unionByName
Return a new SparkDataFrame containing the union of rows, matched by column names
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.
Usage
unionByName(x, y)# S4 method for SparkDataFrame,SparkDataFrame
unionByName(x, y)
Arguments
- x
A SparkDataFrame
- y
A SparkDataFrame
Details
Note: This does not remove duplicate rows across the two SparkDataFrames. This function resolves columns by name (not by position).
Value
A SparkDataFrame containing the result of the union.
Note
unionByName since 2.3.0
See Also
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()
,
union()
,
unpersist()
,
withColumn()
,
withWatermark()
,
with()
,
write.df()
,
write.jdbc()
,
write.json()
,
write.orc()
,
write.parquet()
,
write.stream()
,
write.text()
Examples
# NOT RUN {
sparkR.session()
df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
head(unionByName(df1, df2))
# }