| 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)