| 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, 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, mutate,
ncol, nrow,
persist, printSchema,
randomSplit, rbind,
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:
##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)