Return a new SparkDataFrame containing rows in this SparkDataFrame
but not in another SparkDataFrame while preserving the duplicates.
This is equivalent to EXCEPT ALL
in SQL. Also as standard in
SQL, this function resolves columns by position (not by name).
exceptAll(x, y)# S4 method for SparkDataFrame,SparkDataFrame
exceptAll(x, y)
a SparkDataFrame.
a SparkDataFrame.
A SparkDataFrame containing the result of the except all operation.
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()
,
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()
,
unionByName()
,
union()
,
unpersist()
,
withColumn()
,
withWatermark()
,
with()
,
write.df()
,
write.jdbc()
,
write.json()
,
write.orc()
,
write.parquet()
,
write.stream()
,
write.text()
# NOT RUN {
sparkR.session()
df1 <- read.json(path)
df2 <- read.json(path2)
exceptAllDF <- exceptAll(df1, df2)
# }
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