Hive Funnel Analysis UDFs

Funnel analysis is a method for tracking user conversion rates across actions. This enables detection of actions causing high user fallout.

These Hive UDFs enables funnel analysis to be performed simply and easily on any Hive table.

Table of Contents

• Requirements
• How to build
  • Build JAR
  • Register JAR with Hive
• How to use
  • funnel
  • funnel_merge
  • funnel_conversion
  • funnel_fallout
• Examples
  • Simple funnel
  • Simple funnel with conversion
  • Funnel with multiple groups
  • Multiple parallel funnels
• Contributors
• License

Requirements

Maven is required to build the funnel UDFs.

How to build

There is a provided Makefile with all the build targets.

Build JAR

make jar

This creates a funnel.jar in the target/ directory.

Register JAR with Hive

To use the funnel UDFs, you need to register it with Hive.

With temporary functions:

ADD JAR funnel.jar;
CREATE TEMPORARY FUNCTION funnel            AS 'com.yahoo.hive.udf.funnel.Funnel';
CREATE TEMPORARY FUNCTION funnel_merge      AS 'com.yahoo.hive.udf.funnel.Merge';
CREATE TEMPORARY FUNCTION funnel_conversion AS 'com.yahoo.hive.udf.funnel.Conversion';
CREATE TEMPORARY FUNCTION funnel_fallout    AS 'com.yahoo.hive.udf.funnel.Fallout';

With permenant functions you need to put the JAR on HDFS, and it will be registered with a database (you have to replace DATABASE and PATH_TO_JAR with your values):

CREATE FUNCTION DATABASE.funnel            AS 'com.yahoo.hive.udf.funnel.Funnel'  USING JAR 'hdfs:///PATH_TO_JAR/funnel.jar';
CREATE FUNCTION DATABASE.funnel_merge      AS 'com.yahoo.hive.udf.funnel.Merge'   USING JAR 'hdfs:///PATH_TO_JAR/funnel.jar';
CREATE FUNCTION DATABASE.funnel_conversion AS 'com.yahoo.hive.udf.funnel.Conversion' USING JAR 'hdfs:///PATH_TO_JAR/funnel.jar';
CREATE FUNCTION DATABASE.funnel_fallout    AS 'com.yahoo.hive.udf.funnel.Fallout' USING JAR 'hdfs:///PATH_TO_JAR/funnel.jar';

How to use

There are fout funnel UDFs provided: funnel, funnel_merge, funnel_conversion, funnel_fallout.

The funnel UDF outputs an array of longs showing conversion rates across the provided funnel steps.

The funnel_merge UDF merges multiple arrays of longs by adding them together.

The funnel_conversion UDF takes a raw count funnel result and converts it to the conversion rate.

The funnel_fallout UDF takes a raw count funnel result and converts it to the fallout rate.

There is no need to sort the data on timestamp, the UDF will take care of it. If there is a collision in the timestamps, it then sorts on the action column.

funnel

funnel(action_column, timestamp_column, array(funnel_1_a, funnel_1_b), array(funnel_2), ...)

• Builds a funnel report applied to the action_column, sorted by the timestamp_column.
• The funnel steps are arrays of the same type as the action column. This allows for multiple matches to move to the next funnel.
  • For example, funnel_1 could be array('register_button', 'facebook_invite_register'). The funnel will match the first occurence of either of these actions and proceed to the next funnel.
  • Or, funnel_1 could just be array('register_button').
• You can have an arbitrary number of funnels.
• The timestamp_column can be of any comparable type (Strings, Integers, Dates, etc).

funnel_merge

funnel_merge(funnel_column)

• Merges funnels. Use with funnel UDF.

funnel_conversion

funnel_conversion(funnel_column)

• Converts the result of a funnel_merge to a conversion rate. Use with funnel and funnel_merge UDF.
• For example, a result from funnel_merge could look like [245, 110, 54, 13]. This is result is in raw counts. If we pass this through funnel_conversion then it would look like [1.0, 0.44, 0.49, 0.24].

funnel_fallout

funnel_fallout(funnel_column)

• Converts the result of a funnel_merge to a fallout rate. Use with funnel and funnel_merge UDF.
• For example, a result from funnel_merge could look like [245, 110, 54, 13]. This is result is in raw counts. If we pass this through funnel_fallout then it would look like [0.0, 0.55, 0.50, 0.75].

Examples

Assume a table user_data:

action	timestamp	user_id	gender
signup_page	100	1	f
confirm_button	200	1	f
submit_button	300	1	f
signup_page	200	2	m
submit_button	400	2	m
signup_page	100	3	f
confirm_button	200	3	f
decline	200	3	f
...	...	...	...

Simple funnel

SELECT funnel_merge(funnel)
FROM (SELECT funnel(action, timestamp, array('signup_page', 'email_signup'),
                                       array('confirm_button'),
                                       array('submit_button')) AS funnel
      FROM user_data
      GROUP BY user_id) t1;

Result: [3, 2, 1]

Simple funnel with conversion rate

SELECT funnel_conversion(funnel_merge(funnel))
FROM (SELECT funnel(action, timestamp, array('signup_page'),
                                       array('confirm_button'),
                                       array('submit_button')) AS funnel
      FROM user_data
      GROUP BY user_id) t1;

Result: [1.0, 0.66, 0.5]

Funnel with multiple groups

SELECT gender, funnel_merge(funnel)
FROM (SELECT gender,
             funnel(action, timestamp, array('signup_page'),
                                       array('confirm_button'),
                                       array('submit_button')) AS funnel
      FROM table
      GROUP BY user_id, gender) t1
GROUP BY gender;

Result: m: [1, 0, 0], f: [2, 2, 1]

Multiple parallel funnels

SELECT funnel_merge(funnel1), funnel_merge(funnel2)
FROM (SELECT funnel(action, timestamp, array('signup_page'),
                                       array('confirm_button'),
                                       array('submit_button')) AS funnel1
             funnel(action, timestamp, array('signup_page'),
                                       array('decline')) AS funnel2
      FROM table
      GROUP BY user_id) t1;

Result: [3, 2, 1] [3, 1]

Contributors

Josh Walters, [email protected]

License

Apache License, Version 2.0