Integration with Hive UDFs, UDAFs, and UDTFs
Applies to: Databricks Runtime
Spark SQL supports integration of Hive UDFs, UDAFs, and UDTFs. Similar to Spark UDFs and UDAFs, Hive UDFs work on a single row as input and generate a single row as output, while Hive UDAFs operate on multiple rows and return a single aggregated row as a result. In addition, Hive also supports UDTFs (User Defined Tabular Functions) that act on one row as input and return multiple rows as output. To use Hive UDFs/UDAFs/UTFs, the user should register them in Spark, and then use them in Spark SQL queries.
Examples
Hive has two UDF interfaces: UDF and GenericUDF.
An example below uses GenericUDFAbs derived from GenericUDF
.
-- Register `GenericUDFAbs` and use it in Spark SQL.
-- Note that, if you use your own programmed one, you need to add a JAR containing it
-- into a classpath,
-- e.g., ADD JAR yourHiveUDF.jar;
CREATE TEMPORARY FUNCTION testUDF AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDFAbs';
SELECT * FROM t;
+-----+
|value|
+-----+
| -1.0|
| 2.0|
| -3.0|
+-----+
SELECT testUDF(value) FROM t;
+--------------+
|testUDF(value)|
+--------------+
| 1.0|
| 2.0|
| 3.0|
+--------------+
An example below uses GenericUDTFExplode derived from GenericUDTF.
-- Register `GenericUDTFExplode` and use it in Spark SQL
CREATE TEMPORARY FUNCTION hiveUDTF
AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDTFExplode';
SELECT * FROM t;
+------+
| value|
+------+
|[1, 2]|
|[3, 4]|
+------+
SELECT hiveUDTF(value) FROM t;
+---+
|col|
+---+
| 1|
| 2|
| 3|
| 4|
+---+
Hive has two UDAF interfaces: UDAF and GenericUDAFResolver.
An example below uses GenericUDAFSum derived from GenericUDAFResolver
.
-- Register `GenericUDAFSum` and use it in Spark SQL
CREATE TEMPORARY FUNCTION hiveUDAF
AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum';
SELECT * FROM t;
+---+-----+
|key|value|
+---+-----+
| a| 1|
| a| 2|
| b| 3|
+---+-----+
SELECT key, hiveUDAF(value) FROM t GROUP BY key;
+---+---------------+
|key|hiveUDAF(value)|
+---+---------------+
| b| 3|
| a| 3|
+---+---------------+