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JBoss Drools and Drools Fusion (CEP): Making Business Rules react to RTE
- 1. JBoss Drools and Drools Fusion (CEP): Making Business Rules react to RTE Tihomir Surdilovic [email_address] JBoss, a Division of Red Hat
- 2. Agenda Project (Drools) vs. Product (BRMS)
- 5. Drools at a glance Expert
- 6. Guvnor
- 7. JBPM5 Focus on Drools Fusion (CEP Extensions) Event Declaration and Semantics
- 8. Event Cloud, Streams and the Session Clock
- 11. Streams Support
- 12. Memory Management Questions & Answers
- 13. Project vs. Product Repository Rules and Metadata JBoss Enterprise BRMS Platform JBoss Rules Rules Engine/ Execution Rules Development & Management CEP Complex Events Jboss EWP
- 14. Project vs. Product Cont. Stand-alone Framework
- 15. Innovation
- 16. Fast and Frequent Releases
- 17. Tested on developer environments
- 18. Suitable for development and prototype
- 19. No Patches – On to next big thing
- 20. Non SLA bound forum support Fully Integrated Platform
- 21. Same Innovated Code + Stability
- 22. Stability – Includes usability, performance and security issues identified during productization
- 23. Certified for Multi-OS, Multi-DB
- 24. Best for Development and Production
- 25. 5 Yr lifecycle – Includes patches, updates, backward compatibility
- 26. SLA based full support from dedicated support engineers
- 27. Open Source Assurance – legal protection derived
- 28. Jboss community and Enterprise Changes Community / Enterprise Platform Delta BRMS Drools Enterprise Platforms - Performance, Scalability, Security and Quality improves over time without compromising long-term compatibility. 08/09 12/10 03/11 05/11 Over 150+ defect fixes & 35+ OS/JVM/DB certifications (& counting) between Drools Community 5.1 & JBoss BRMS 5.1.x
- 29. Evolution of Jboss BRMS 05/08 04/09 12/10 ? Lightweight Business Rules Engine Business Rules Engine
- 30. Authoring and Management App
- 31. Repository
- 32. EAP Certified
- 33. DBs, JVMs Business Rules Engine
- 34. Authoring and Management App
- 37. CEP – Tech Preview
- 38. EAP, EWS, EWP, JVMs, Dbs and more
- 39. Performance Repository JBoss Enterprise BRMS Platform 5.0 JBoss Rules BRM Repository JBoss Enterprise BRMS Platform 5.1 JBoss Rules BRM CEP Jboss EWP
- 40. “ A common platform to model and govern the business logic of the enterprise.” Drools Vision
- 41. Drools Vision Cont. Event Processes Semantic Ontologies Workflows Rules Rules Workflows Event Processes Semantic Ontologies
- 42. Drools History – Business Rule Engines 1980s 2010s 1990s 2000s OPS5 ART Clips Jess Drools 2 JRules Drools 3 Drools 4 Drools 5
- 43. Drools History Drools 2 Rete like XML Scripting language Drools 3 Based on Clips functionality
- 44. Iterative improves to JRules syntax with Clips functionality Drools 4 More declarative
- 45. Basic functional programming feature with “from”
- 46. Basic Rule Flow
- 47. Basic BRMS Drools 5 Improved functional programming with 'accumulate'
- 48. More Advanced Rule Flow integration
- 49. Complex Event Process Temporal Comparators
- 50. Sliding Time Windows Production ready BRMS (Guvnor)
- 51. Drools History Cont. Drools 5.1 Differential Diff (true modify) Drools 5.2 (this month, 5.2.0.CR1 available for download) Freeform expressions between patterns
- 53. Prolog like derivation queries
- 54. Decision tables and rule templates (Guvnor)
