Technical Report. Implementation and Performance Testing of Business Rules Evaluation Systems in a Computing Grid. Brian Fletcher x

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1 Technical Report Implementation and Performance Testing of Business Rules Evaluation Systems in a Computing Grid Brian Fletcher x

2 Executive Summary 4 Introduction 5 Background 5 Aims 5 Technology 5 Structure 5 Background 7 Coherence 7 RETE 7 Knowledge Base 7 What is a Rule 7 Rete Algorithm 8 Drools 8 System 9 Requirements 9 Functional Requirements 9 Data Requirements 9 User Requirements 9 Environmental Requirements 9 Design and Architecture 10 Standalone Rule Grid Application 10 Amazon Virtual Server Image 10 Deployment Descriptor 11 Build Configuration Script 11 Environment Directory Structure 11 Grid Configuration 11 User Interface 12 Implementation 12 Algorithm 15 Testing 16 Stand Alone Rule Evaluation Test 16

3 RuleGrid Test 16 Graphical User Interface 17 Dashboard 17 Load Data 17 Run Rule 17 Edit Rule 17 Customer Acceptance Testing 17 Evaluation 18 Stand Alone Rule Evaluation Test 18 RuleGrid Test 19 Conclusions 21 Bibliography Error! Bookmark not defined. Appendix 23 Appendix A: Tomcat Context Configuration 23 Appendix B: Bash Script 23 Appendix C: Attached Documents 24 Project Proposal and Project Plan 24 Requirements Specification 24 Monthly Log Book Reflective Journals 24

4 Executive Summary Once you open a can of worms, the only way to re-can them is to use a bigger can. (Seovic, 2010) The RuleGrid application shows that, using grid technology, it is possible to create an application with externalised business logic that is scalable. RuleGrid shows that the logic of an application may be written out side of the compiled code. It shows performance increases as the size of the grid increases. It also shows that there is almost no limitation to the size of the universe of data which is processed by the application.

5 Introduction Background The cloud computing paradigm has increased pressure on the software architect to design applications which are high performing, available, scalable, and reliable. Also due to the fast pace of change in business and online services, modern software must provide flexibility to modification. Taken in isolation, many of these non-functional requirements may be dealt with by software platforms, frameworks and patterns. However, few exist which deal with all of them together. Aims This project makes use of Drools and Oracle Coherence to distribute the processing of the Drools rule evaluation system across a computing grid in order to create a high performing Software platform for externalising business logic in an available, scalable, and reliable manner. Technology Oracle Coherence is a software framework which provides the ability to create a data grid to develop high performance applications which deliver reliability, scalability, and availability. Drools is a business rule evaluation system. It externalises business logic from the application code to create dynamic flexible applications. The environment used for testing RuleGrid was the Amazon Elastic Cloud. RuleGrid also makes use of many other technologies including Tomcat, JSP, the Servlet API, JDK 1.6, Eclipse IDE, Log4j, Jackson, Maven etc. Structure This report begins by describing the background of the main technologies and software packages which were used during the project. It continues by giving an overview of the requirements of the project (the detailed requirements specification document is attached in the appendix). The architecture chapter describes the deployment environment of the application that was developed.

6 The report continues by describing the implementation and the main algorithm of the application. Next the method used to test and evaluate are discussed. The report then finishes with a conclusion. The appendix contains links to other relevant documents and some code.

