| join {SparkR} | R Documentation |
Joins two SparkDataFrames based on the given join expression.
## S4 method for signature 'SparkDataFrame,SparkDataFrame' join(x, y, joinExpr = NULL, joinType = NULL)
x |
A SparkDataFrame |
y |
A SparkDataFrame |
joinExpr |
(Optional) The expression used to perform the join. joinExpr must be a Column expression. If joinExpr is omitted, the default, inner join is attempted and an error is thrown if it would be a Cartesian Product. For Cartesian join, use crossJoin instead. |
joinType |
The type of join to perform, default 'inner'. Must be one of: 'inner', 'cross', 'outer', 'full', 'full_outer', 'left', 'left_outer', 'right', 'right_outer', 'left_semi', or 'left_anti'. |
A SparkDataFrame containing the result of the join operation.
join since 1.4.0
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,
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:
##D sparkR.session()
##D df1 <- read.json(path)
##D df2 <- read.json(path2)
##D join(df1, df2, df1$col1 == df2$col2) # Performs an inner join based on expression
##D join(df1, df2, df1$col1 == df2$col2, "right_outer")
##D join(df1, df2) # Attempts an inner join
## End(Not run)