- 56. Sample Industries and Users Investment Millennium Investment Group (MIG) Logistics Fedex Airline Sabre Mortgage Franklin American Healthcare OSDE
- 57. Drools at a glance - Declarative programming Production Rule Systems PRD (forward chaining) Reactive
- 58. when Alarm( status == “alert” ) then send( “warning” ) Logic Programming LP (backward chaining) Query
- 59. descendant( “mary”, “jane”) Functional Programming FP Map,Fold, Filter
- 60. avg([12, 16, 4, 6]) Returns single value 9.5 round([10.3, 4.7, 7.8] ) Returns List [10, 5, 8] Description Logic (model concepts, roles, and individuals) Person Has Name and lives at Address
- 61. Drools Expert at a glance – Example A - SQL comparison example select * from Account acc, Cashflow cf, AccountPeriod ap where acc.accountNo == cf.accountNo and cf.type == CREDIT cf.date >= ap.start and cf.date <= ap.end trigger : acc.balance += cf.amount rule “increase balance for AccountPeriod Credits” when ap : AccountPeriod() acc : Account( $accountNo : accountNo ) CashFlow( type == CREDIT, accountNo == $accountNo, date >= ap.start && <= ap.end, $ammount : ammount ) then acc.balance += $amount; end
- 62. Drools Expert at a glance – Rules as a view rule “increase balance for AccountPeriod Credits” when ap : AccountPeriod() acc : Account( $accountNo : accountNo ) CashFlow( type == CREDIT, accountNo == $accountNo, date >= ap.start && <= ap.end, $ammount : ammount ) then acc.balance += $amount; end rule “decrease balance for AccountPeriod Debits” when ap : AccountPeriod() acc : Account( $accountNo : accountNo ) CashFlow( type == DEBIT, accountNo == $accountNo, date >= ap.start && <= ap.end, $ammount : ammount ) then acc.balance -= $amount; end
- 63. Drools Expert at a glance – Example A - Building and executing rules
- 64. Drools Expert at a glance – Example A Building and executing rules cont. Building Executing
- 65. Drools Expert at a glance – Example B - Building and executing rules
- 66. Drools Expert at a glance – Example B cont. No Fires Add some Fires
- 67. Drools Expert at a glance – Example B cont. Fires are put out after a while
- 68. Drools Expert at a glance – Conditional Elements
- 69. Drools Expert at a glance – Accumulate CE Bus Example Accumulate general syntax Bus Example Revisited (no accumulate functions)
- 70. Drools Expert at a glance – Conditional Elements From
- 71. Drools Expert at a glance – Timers and Calendars Interval Timers Field Name Mandatory? Allowed Values Allowed Special Characters Seconds YES 0-59 , - * / Minutes YES 0-59 , - * / Hours YES 0-23 , - * / Day of month YES 1-31 , - * ? / L W Month YES 1-12 or JAN-DEC , - * / Day of week YES 1-7 or SUN-SAT , - * ? / L # Year NO empty, 1970-2099 , - * / Cron-based Timers
- 72. Drools Expert at a glance – Timers and Calendars Calendars Using Timers and Calendars together Execute now and after 1 hour duration on week days Execute now and after 4 hour duration on weekend days
- 73. Drools Expert at a glance – Truth maintenance and Inference Issuing Buss passes – typical rule implementation Good practice to do: De-couple knowledge responsibilities
- 75. Provide semantic abstractions for those encapsulation
- 76. Integrity robustness – truth maintenance These types of implementations are considered Bad
- 77. Monolithic
- 78. Leaky
- 79. Brittle integrity - manual maintenance Couples the logic What happens when the Child becomes 16?
