DeveloperGuide Hive UDF
Creating Custom UDFs
First, you need to create a new class that extends UDF, with one or more methods named evaluate.
package
import
import
public
final
class
Lower
extends
UDF {
public
Text evaluate(
final
Text s) {
if
(s ==
null
) {
return
null
; }
return
new
Text(
}
}
|
(Note that there's already a built-in function for this, it's just an easy example).
After compiling your code to a jar, you need to add this to the Hive classpath. See the section below on deploying jars.
Once Hive is started up with your jars in the classpath, the final step is to register your function as described in :
create temporary function my_lower as
'
;
|
Now you can start using it:
hive> select my_lower(title), sum(freq) from titles group by my_lower(title);
...
Ended Job = job_200906231019_0006
OK
cmo
13.0
vp
7.0
|
For a more involved example, see .
As of , you can register your function as a permanent UDF either in the current database or in a specified database, as described in . For example:
create function as
'
;
|
Deploying Jars for User Defined Functions and User Defined SerDes
In order to start using your UDF, you first need to add the code to the classpath:
hive> add jar
Added to
class
path
|
By default, it will look in the current directory. You can also specify a full path:
hive> add jar /tmp/
Added /tmp/ to
class
path
|
Your jar will then be on the classpath for all jobs initiated from that session. To see which jars have been added to the classpath you can use:
hive> list jars;
|
See for full syntax and more examples.
As of , UDFs also have the option of being able to specify required jars in the statement:
CREATE FUNCTION myfunc AS
'myclass'
USING JAR
'hdfs:///path/to/jar'
;
|
This will add the jar to the classpath as if ADD JAR had been called on that jar.
