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Showing content from https://spark.apache.org/docs/latest/api/R/reference/mutate.html below:

Mutate — mutate • SparkR

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

mutate(.data, ...)

transform(`_data`, ...)

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

# S4 method for class '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

rename withColumn

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(), unpivot(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

if (FALSE) { # \dontrun{
sparkR.session()
path <- "path/to/file.json"
df <- read.json(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(list(list("Andy", 30L), list("Justin", 19L)), c("name", "age"))
# Replace the "age" column
df1 <- mutate(df, age = df$age + 1L)
} # }

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