- 80. Drools Expert at a glance – Truth maintenance and Inference cont. De-coupling knowledge responsibilities De-couples the logic Maintains the truth by automatically retracting. Rule “logically” inserts an object. When the rule is no longer true, the object is retracted. The truth maintenance cascades
- 81. Drools Expert at a glance – Truth maintenance and Inference cont. Notification upon automatic fact retraction Executing The truth maintenance cascades
- 82. Drools Expert at a glance – Roadmap Improved backward chaining (open queries)
- 88. Runtime Management BAM (Business Activity Monitoring)
- 89. Drools Guvnor at a glance Technology JCR 2.0 (JSR-170) backend
- 90. Seam 2 + GWT frontend
- 91. WebDav
- 93. Role based security Authoring Decision Tables
- 94. Guided Editor QA Scenario Testing + Rule Verification
- 95. Drools Guvnor at a glance – Business asset storage
- 96. Drools Guvnor at a glance – Guided Editor
- 97. Drools Guvnor at a glance – Decision Tables
- 98. Drools Guvnor at a glance – Scenario Testing
- 99. Drools Guvnor at a glance – BPMN2 processes
- 100. Drools Guvnor at a glance – Compiling and exposing rule packages
- 101. jBPM5 at a glance – What is BPM? Business Process Management A business process is a process that describes the order in which a series of steps need to be executed, using a flow chart.
- 102. jBPM5 at a glance – Why BPM? Visibility
- 103. Monitoring
- 105. Speed of development
- 106. Increased agility
- 107. jBPM5 at a glance – Key Characteristics Open-source business process management project offering: generic process engine supporting native BPMN 2.0 execution
- 108. targeting developers and business users
- 109. collaboration, management and monitoring using web-based consoles
- 110. powerful rules and event integration Core engine is a workflow engine in pure Java state transitions
- 111. lightweight
- 112. embeddable
- 113. generic, extensible Core Engine
- 114. jBPM5 at a glance – Core Engine // (1) Create knowledge base and add process definition KnowledgeBuilder kbuilder = ... kbuilder.add( ..., "sample.bpmn", ResourceType.BPMN2); KnowledgeBase kbase = kbuilder.newKnowledgeBase(); kbase.addKnowledgePackages(kbuilder.getKnowledgePackages()); // (2) Create new stateful knowledge session StatefulKnowledgeSession ksession = kbase.newStatefulKnowledgeSession(); // (3) Start a new process instance ksession.startProcess(“com.sample.bpmn.hello”); Knowledge Base Stateful Knowledge Session Process Definition Process Instance
- 115. jBPM5 at a glance – BPMN 2.0 OMG specification Model
- 116. Notation
- 117. Execution semantics Understandable by all business users
- 119. Extensible < definitions ... > < process id="com.sample.bpmn.hello" name="Hello World" > < startEvent id="_1" name="StartProcess" /> < sequenceFlow sourceRef="_1" targetRef="_2" /> < scriptTask id="_2" name="Hello" > < script >System.out.println("Hello World");</ script > </ scriptTask > < sequenceFlow sourceRef="_2" targetRef="_3" /> < endEvent id="_3" name="EndProcess" /> </ process > </ definitions > Core Engine BPMN 2.0 XML
- 120. jBPM5 at a glance – Persistence and Transactions Persistence (JPA, pluggable) Runtime persistence
- 121. History logging
- 122. Services Transactions (JTA, pluggable) Command-scoped
- 123. User-defined Core Engine BPMN 2.0 XML Persistence Trans- actions JPA JTA
- 124. jBPM5 at a glance – Console Web-based management
- 125. Business user
- 126. Features Process instance management
- 127. User task lists / forms
- 128. Reporting Core Engine BPMN 2.0 XML Persistence Trans- actions Events History Log Management Console BAM
- 129. jBPM5 at a glance – Console Domain-specific Processes: Extend palette with
- 131. service nodes define input / output parameters
- 132. runtime binding User task
- 133. Human task service (WS-HT) Task lists
- 134. Task life cycle Task clients Task forms Core Engine BPMN 2.0 XML Persistence Trans- actions Events Integration Domain-specific Processes Human Task Service ESB
- 135. jBPM5 at a glance – Roadmap jBPM 5.0: February 2011
- 136. jBPM 5.1: NOW ... Improve Oryx BPMN2 designer to support full round-tripping
- 137. New Eclipse BPMN2 editor
- 138. Lots of small feature improvements and bug fixes jBPM 5.2 – jBPM 6.x Simulation / testing / replay
- 139. Flexible, adaptive, goal-oriented processes
- 140. Integrated “no-code” tooling (form builder, etc.)
