withColumn {SparkR} | R Documentation |
Return a new SparkDataFrame by adding a column or replacing the existing column that has the same name.
withColumn(x, colName, col) ## S4 method for signature 'SparkDataFrame,character,Column' withColumn(x, colName, col)
x |
A SparkDataFrame |
colName |
A column name. |
col |
A Column expression. |
A SparkDataFrame with the new column added or the existing column replaced.
Other SparkDataFrame functions: SparkDataFrame-class
,
[[
, agg
,
arrange
, as.data.frame
,
attach
, cache
,
collect
, colnames
,
coltypes
, columns
,
count
, dapply
,
describe
, dim
,
distinct
, dropDuplicates
,
dropna
, drop
,
dtypes
, except
,
explain
, filter
,
first
, group_by
,
head
, histogram
,
insertInto
, intersect
,
isLocal
, join
,
limit
, merge
,
mutate
, ncol
,
persist
, printSchema
,
registerTempTable
, rename
,
repartition
, sample
,
saveAsTable
, selectExpr
,
select
, showDF
,
show
, str
,
take
, unionAll
,
unpersist
, write.df
,
write.jdbc
, write.json
,
write.parquet
, write.text
## Not run:
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D path <- "path/to/file.json"
##D df <- read.json(sqlContext, path)
##D newDF <- withColumn(df, "newCol", df$col1 * 5)
##D # Replace an existing column
##D newDF2 <- withColumn(newDF, "newCol", newDF$col1)
## End(Not run)