7 Background Coherence Coherence is a data caching technology developed by Oracle. It provides an interface to the developer to access a data cache by name. When this handle to the cache is received it is possible to put and get objects to and from the cache. Coherence transmits a multi-cast message to the network on which it is connected in order to discover other applications which are running Coherence. If it finds one it will pair with the other instance of Coherence and begin to share data. This pair of instances are called a grid. Coherence provides a number of configuration options for a named data cache: Distributed Cache; Replication Cache. Replicated Cache ensures that all objects that are put into the cache will be replicated on each and every Coherence instance. Distributed Cache ensures that each object is replicated on only two instances at a time. One of the objects is considered the primary and the second is a backup. The backup is kept for the case where the instance which holds the primary copy of the object goes down. Coherence provides seamless failover of instances on a grid. RETE Rete is a pattern matching algorithm for rule evaluation. It was developed by Chales L. Forgy. It was first published in his PhD thesis in (Forgy, 1982) It works by building a type of data structure tree in memory which represents the rule. The objects are then tested against the nodes of the tree. If it is decided that it is a match for a rule then it is marked for execution. When all objects are processed then execution phase is triggered. Knowledge Base A knowledge base contains the set of facts, in the form of objects, which are tested using a business rule. An example of a facts are: Person 1 is 28; Person 1 is Male. What is a Rule In the context of a Business rule system a rule consists of a left hand side (LHS) and a right hand side (RHS). The LHS contains a set of conditions e.g. if persion is male and person is older than 27.

8 The RHS contains a set of instructions e.g. set insurance quote to If a fact is found that matches on all of the conditions in the LHS then the fact is considered as a match for the rule. The RHS is executed when a match is found for a rule. This execution is referred to as the agenda of a rule. Rete Algorithm Figure 1 below shows a diagram of the Rete network. (Young, 2006) Figure 1 The Alpha network matches the facts contained in the knowledge base against the rule. This will match only the objects themselves and does not consider the relationships between the objects. The beta network matches the relationships between the nodes. If a match is found an agenda is generated and the new information is added to the knowledge base as a fact. The object is then passed back through the Rete network. The benefit of the Rete algorithm is that changes to the knowledge base will only require the changed fact to be passed back through the network again. Drools Drools is an open source Business rules evaluation system. It provides an implementation of the Rete pattern matching algorithm. It also provides a scripting language which may be used to implement the business rules.

9 System Requirements A more detailed requirements specification is attached to the appendix. This section represents a retrospective view of the requirements of the system. Functional Requirements Rule Invocation must run across the grid The system must provide an interface for a developer to make use of the rule grid It must be possible to scale up or down the number of machine nodes Data Requirements The data processed must be absolutely accurate The data is provided as Java objects either serializable or Portable Object Format The calculations of the rules engine must be exact The system must be scalable to react to increase in processing User Requirements It must have an administration GUI to view current status of the system It must have the ability to edit the current rule It must have the ability to view the number of running nodes It must have the ability to trigger the loading of data from a file It must have the ability to trigger the rule on the loaded data Environmental Requirements The software must run on Windows, Mac or Linux Each node must run on any standard machine A live node must be able to find its parter nodes A starting node must dynamically set itself up to join the grid The transferred data must be encrypted to travel across the internet

10 Design and Architecture Standalone Rule Grid Application RuleGrid is a Java enterprise web application which is delivered as a web application archive (.war). The application is deployed in a Java web application container such as Apache Tomcat. RuleGrid reads a configuration file at start up and writes logs during its operation. Amazon Virtual Server Image A custom Amazon Virtual Server Image (AMI) was developed. The image is programmed to download a build configuration script from a known FTP server and run it. This configuration script creates the local infrastructure to run the application on the Virtual Server. Please refer to the User Manual for steps on how to recreate this environment.

11 Deployment Descriptor The deployment descriptor is an xml file which is read by the Tomcat Application Server. It instructs Tomcat to deploy and configure the RuleGrid application. Build Configuration Script The purpose of the build configuration script is to create the environment required to launch Rule Grid. It follows the following steps 1. Create Environment Directory Structure 2. Download Tomcat 3. Un-Pack tomcat to the correct directory 4. Download the latest Deployment Descriptor 5. Download the latest RuleGrid web application 6. Launches the Application Environment Directory Structure The following directory structure is created dynamically by the Build Configuration Script. +---build +---rulegrid \---rules +---servers \---tar The directories contain the following: build contains the downloaded web application archive file; rulegrid contains configuration files, including data to load into the grid and the business rules; servers contains the tomcat application server; and tar contains the downloaded tomcat archive. Grid Configuration The first node which starts up must be assigned a known IP address. This service is provided by the Amazon Elastic Cloud Infrastructure. The service is called Elastic IP. Every subsequent node will use this IP address as an entry point to the grid. It will use Elastic IP to look up the first node to look up the other nodes in the grid.