- 141. Focus on Drools Fusion (CEP) Brief introduction on CEP and Terminology
- 142. Drools Vision
- 143. Drools Fusion: Complex Event Processing extensions Event Declaration and Semantics
- 144. Event Cloud, Streams and the Session Clock
- 145. Temporal Reasoning
- 147. Streams Support
- 148. Memory Management
- 149. Drools Fusion – What is an Event? “ An event is an observable occurrence .”
- 150. “ An event in the Unified Modelling Language is a notable occurrence at a particular point in time .”
- 152. “ Anything that happens , or is contemplated as happening .”
- 153. “ An object that represents, encodes or records an event , generally for the purpose of computer processing ”
- 154. http://complexevents.com For the scope of this presentation:
- 155. “ An event is a significant change of state at a particular point in time ”
- 156. Drools Fusion – What is a Complex Event? “ Complex Event , is an abstraction of other events called its members.” Examples : The 1929 stock market crash – an abstraction denoting many thousands of member events, including individual stock trades)
- 157. The 2004 Indonesian Tsunami – an abstraction of many natural events
- 158. A completed stock purchase -an abstraction of the events in a transaction to purchase the stock
- 159. A successful on-line shopping cart checkout – an abstraction of shopping cart events on an on-line website Source: http://complexevents.com
- 160. Drools Fusion – What is Complex Event Processing (CEP)? “ Complex Event Processing , or CEP, is primarily an event processing concept that deals with the task of processing multiple events with the goal of identifying the meaningful events within the event cloud.
- 161. CEP employs techniques such as detection of complex patterns of many events, event correlation and abstraction , event hierarchies, and relationships between events such as causality, membership, and timing, and event-driven processes.”
- 162. -- wikipedia
- 163. Drools Fusion – CEP Scenarios Examples: Emergency Response Systems
- 164. Credit Card Fraud Detection
- 165. Logistics Real-Time Awareness solution
- 166. Neonatal ICU: infant vital signs monitoring A few characteristics of common CEP scenarios: Huge volume of events, but only a few of real interest Usually events are immutable
- 167. Usually queries/rules have to run in reactive mode
- 168. Strong temporal relationships between events Individual events are usually not important The composition and aggregation of events is important
- 169. Drools Fusion – CEP vs. ESP Complex Event Processing , or CEP, and Event Stream Processing , or ESP, are two technologies that were born separate, but converged . An oversimplification : In their origins... Event Stream Processing focused on the ability to process high volume streams of events.
- 170. Complex Event Processing focused on defining, detecting and processing the relationships among events. For the scope of this presentation:
- 171. “ CEP is used as a common term meaning both CEP and ESP .”
- 172. Drools Fusion – EDA “ Event Driven Architecture (EDA) is a software architecture pattern promoting the production , detection , consumption of, and reaction to events. An event can be defined as "a significant change in state"[1]. For example, when a consumer purchases a car, the car's state changes from "for sale" to "sold". A car dealer's system architecture may treat this state change as an event to be produced, published, detected and consumed by various applications within the architecture.” http://en.wikipedia.org/wiki/Event_Driven_Architecture CEP is a component of the EDA
- 173. Drools Fusion – EDA vs SOA EDA is **not** SOA 2.0
- 175. Metaphor In our body : SOA is used to build our muscles and organs (what's needed to DO things)
- 176. EDA is used to build our sensory system (what's needed to REACT TO things)
- 177. Drools Fusion – CEP Characteristics A few characteristics of common CEP scenarios: Huge volume of events, but only a few of real interest Usually events are immutable
- 178. Usually queries/rules have to run in reactive mode
- 179. Strong temporal relationships between events Individual events are usually not important The composition and aggregation of events is important
- 180. Drools Fusion – Enables... Event Detection: From an event cloud or set of streams, select all the meaningful events, and only them. [Temporal] Event Correlation: Ability to correlate events and facts declaring both temporal and non-temporal constraints between them.
