coltypes {SparkR}R Documentation

coltypes

Description

Get column types of a SparkDataFrame

Set the column types of a SparkDataFrame.

Usage

coltypes(x)

coltypes(x) <- value

## S4 method for signature 'SparkDataFrame'
coltypes(x)

## S4 replacement method for signature 'SparkDataFrame,character'
coltypes(x) <- value

Arguments

x

A SparkDataFrame

value

A character vector with the target column types for the given SparkDataFrame. Column types can be one of integer, numeric/double, character, logical, or NA to keep that column as-is.

Value

value A character vector with the column types of the given SparkDataFrame

Note

coltypes since 1.6.0

coltypes<- since 1.6.0

See Also

Other SparkDataFrame functions: SparkDataFrame-class, agg, alias, arrange, as.data.frame, attach,SparkDataFrame-method, broadcast, cache, checkpoint, coalesce, collect, colnames, 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, withColumn, withWatermark, with, write.df, write.jdbc, write.json, write.orc, write.parquet, write.stream, write.text

Examples

## Not run: 
##D irisDF <- createDataFrame(iris)
##D coltypes(irisDF) # get column types
## End(Not run)
## Not run: 
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D coltypes(df) <- c("character", "integer") # set column types
##D coltypes(df) <- c(NA, "numeric") # set column types
## End(Not run)

[Package SparkR version 3.0.0 Index]