12 User Interface Users access the application through the Elastic IP Address using a standard web browser. The User Interface is implemented using Java Server Pages and can be accessed through any of the RuleGrid nodes in the grid. This means that a gateway may be setup which redirects users to an available node depending on load. Implementation RuleGrid is made up of four java packages: org.brianfletcher.rulegrid.gui; org.brianfletcher.rulegrid.domain; org.brianfletcher.rulegrid.source; org.brianfletcher.rulegrid.util.

13 The org.brianfletcher.rulegrid.gui packagecontains classes that are used by the jsp pages. The org.brianfletcher.rulegrid.domain package defines some business domain classes which are used to demonstrate the RuleGrid.

14 The org.brianfletcher.rulegrid.source contains a class for parsing data from a csv file and creating Instrument objects. The org.brianfletcher.rulegrid.util package contains other utility classes. The StartupServlet is called by the application container when a node is started. It is therefore the entry point to the application. The PropertiesHolder is used to store property information.

15 Algorithm The Coherence data grid is configured using a distributed cache. As described above, this means that the objects that are stored in the cache are distributed throughout the grid. Figure 2 below shows a diagram of a distributed cache. (Misek, 2008) Figure 2 When an object is added to the cache, it is distributed among the nodes in the grid. An object will appear once in a primary partition and once in a backup partition. The distributed rule evaluation algorithm works by performing the rule evaluation on each of the objects that are stored in the grid in the location in which they currently reside. By sending the operation to the node that is currently holding the object the network transfer is reduced. As well as this the node that instigates the rule evaluation does not need to copy all of the objects into its own local memory cache. This means that the number of objects that are supported by the distributed rule evaluation is scalable with the number of nodes.

16 Testing Stand Alone Rule Evaluation Test A separate test application was written. It measures the time it takes to load a variable set of data objects into the knowledge session. It then measures the time it takes to run a standard rule on the data. RuleGrid Test A separate test was run whereby a fixed number of data objects (125000) were loaded into the rule grid. A standard rule was then run on all of these objects contained in the RuleGrid. The test was repeated for 1 to 10 RuleGrid nodes. The results were recorded.

17 Graphical User Interface The User interface for the RuleGrid application is built using JSP and Java Sevlet Technologies. There are four basic interface windows. The purpose of each is to demonstrate the working of the application. Dashboard Load Data Run Rule Edit Rule Dashboard The purpose of the dashboard is to display the current status of the nodes within the grid. It shows the number of currently active nodes in the grid and gives some detail about the machines and processes in which the RuleGrid application is running. This demonstrates how the application is almost limitlessly scaleable. Load Data The Load Data window allows the user to trigger the loading of sample data into the RuleGrid cache. This data is shared between all of the running nodes in the grid. When the data is loaded it is displayed on the page. This page is used to demonstrate the data before and after the Rule is run. Run Rule The Run Rule windows purpose is to execute the rule on the loaded data. It shows the date and time that the rule began evaluating and the time that it completed. It then gives a figure about how long the processing of the rule took. This value is used in the performance testing on the application. Edit Rule This allows the user to edit the rule. This demonstrates the externalising of the logic of the Rule Evaluation. Customer Acceptance Testing In the absence of a real customer for this application, it was made available on the internet. Other students in the class were asked to test and make comment and suggestions about RuleGrid.

18 Evaluation The tests were performed as described in the testing section above. The results were as follows: Stand Alone Rule Evaluation Test In the first test the stand alone application was run. It generated a number of random Instrument 1 objects. The number of objects in each test went from 2500 to When the test reached the Java Virtual machine hit an Out Of Memory error. The time that it took to Load the data into the Rules Session was recorded and the time that it took to run the rule was recorded. Number of Instruments Loading Data Rule Running Number of Instruments Loading Data An Instrument is a financial term for a type of product.

