coltypes, createOrReplaceTempView, crossJoin, dapply, describe, dim, distinct, dropDuplicates, dropna, drop, dtypes, except, explain, filter, first, gapplyCollect, gapply, getNumPartitions, group_by, head, histogram, insertInto, intersect, isLocal, join, limit, merge, mutate, ncol, nrow, persist, printSchema, randomSplit, rbind, registerTempTable, rename, repartition, sample, saveAsTable, schema, selectExpr, select, showDF, show, storageLevel, str, subset, take, union, unpersist, withColumn, with, write.df, write.jdbc, write.json, write.orc, write.parquet, write.text

Examples

# NOT RUN {
  df <- createDataFrame(iris)
  ldf <- dapplyCollect(df, function(x) { x })

  # filter and add a column
  df <- createDataFrame(
          list(list(1L, 1, "1"), list(2L, 2, "2"), list(3L, 3, "3")),
          c("a", "b", "c"))
  ldf <- dapplyCollect(
           df,
           function(x) {
             y <- x[x[1] > 1, ]
             y <- cbind(y, y[1] + 1L)
           })
  # the result
  #       a b c d
  #       2 2 2 3
  #       3 3 3 4
# }