merge {SparkR} | R Documentation |
Merges two data frames
merge(x, y, ...) ## S4 method for signature 'SparkDataFrame,SparkDataFrame' merge(x, y, by = intersect(names(x), names(y)), by.x = by, by.y = by, all = FALSE, all.x = all, all.y = all, sort = TRUE, suffixes = c("_x", "_y"), ...)
x |
the first data frame to be joined. |
y |
the second data frame to be joined. |
... |
additional argument(s) passed to the method. |
by |
a character vector specifying the join columns. If by is not
specified, the common column names in |
by.x |
a character vector specifying the joining columns for x. |
by.y |
a character vector specifying the joining columns for y. |
all |
a boolean value setting |
all.x |
a boolean value indicating whether all the rows in x should be including in the join. |
all.y |
a boolean value indicating whether all the rows in y should be including in the join. |
sort |
a logical argument indicating whether the resulting columns should be sorted. |
suffixes |
a string vector of length 2 used to make colnames of
|
If all.x and all.y are set to FALSE, a natural join will be returned. If all.x is set to TRUE and all.y is set to FALSE, a left outer join will be returned. If all.x is set to FALSE and all.y is set to TRUE, a right outer join will be returned. If all.x and all.y are set to TRUE, a full outer join will be returned.
merge since 1.5.0
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
, 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:
##D sparkR.session()
##D df1 <- read.json(path)
##D df2 <- read.json(path2)
##D merge(df1, df2) # Performs an inner join by common columns
##D merge(df1, df2, by = "col1") # Performs an inner join based on expression
##D merge(df1, df2, by.x = "col1", by.y = "col2", all.y = TRUE)
##D merge(df1, df2, by.x = "col1", by.y = "col2", all.x = TRUE)
##D merge(df1, df2, by.x = "col1", by.y = "col2", all.x = TRUE, all.y = TRUE)
##D merge(df1, df2, by.x = "col1", by.y = "col2", all = TRUE, sort = FALSE)
##D merge(df1, df2, by = "col1", all = TRUE, suffixes = c("-X", "-Y"))
##D merge(df1, df2, by = NULL) # Performs a Cartesian join
## End(Not run)