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Slide 1: Creating Interactive OLAP Applications with MySQL Enterprise and Mondrian Julian Hyde: Chief Architect, OLAP, at Pentaho and Mondrian Project Founder Wednesday, April 16th 2008
Slide 2: Agenda Pentaho Introduction Mondrian features and architecture Schemas and queries olap4j Roadmap Case Studies Business Intelligence suite Q&A
Slide 3: Pentaho Introduction World’s most popular enterprise open source BI Suite 2 million lifetime downloads, averaging 100K / month Founded in 2004: Pioneer in professional open source BI Management - proven BI and open source veterans from Business Objects, Cognos, Hyperion, JBoss, Oracle, Red Hat, SAS Board of Directors – deep expertise and proven success in open source Larry Augustin - founder, VA Software, helped coin the phrase “open source” New Enterprise Associates – investors in SugarCRM, Xensource, others Index Ventures – investors in MySQL, Zend, others Widely recognized as the leader in open source BI Distributed worldwide by Red Hat via the Red Hat Exchange Embedded in next release of OpenOffice (40 million users worldwide)
Slide 4: What is OLAP? View data “dimensionally” i.e. Sales by region, by channel, by time period Navigate and explore Ad Hoc analysis “Drill-down” from year to quarter Pivot Select specific members for analysis Interact with high performance Technology optimized for rapid interactive response
Slide 5: Mondrian features and architecture
Slide 6: Key Features On-Line Analytical Processing (OLAP) cubes automated aggregation speed-of-thought response times Open Architecture 100% Java J2EE Supports any JDBC data source MDX and XML/A Analysis Viewers Enables ad-hoc, interactive data exploration Ability to slice-and-dice, drill-down, and pivot Provides insights into problems or successes
Slide 7: How Mondrian Extends MySQL for OLAP Applications MySQL Provides Mondrian Provides Data storage SQL query execution Heavy-duty sorting, correlation, aggregation Integration point for all BI tools Dimensional view of data MDX parsing SQL generation Caching Higher-level calculations Aggregate awareness
Slide 8: Open Architecture Open Standards (Java, XML, MDX, XML/A, SQL) Cross Platform (Windows & Unix/Linux) J2EE Architecture Server Clustering Fault Tolerance Cube Schema XML Cube Schema XML Cube Schema XML Viewers Microsoft Excel (via Spreadsheet Services) Web Server JPivot servlet J2EE Application Server JPivot servlet Mondrian cube cube cube XML/A servlet Data Sources JDBC JNDI File or RDBMS Repository JDBC JDBC JDBC RDBMS RDBMS
Slide 9: <mondrian/jpivot demonstration>
Slide 10: Schemas and queries
Slide 11: A Mondrian schema consists of… A dimensional model (logical) Cubes & virtual cubes Shared & private dimensions Calculated measures in cube and in query language Parent-child hierarchies … mapped onto a star/snowflake schema (physical) Fact table Dimension tables Joined by foreign key relationships
Slide 12: Writing a Mondrian Schema Regular cubes, dimensions, hierarchies Shared dimensions Virtual cubes Parent-child hierarchies Custom readers Access-control <!-- Shared dimensions --> <Dimension name="Region"> <Hierarchy hasAll="true“ allMemberName="All Regions"> <Table name="QUADRANT_ACTUALS"/> <Level name="Region" column="REGION“ uniqueMembers="true"/> </Hierarchy> </Dimension> <Dimension name="Department"> <Hierarchy hasAll="true“ allMemberName="All Departments"> <Table name="QUADRANT_ACTUALS"/> <Level name="Department“ column="DEPARTMENT“ uniqueMembers="true"/> </Hierarchy> </Dimension> (Refer to http://mondrian.pentaho.org/documentation/schema.php )
Slide 13: Tools Schema Workbench Pentaho cube designer cmdrunner