19 Number of Instruments Rule Running RuleGrid Test The test performed on the RuleGrid application took a fixed number of instrument objects (125000). These objects were loaded into the grid with one RuleGrid node running. The same rule was run on the data as was for the previous test. The test was then repeated for 2 to 10 RuleGrid nodes running. Number of RuleGrid Nodes Time Taken

20 Number of RuleGrid Nodes Time Taken

21 Conclusion The RuleGrid application shows that it is possible to create an application with externalised business logic that is scalable using grid technology. We can see from the Evaluation of the application that there are performance gains as the number of nodes in the grid increases. It can also be seen that the limit of memory inherent in a standalone application does not apply in a grid setup. This means that as an application requires more objects to be stored in its cache, new nodes may be added. A limitation of the RuleGrid is that relationships between objects in the grid are ignored. The RuleGrid executes the rule evaluation on each object individually. This means that no relationship can be considered. A similar project to this is currently in process in the Drools source code. It is called Drools Grid. It slightly improves the implementation that was used here. It works by allowing each node in a grid to host a business knowledge session. This means that if there are multiple sessions required then each may be sent for processing on alternative nodes. (Salaboy, 2010) In order to fully make use of a rules system working on a distributed set of objects, it may be possible to create an algorithm which better deals with the grid topology. However the Rete algorithm was designed with a standalone process in mind.

22 Bibliography Bali, M. (2009). Drools JBoss Rules 5.0 Developer's Guide. Packt Publishing. Ching, M. (2009). Apache Maven 2 Effective Implementation. Packt Publishing. Doorenbos, R. B. (1995). Production Matching for Large Learning Systems. Pittsburgh: Carnegie Mellon University. Forgy, C. L. (1982). Rete: A Fast Algoritm for the Many Pattern/Many Object Pattern Match Problem. Pittsburgh: Carnegie-Mellon University. Gupta, A., Forgy, C., Newell, A., & Wedig, R. (1986). Parallel Algorithms and Architectures for Rule Based Systems. Pittsburgh: Carnegie Mellon University. Misek, R. (2008, September 15). Retrieved from Oracle Coherence: Salaboy. (2010). Retrieved 2010, from Seovic, A., Falco, M., & Peralta, P. (2010). Oracle Coherence 3.5. Packt Publishing.

23 Appendix Appendix A: Tomcat Context Configuration <Context path="/rulesgrid" docbase="/home/ec2-user/dev/build/rulegrid2.war" debug="0"> </Context> Appendix B: Bash Script #!/bin/bash echo Rule Grid Environment Setup Script from FTP hostname localhost cd /home/ec2-user rm -rf dev mkdir dev cd dev mkdir tar mkdir servers cd tar wget tar.gz cp apache-tomcat tar.gz../servers/apache-tomcat tar.gz cd../servers tar zxvf apache-tomcat tar.gz rm apache-tomcat tar.gz sudo yum -y install ftp mkdir apache-tomcat /conf/catalina/ mkdir apache-tomcat /conf/catalina/localhost cd apache-tomcat /conf/catalina/localhost wget --no-check-certificate cd../../../../.. mkdir build cd build wget --no-checkcertificate cd.. mkdir rulegrid cd rulegrid mkdir rules cd rules wget --no-check-certificate cd.. wget --no-checkcertificate cd /home/ec2-user/dev/servers/apache-tomcat /bin/./startup.sh -Dtangosol.pof.enabled=true -Dtangosol.pof.config="pof-config.xml"

24 Appendix C: Attached Documents Project Proposal and Project Plan Project_Proposal_Fin ished_grid_rules (1).docx Requirements Specification RequirementsSpecific ation.pdf Monthly Log Book Reflective Journals ReflectiveJournal doc ReflectiveJournal doc ReflectiveJournal doc ReflectiveJournal201 ReflectiveJournal doc doc ReflectiveJournal201 ReflectiveJournal doc doc

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