Hive Funnel Analysis UDFs

Build Status Coverage Status Apache License 2.0

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

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 four 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), ...)

funnel_merge

funnel_merge(funnel_column)

funnel_conversion

funnel_conversion(funnel_column)

funnel_fallout

funnel_fallout(funnel_column)

Security

Older versions of Hive have known security issues. Keep the following issues in mind when deciding what Hive version to use when building the UDFs. Use the following steps to mitigate these issues, or update to Hive 2.3.4 to avoid all issues at once.

CVE-2018-11777

Description

In Apache Hive 2.3.3, 3.1.0 and earlier, local resources on HiveServer2 machines are not properly protected against malicious user if ranger, sentry or sql standard authorizer is not in use.

Resolution

Update pom.xml to use Hive 2.3.4.

CVE-2018-1284

Description

In Apache Hive 0.6.0 to 2.3.2, malicious user might use any xpath UDFs (xpath/xpath_string/xpath_boolean/xpath_number/xpath_double/xpath_float/xpath_long/xpath_int/xpath_short) to expose the content of a file on the machine running HiveServer2 owned by HiveServer2 user (usually hive) if hive.server2.enable.doAs=false.

Resolution

Update pom.xml to use Hive 2.3.3 or do not set hive.server2.enable.doAs to false.

CVE-2015-7521

Description

The authorization framework in Apache Hive 1.0.0, 1.0.1, 1.1.0, 1.1.1, 1.2.0 and 1.2.1, on clusters protected by Ranger and SqlStdHiveAuthorization, allows attackers to bypass intended parent table access restrictions via unspecified partition-level operations.

Resolution

Update pom.xml to use Hive 1.2.2.

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