Slide 14: MDX – Multi-Dimensional Expressions A language for multidimensional queries Plays the same role in Mondrian’s API as SQL does in JDBC SQL-like syntax SELECT {[Measures].[Unit Sales]} ON COLUMNS, {[Store].[USA], [Store].[USA].[CA]} ON ROWS FROM [Sales] WHERE [Time].[1997].[Q1] … but un-SQL-like semantics (Refer to http://mondrian.pentaho.org/documentation/mdx.php )
Slide 15: olap4j
Slide 16: OLAP APIs OLAP APIs that failed: OLAP Council’s MDAPI and OLAPI Sun’s JOLAP OLAP APIs that succeeded: Microsoft’s OLE DB for OLAP, ADOMD, XMLA Mondrian has an API for creating running MDX queries: Powerful and intuitive Features the MDX language Used by Mondrian’s XMLA provider, JPivot, other clients But it’s Mondrian-only
Slide 17: The problem with APIs Client 1 Client 2 Client 3 API 1 Server 1 API 2 Server 2 API 3 Server 3
Slide 18: The problem with APIs #2 Client 1 Client 2 Client 3 API 1 Server 1 API 2 Server 2 API 3 Server 3
Slide 19: The problem with APIs – the solution Client 1 Client 2 Client 3 Common API Driver 1 Server 1 Driver 2 Server 2 Driver 3 Server 3
Slide 20: olap4j olap4j aims to be the “JDBC for OLAP” An extension to JDBC Also inspired by ADOMD.NET Implementations for many OLAP servers Enable one client to work against many servers Break the ‘lock-in’ Encourage more businesses to ‘take a chance’ on open-source Backed by: Companies: Jedox, JasperSoft, Loyalty Matrix, LucidEra, Pentaho, Tensegrity, Tonbeller AG Projects: Halogen, JPivot, JRubik, Mondrian, OpenI, PALO Community at SourceForge.net
Slide 21: olap4j connecting to mondrian in-process import org.olap4j.*; Class.forName("mondrian.olap4j.MondrianOlap4jDriver"); OlapConnection connection = DriverManager.createConnection( "jdbc:mondrian:Jdbc=jdbc:mysql://localhost/foodmart;" + "JdbcUser=foodmart;JdbcPassword=foodmart;" + "Catalog=/WEB-INF/queries/FoodMart.xml;" + "Role='California manager'"); OlapConnection olapConnection = connection.unwrap(OlapConnection.class); OlapStatement statement = olapConnection.createOlapStatement(); OlapResult result = statement.execute( "SELECT {[Measures].[Unit Sales]} ON COLUMNS,\n" + " {[Product].Members} ON ROWS\n" + "FROM [Sales]");
Slide 22: olap4j connecting to SQL Server Analysis Services via XMLA import org.olap4j.*; Class.forName("org.olap4j.driver.xmla.XmlaOlap4jDriver"); OlapConnection connection = DriverManager.createConnection( "jdbc:xmla:Server=http://marmalade/xmla/msxisapi.dll;" + "Catalog=FoodMart;" + "Role='California manager'"); OlapConnection olapConnection = connection.unwrap(OlapConnection.class); OlapStatement statement = olapConnection.createOlapStatement(); OlapResult result = statement.execute( "SELECT {[Measures].[Unit Sales]} ON COLUMNS,\n" + " {[Product].Members} ON ROWS\n" + "FROM [Sales]");
Slide 23: olap4j architecture Client: In-process XMLA HTML AJAX Server: Mondrian in-process Mondrian via XMLA Microsoft SSAS via XMLA Other OLAP server via XMLA Other OLAP server via dedicated olap4j driver Mondrian XML/A servlet Mondrian Mondrian XML/A servlet Web client #1 Pure HTML web browser Web client #2 AJAX client in web browser Application server JPivot In-process client AJAX server olap4j olap4j driver for Mondrian Mondrian (in-process) olap4j driver for XML/A Other olap4j driver Microsoft SQL Server Analysis Services Other XML/A Server Data server #1 Data server #2 Data server #3
Slide 24: olap4 components Metadata Driver management Session Metadata MDX Transform & layout Driver Cube Dimension Hierarchy Level Member/ Measure Role Property Set Schema Session Connection MDX MDX parser Query MDX object model Result set Transform Sort/Rank Slice/Dice Layout Grid layout Chart layout Expand/ Collapse
