| mutate {SparkR} | R Documentation |
Return a new SparkDataFrame with the specified columns added or replaced.
mutate(.data, ...)
transform(`_data`, ...)
## S4 method for signature 'SparkDataFrame'
mutate(.data, ...)
## S4 method for signature 'SparkDataFrame'
transform(`_data`, ...)
.data |
a SparkDataFrame. |
... |
additional column argument(s) each in the form name = col. |
_data |
a SparkDataFrame. |
A new SparkDataFrame with the new columns added or replaced.
mutate since 1.4.0
transform since 1.5.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
colnames(),
coltypes(),
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(),
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()
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D newDF <- mutate(df, newCol = df$col1 * 5, newCol2 = df$col1 * 2)
##D names(newDF) # Will contain newCol, newCol2
##D newDF2 <- transform(df, newCol = df$col1 / 5, newCol2 = df$col1 * 2)
##D
##D df <- createDataFrame(list(list("Andy", 30L), list("Justin", 19L)), c("name", "age"))
##D # Replace the "age" column
##D df1 <- mutate(df, age = df$age + 1L)
## End(Not run)