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Union two or more SparkDataFrames. This is equivalent to UNION ALL
in SQL.
rbind(..., deparse.level = 1)# S4 method for SparkDataFrame
rbind(x, ..., deparse.level = 1)
additional SparkDataFrame(s).
currently not used (put here to match the signature of the base implementation).
a SparkDataFrame.
A SparkDataFrame containing the result of the union.
Note: This does not remove duplicate rows across the two SparkDataFrames.
Other SparkDataFrame functions: SparkDataFrame-class
,
agg
, arrange
,
as.data.frame
, attach
,
cache
, coalesce
,
collect
, colnames
,
coltypes
,
createOrReplaceTempView
,
crossJoin
, dapplyCollect
,
dapply
, describe
,
dim
, distinct
,
dropDuplicates
, dropna
,
drop
, dtypes
,
except
, explain
,
filter
, first
,
gapplyCollect
, gapply
,
getNumPartitions
, group_by
,
head
, histogram
,
insertInto
, intersect
,
isLocal
, join
,
limit
, merge
,
mutate
, ncol
,
nrow
, persist
,
printSchema
, randomSplit
,
registerTempTable
, rename
,
repartition
, sample
,
saveAsTable
, schema
,
selectExpr
, select
,
showDF
, show
,
storageLevel
, str
,
subset
, take
,
union
, unpersist
,
withColumn
, with
,
write.df
, write.jdbc
,
write.json
, write.orc
,
write.parquet
, write.text
# NOT RUN {
sparkR.session()
unions <- rbind(df, df2, df3, df4)
# }
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