Slide 25: olap4j/mondrian roadmap 2006 September olap4j 0.5 (draft) 2007 August – mondrian 2.4 2007 October – olap4j 0.9 (beta) 2008 February – olap4j driver for XMLA 2008 July – olap4j 1.0 2008 August – mondrian 3.1 featuring olap4j 1.0 API 2008 March – mondrian 3.0 featuring olap4j API
Slide 26: mondrian 3.0 features olap4j API Rollup policy Aggregate roles Allow distinct-count measures to be aggregated Improve dimension sharing JNDI in connect string Over 90 new MDX functions
Slide 27: Halogen Pentaho incubator project Slice/dice OLAP client Built using GWT  AJAX Built on olap4j  portable across OLAP servers
Slide 28: <halogen demonstration>
Slide 29: Case studies
Slide 30: Case Study: Frontier Airlines Frontier Airlines Key Challenges “The competition is intense in the airline industry and Frontier is committed to staying ahead of the curve by leveraging technology that will help us offer the best prices and the best flight experience…. [the application] fits right in with our philosophy of providing world-class performance at a low price.” Understanding and optimizing fares to ensure Maximum occupancy (no empty seats) Maximum profitability (revenue per seat) Pentaho Solution Pentaho Analysis (Mondrian) Chose Open Source RDBMS and Mondrian over Oracle 500 GB of data, 6 server cluster Results Comprehensive, integrated analysis to set strategic pricing Improved per-seat profitability (amount not disclosed) Why Pentaho Rich analytical and MDX functionality Cost of ownership
Slide 31: Pentaho at Loma Linda University Health Care Leading Healthcare Provider Key Challenges “Pentaho Customer Support has been exceptional. This is a strategic application at LLUHC, and working with Pentaho has accelerated our deployment and improved our overall application delivery.” Providing analytics for billing and operations supporting 500,000 patients and 600 doctors Pentaho Solution Pentaho Analysis Subscription Selected over Business Objects and Cognos Microsoft Windows Server with SQL Server Integrated with LDAP and Active Directory Results Comprehensive analysis of time periods, services provided, billing groups, physicians Centralized, secured, consistent information delivery (versus prior Excel-based system) Ability to drill and analyze down to the individual patient level Why Pentaho Open standards support and ease of integration Cost of ownership
Slide 32: The big picture
Slide 33: Business Intelligence Suite Mondrian OLAP Analysis tools: Pivot table Charting Dashboards ETL (extract/transform/load) Integration with operational reporting Integration with data mining Actions on operational data Design/tuning tools
Slide 34: Pentaho Open Source BI Offerings All available in a Free Open Source license
Slide 35: A Sample of Joint MySQL-Pentaho Users “Pentaho provided a robust, open source platform for our sales reporting application, and the ongoing support we needed. The experts at OpenBI provided outstanding services and training, and allowed us to deploy and start generating results very quickly.” “We selected Pentaho for its ease-ofuse. Pentaho addressed many of our requirements -- from reporting and analysis to dashboards, OLAP and ETL, and offered our business users the Excel-based access that they wanted.”
Slide 36: Next Steps and Resources Contact Information Julian Hyde, Chief Architect, jhyde@pentaho.com More information http://www.pentaho.org and http://mondrian.pentaho.org Pentaho Community Forum http://community.pentaho.org Go to Developer Zone Discussions Pentaho BI Platform including Mondrian http://www.pentaho.org/download/latest Mondrian OLAP Library only http://sourceforge.net/project/showfiles.php?group_id=35302
Slide 37: Thank you for attending!