mutate {SparkR}R Documentation

Mutate

Description

Return a new SparkDataFrame with the specified columns added or replaced.

Usage

## S4 method for signature 'SparkDataFrame'
mutate(.data, ...)

## S4 method for signature 'SparkDataFrame'
transform(`_data`, ...)

mutate(.data, ...)

transform(`_data`, ...)

Arguments

.data

A SparkDataFrame

col

a named argument of the form name = col

Value

A new SparkDataFrame with the new columns added or replaced.

See Also

rename withColumn

Other SparkDataFrame functions: $, $<-, select, select, select,SparkDataFrame,Column-method, select,SparkDataFrame,list-method, selectExpr; SparkDataFrame-class, dataFrame; [, [[, subset; agg, agg, count,GroupedData-method, summarize, summarize; arrange, arrange, arrange, orderBy, orderBy, orderBy, orderBy; as.data.frame, as.data.frame,SparkDataFrame-method; attach, attach,SparkDataFrame-method; cache; collect; colnames, colnames, colnames<-, colnames<-, columns, names, names<-; coltypes, coltypes, coltypes<-, coltypes<-; columns, dtypes, printSchema, schema, schema; count, nrow; dapply, dapply, dapplyCollect, dapplyCollect; describe, describe, describe, summary, summary, summary,AFTSurvivalRegressionModel-method, summary,GeneralizedLinearRegressionModel-method, summary,KMeansModel-method, summary,NaiveBayesModel-method; dim; distinct, unique; dropDuplicates, dropDuplicates; dropna, dropna, fillna, fillna, na.omit, na.omit; drop, drop; dtypes; except, except; explain, explain; filter, filter, where, where; first, first; groupBy, groupBy, group_by, group_by; head; histogram; insertInto, insertInto; intersect, intersect; isLocal, isLocal; join; limit, limit; merge, merge; 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, write.df; selectExpr; showDF, showDF; show, show, show,GroupedData-method, show,WindowSpec-method; str; take; unpersist; withColumn, withColumn; write.jdbc, write.jdbc; write.json, write.json; write.text, write.text

Examples

## Not run: 
sc <- sparkR.init()
sqlContext <- sparkRSQL.init(sc)
path <- "path/to/file.json"
df <- read.json(sqlContext, path)
newDF <- mutate(df, newCol = df$col1 * 5, newCol2 = df$col1 * 2)
names(newDF) # Will contain newCol, newCol2
newDF2 <- transform(df, newCol = df$col1 / 5, newCol2 = df$col1 * 2)

df <- createDataFrame(sqlContext,
                      list(list("Andy", 30L), list("Justin", 19L)), c("name", "age"))
# Replace the "age" column
df1 <- mutate(df, age = df$age + 1L)

## End(Not run)

[Package SparkR version 2.0.0 Index]