pyspark.sql.DataFrame.intersectAll¶

DataFrame.intersectAll(other)[source]¶

Return a new DataFrame containing rows in both this DataFrame and another DataFrame while preserving duplicates.

This is equivalent to INTERSECT ALL in SQL. >>> df1 = spark.createDataFrame([(“a”, 1), (“a”, 1), (“b”, 3), (“c”, 4)], [“C1”, “C2”]) >>> df2 = spark.createDataFrame([(“a”, 1), (“a”, 1), (“b”, 3)], [“C1”, “C2”])

>>> df1.intersectAll(df2).sort("C1", "C2").show()
+---+---+
| C1| C2|
+---+---+
|  a|  1|
|  a|  1|
|  b|  3|
+---+---+

Also as standard in SQL, this function resolves columns by position (not by name).

New in version 2.4.

pyspark.sql.DataFrame.intersect pyspark.sql.DataFrame.isLocal