- 181. Ability to reason over event aggregation Event Abstraction: Ability to compose complex events from atomic events AND reason over them
- 182. Drools Fusion – Features Features: Event Semantics as First Class Citizens
- 183. Allow Detection, Correlation and Composition
- 184. Temporal Constraints
- 185. Session Clock
- 186. Stream Processing
- 187. Sliding Windows
- 189. (Re)Active Rules
- 190. Data Loaders for Input
- 191. Drools Fusion – Demo Twitter Stream CEP Demo: Listen to the Twitter Stream API Twitter4J API
- 192. Listens to a random sample of tweets Detects patterns and reacts Drools Fusion Simple one process (multi-thread) demo Focus on specific features
- 193. Drools Fusion – Event Declaration and Semantics Event semantics: Point-in-time and Interval An event is a fact with a few special characteristics: Usually immutable , but not enforced
- 194. Strong temporal relationships Lifecycle may be managed Allow use of sliding windows “ All events are facts , but not all facts are events.”
- 195. Demo twitter rules part 1, 2, 3) // declaring existing class import some.package.VoiceCall declare VoiceCall @role ( event ) @timestamp ( calltime ) @duration ( duration ) end // generating an event class declare StockTick @role ( event ) symbol : String price : double end
- 196. Drools Fusion – Temporal Reasoning Semantics for: time: discrete
- 197. events: point-in-time and interval Ability to express temporal relationships: Allen’s 13 temporal operators James F. Allen defined the 13 possible temporal relations between two events.
- 198. Eiko Yoneki and Jean Bacon defined a unified semantics for event correlation over time and space.
- 199. Drools Fusion – Temporal Relationships rule “Shipment not picked up in time” when Shipment ( $pickupTime : scheduledPickupTime ) not ShipmentPickup ( this before $pickupTime ) then // shipment not picked up... Action required. end Temporal Relationship
- 200. Drools Fusion – Allen’s 13 Temporal Operators Point-Point Point-Interval Interval-Interval A before B A meets B A overlaps B A finishes B A includes B A starts B A coincides B A B A B A B A B A B A B A B
- 201. Drools Fusion – Allen’s 13 Temporal Operators Point-Point Point-Interval Interval-Interval A after B A metBy B A overlapedBy B A finishedBy B A during B A finishes B Demo twitter rules part 4 A B A B A B A B A B A B
- 202. Drools Fusion – Streams : Simple Example Scenario
- 203. Drools Fusion – Stream Support (entry-points) A scoping abstraction for stream support Rule compiler gather all entry-point declarations and expose them through the session API
- 204. Engine manages all the scoping and synchronization behind the scenes. rule “Stock Trade Correlation” when
- 205. $c : Customer( type == “VIP” )
- 206. BuyOrderEvent( customer == $c , $id : id ) from entry-point “Home Broker Stream”
- 207. BuyAckEvent( sourceEvent == $id ) from entry-point “Stock Trader Stream”
- 208. then
- 209. // take some action
- 210. end
- 211. No notion of “flow of time” : the engine sees all facts without regard to time
- 212. No attached Session Clock
- 213. No requirements on event ordering
- 214. No automatic event lifecycle management
- 215. No sliding window support Notion of “flow of time” : concept of “now”
- 216. Session Clock has an active role synchronizing the reasoning
- 217. Event Streams must be ordered
- 218. Automatic event lifecycle management
- 219. Sliding window support
- 220. Automatic rule delaying on absence of facts Drools Fusion – Cloud Mode, Stream Mode, Session Clock CLOUD STREAM
- 221. Drools Fusion – Reference Clock Reference clock defines the flow of time Named Session Clock is assigned to each session created Synchronizes time sensitive operations duration rules
- 222. event streams
- 223. process timers
- 224. sliding windows
- 225. Drools Fusion – Session Clock Uses the strategy pattern and multiple implementations: Real-time operation
- 226. Tests
- 227. Simulations
- 228. etc
- 229. Drools Fusion – Session Clock Selecting the session clock: API: KnowledgeSessionConfiguration conf = ...
