Introduction

A rules engine transform will apply predefined set of rules to incoming data (realtime as well as batch) based on the field values in each record.

Use case(s)

• CompanyA wants to develop a streaming pipeline to read and process signals from wearable and non-wearable devices, and apply rules on incoming signals. Based on the rules, it wants to send notifications to configured mobile devices to provide concierge and/or healthcare services. A rules engine would be leveraged to determine which notifications to send based on the incoming signal.
• CompanyA has a rules management system that can allow each user to feed in a unique set of rules for each device. Rules can state actions to be taken if certain conditions are met in the signals from the provided devices. These rules are stored and can be retrieved and edited by the user at any time. A long running streaming pipeline would refresh the rules automatically, and begin applying them to incoming signals as needed.
• CompanyA would like a selection criteria for applying rules to incoming signals based on 3 different fields in the message. If there are no rules for field 1 found, then the pipeline would need to lookup based on the second field, and then the third field. Selection criteria could be based on device hierarchy, but could also be arbitrary. The company would like to configure the rule selection criteria in the plugin to account for this hierarchy.

User Storie(s)

• As a developer, I would like a way to define input field level transformations based on criteria such as field1 > 10 && field2 = "phone" where the output of the rule is an update to an existing field or the creation of a new field in the output record. (rule)
• As a developer, I would like a way for users to add/remove/edit rules that should be applied to data in the system. (rule management)
• As a developer, I would like to group those rules together using a common set of lookup criteria, such as field1=2343243,field2=device-name,field3=phone. (ruleset)
• As a Hydrator user, I would like to apply rulesets on the incoming messages based on fields from the incoming data. (ruleset criteria)
• As a Hydrator user, I would like to be able to look up rules from a rules repository (rule management)
• As a Hydrator user, I would like to apply only those rules that are applicable to the incoming record. For achieving this, I would like to specify a selection criteria for rules. The selection criteria may be based on input schema. (ruleset criteria)

Plugin Type

• Transform

Configurable Parameters

This section defines properties that are configurable for this plugin. 

Design / Implementation Tips

• The format of the rules can be in compliance with Jexl http://commons.apache.org/proper/commons-jexl/
• Rules in the rule-sets should be added in the order of their priority.
• Field names in the rules should be populated automatically by parsing the rule

Design

The output fields will be populated based on the output of the application of rules on one or many fields in the input schema.

Rules DB

Rule set DB

Approach(s)

• We will Set up a rule-set db in Tracker where a user can go and add rules with the specified rule set conditions
• If user does not select any rule set, The output will be the result of one to one mapping of the input and the output schema
• User will be able to reference the rule-set db from within the plugin to assign rule sets
• Rule-sets could be applied in the hierarchal manner such that, If no rule set exists for Field A, lookup rules for for Field B
• Post actions could be taken based on the values in the output.

Properties

• Rule-set DB: Name of the data set to be used as the rules repository, If left blank the default Tracker rules dataset will be used.
• LookUp fields: Map of  out put fields and corresponding list of fields based on which the rule - sets are to be applied. Multiple rules can be applied for single field.
• Hierarchal: Boolean (checkbox) to specify that the rule set lookup should be hierarchal or not.
  
  

Security

Limitation(s)

Point lookups are not currently supported by spark streaming

Future Work

• Some future work – HYDRATOR-99999
• Another future work – HYDRATOR-99999

Test Case(s)

• User is able to apply multiple rule sets.
• Output data is being filtered according to rules
• Not configuring any rule results in one to one mapping

Sample Pipeline