coltypes {SparkR}R Documentation

coltypes

Description

Get column types of a DataFrame

Set the column types of a DataFrame.

Usage

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

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

coltypes(x)

coltypes(x) <- value

Arguments

x

A SparkSQL DataFrame

value

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

x

A SparkSQL DataFrame

Value

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

See Also

Other DataFrame functions: $, $<-, select, select, select,DataFrame,Column-method, select,DataFrame,list-method, selectExpr; DataFrame-class, dataFrame, groupedData; [, [, [[, subset; agg, agg, count,GroupedData-method, summarize, summarize; arrange, arrange, arrange, orderBy, orderBy; as.data.frame, as.data.frame,DataFrame-method; attach, attach,DataFrame-method; cache; collect; colnames, colnames, colnames<-, colnames<-, columns, names, names<-; columns, dtypes, printSchema, schema, schema; count, nrow; describe, describe, describe, summary, summary, summary,PipelineModel-method; dim; distinct, unique; dropna, dropna, fillna, fillna, na.omit, na.omit; dtypes; except, except; explain, explain; filter, filter, where, where; first, first; groupBy, groupBy, group_by, group_by; head; insertInto, insertInto; intersect, intersect; isLocal, isLocal; join; limit, limit; merge, merge; mutate, mutate, transform; ncol; persist; printSchema; rbind, rbind, unionAll, unionAll; registerTempTable, registerTempTable; rename, rename, withColumnRenamed, withColumnRenamed; repartition; sample, sample, sample_frac, sample_frac; saveAsParquetFile, saveAsParquetFile, write.parquet, write.parquet; saveAsTable, saveAsTable; saveDF, saveDF, write.df, write.df; selectExpr; showDF, showDF; show, show, show,GroupedData-method; take; transform, withColumn, withColumn; unpersist; write.json, write.json

Examples

## Not run: 
##D irisDF <- createDataFrame(sqlContext, iris)
##D coltypes(irisDF)
## End(Not run)
## Not run: 
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D path <- "path/to/file.json"
##D df <- read.json(sqlContext, path)
##D coltypes(df) <- c("character", "integer")
##D coltypes(df) <- c(NA, "numeric")
## End(Not run)

[Package SparkR version 1.6.0 Index]