- 230. conf.setOption( ClockTypeOption.get( “realtime” ) ); System Property or Configuration File: drools.clockType = pseudo
- 231. Drools Fusion – Sliding Window Support Allows reasoning over a moving window of “interest” Time
- 232. Length Sliding window 1 Sliding window 2
- 233. Drools Fusion – Sliding Window Support Allows reasoning over a moving window of “interest” Time
- 234. Length Sliding window 1 Sliding window 2 Joined window
- 235. Drools Fusion – Sliding Window Support Allows reasoning over a moving window of “interest” Time
- 236. Length Demo twitter rules part 5 rule “Average Order Value over 12 hours” when $c : Customer() $a : Number() from accumulate ( BuyOrder( customer == $c , $p : price ) over window:time ( 12h ),
- 237. average ( $p ) )
- 238. then
- 239. // do something
- 240. end
- 241. Drools Fusion – Delaying Rules Negative patterns may require rule firings to be delayed. rule “Order timeout” when $bse : BuyShares ( $id : id ) not BuySharesAck( id == $id , this after[0s,30s] $bse ) then // Buy order was not acknowledged. Cancel operation // by timeout. end Forces the rule to wait for 30 seconds before firing, because the acknowledgement may arrive at any time!
- 242. Drools Fusion – Temporal Dimension Requires the support to the temporal dimension A rule/query might match in a given point in time, and not match in the subsequent point in time That is the single most difficult requirement to support in a way that the engine: stays deterministic
- 243. stays a high-performance engine Achieved mostly by compile time optimizations that enable: constraint tightening
- 245. memory management
- 246. Drools Fusion – Temporal Dimension Support CEP scenarios are stateful by nature.
- 247. Events usually are only interesting during a short period of time .
- 248. Hard for applications to know when events are not necessary anymore Temporal constraints and sliding windows describe such “ window of interest ”
- 249. Drools Fusion – Simple Example Rule rule “Bag was lost” when $b : BagScannedEvent() from entry-point “check-in” not BagScannedEvent( id == $b.id , this after[0s,5m] $b ) from entry-point “pre-load”
- 250. then
- 251. // Bag was lost, do something
- 252. end Easy to “see” that the only temporal relationship between the events defines a 5 minutes interest window.
- 253. Drools Fusion – Abstract Example Rule rule “Abstract event relationship example” when $a : A() $b : B( this after[-2, 2] $a ) $c : C( this after[-3, 4] $a ) $d : D( this after[ 1, 2] $b, this after[2,3] $c ) not E( this after[ 1,10] $d ) then // Bag was lost, do something end How about now? What is the temporal relationship between A and E?
- 254. Drools Fusion – Temporal Dependency Matrix A B C D E A [ 0, 0 ] [ -2, 2 ] [ -3, 2 ] [ -1, 4 ] [ 0, 14 ] B [ -2, 2 ] [ 0, 0 ] [ -2, 0 ] [ 1, 2 ] [ 2, 12 ] C [ -2, 3 ] [ 0, 2 ] [ 0, 0 ] [ 2, 3 ] [ 3, 13 ] D [ -4, 1 ] [ -2, -1 ] [ -3, -2 ] [ 0, 0 ] [ 1, 10 ] E [ -14, 0 ] [ -12, -2 ] [ -13, -3 ] [-10,-1 ] [ 0, 0 ] Constraint tightening Demo twitter rules part 6 [-2,2] [-3,4] [2,3] [1,2] [1,10] A D B E C
- 255. Q&A Drools project site: http://www.drools.org ( http://www.jboss.org/drools/ ) Documentation: http://www.jboss.org/drools/documentation.html Tihomir Surdilovic – tsurdilo @redhat.com