intersectAll

Return a new SparkDataFrame containing rows in both this SparkDataFrame and another SparkDataFrame while preserving the duplicates. This is equivalent to INTERSECT ALL in SQL. Also as standard in SQL, this function resolves columns by position (not by name).

Usage

intersectAll(x, y)

# S4 method for class 'SparkDataFrame,SparkDataFrame'
intersectAll(x, y)

Arguments

x

a SparkDataFrame.

y

a SparkDataFrame.

Value

A SparkDataFrame containing the result of the intersect all operation.

Note

intersectAll since 2.4.0

See also

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), arrange(), as.data.frame(), attach,SparkDataFrame-method, broadcast(), cache(), checkpoint(), coalesce(), collect(), colnames(), coltypes(), createOrReplaceTempView(), crossJoin(), cube(), dapply(), dapplyCollect(), describe(), dim(), distinct(), drop(), dropDuplicates(), dropna(), dtypes(), except(), exceptAll(), explain(), filter(), first(), gapply(), gapplyCollect(), getNumPartitions(), group_by(), head(), hint(), histogram(), insertInto(), intersect(), isLocal(), isStreaming(), join(), limit(), localCheckpoint(), merge(), mutate(), ncol(), nrow(), persist(), printSchema(), randomSplit(), rbind(), rename(), repartition(), repartitionByRange(), rollup(), sample(), saveAsTable(), schema(), select(), selectExpr(), show(), showDF(), storageLevel(), str(), subset(), summary(), take(), toJSON(), union(), unionAll(), unionByName(), unpersist(), unpivot(), with(), withColumn(), withWatermark(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

if (FALSE) { # \dontrun{
sparkR.session()
df1 <- read.json(path)
df2 <- read.json(path2)
intersectAllDF <- intersectAll(df1, df2)
} # }