| unionByName {SparkR} | R Documentation |
Return a new SparkDataFrame containing the union of rows in this SparkDataFrame
and another SparkDataFrame. This is different from union function, and both
UNION ALL and UNION DISTINCT in SQL as column positions are not taken
into account. Input SparkDataFrames can have different data types in the schema.
unionByName(x, y) ## S4 method for signature 'SparkDataFrame,SparkDataFrame' unionByName(x, y)
x |
A SparkDataFrame |
y |
A SparkDataFrame |
Note: This does not remove duplicate rows across the two SparkDataFrames. This function resolves columns by name (not by position).
A SparkDataFrame containing the result of the union.
unionByName since 2.3.0
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,
mutate, ncol,
nrow, persist,
printSchema, randomSplit,
rbind, rename,
repartitionByRange,
repartition, rollup,
sample, saveAsTable,
schema, selectExpr,
select, showDF,
show, storageLevel,
str, subset,
summary, take,
toJSON, unionAll,
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 df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
##D df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
##D head(unionByName(df1, df2))
## End(Not run)