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Making MySQL Great for Business Intelligence Robin Schumacher VP Products Calpont
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object]
A Quick Overview of Business Intelligence
What is Business Intelligence? Business Intelligence (BI)  refers to skills, processes, technologies, applications and practices used to support decision making. BI technologies provide historical, current, and predictive views of business operations. Common functions of Business Intelligence technologies are reporting, online analytical processing, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics.
Why Business Intelligence? ,[object Object],[object Object],[object Object]
Overview of Most BI Frameworks OLTP Files/XML Log Files Operational Source Data Staging  or ODS ETL Final  ETL Reporting, BI, Notification Layer Ad-Hoc Dashboards Reports Notifications Users Staging Area Data Warehouse Warehouse Archive Purge/Archive Data Warehouse and Metadata Management
Simple Reporting Databases OLTP Database Read Shard One Reporting Database Application Servers End Users ETL Data Archiving Link Replication
Building the Right Technical Foundation
What is the Key Component for Success? In other words, what you do with your MySQL Server – in terms of physical design, schema design, and performance design – will be the biggest factor on whether a BI system hits the mark… * Philip Russom, “Next Generation Data Warehouse Platforms”, TDWI, 2009.  *
What Technology Decisions are Being Made? * Philip Russom, “Next Generation Data Warehouse Platforms”, TDWI, 2009.  *
What General MySQL Design Decisions Help Success?
First – Get/Use a Modeling Tool
Horizontal Partitioning Model
Read Sharding / Horizontal Partitioning
Vertical Partitioning Model
General List of Top BI Design Decisions ,[object Object],[object Object],[object Object],[object Object],[object Object]
Core BI Features for MySQL ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Storage Engines Internal to MySQL MyISAM Archive Memory CSV ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Also:Merge for pre-5.1 partitioning
Partitioning and Performance (5.1+) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],90%  Response Time Reduction
Index Creation and Placement ,[object Object],[object Object],[object Object],[object Object],[object Object]
Row vs. Column Engines / Databases
Column vs. Row Orientation  A column-oriented architecture looks the same on the surface, but stores data differently than legacy/row-based databases…
Why a Column Database? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Why a Column Database? "If you're bringing back all the columns, a column-store database isn't going to perform any better than a row-store DBMS, but analytic applications are typically looking at all rows and only a few columns. When you put that type of application on a column-store DBMS,  it outperforms anything that doesn't take a column-store approach ."   - Donald Feinberg, Gartner Group
Why Not a Column Database? ,[object Object],[object Object],[object Object],[object Object]
What is Calpont’s InfiniDB? InfiniDB is an open source, column-oriented database architected to handle data warehouses, data marts, analytic/BI systems, and other read-intensive applications. It delivers true scale up (more CPU’s/cores, RAM) and massive parallel processing (MPP) scale out capabilities for MySQL users. Linear performance gains are achieved when adding either more capabilities to one box or using commodity machines in a scale out configuration.  Scale up Scale Out
InfiniDB vs. a Leading Row RDBMS 2 TB’s of raw data; 16 CPU 16GB RAM 14 SAS 15K RPM RAID-0 512MB Cache
Percona’s Test of Column Databases 610 GB of raw data; 8 Core Machine http://www.mysqlperformanceblog.com/2010/01/07/star-schema-bechmark-infobright-infinidb-and-luciddb/
Calpont Solutions Calpont Analytic Database Server Editions Calpont Analytic Database Solutions InfiniDB  Community Server Column-Oriented Multi-threaded Terabyte Capable Single Server InfiniDB Enterprise Server Scale out / Parallel Processing Automatic Failover InfiniDB Enterprise Solution Monitoring 24x7 Support Auto Patch Management Alerts & SNMP Notifications Hot Fix Builds Consultative Help
InfiniDB Community & Enterprise Server Comparison Yes No Multi-Node, MPP scale out capable w/ failover Formal Production Support Forums Only Support Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes InfiniDB Community Yes INSERT/UPDATE/DELETE (DML) support Yes Transaction support (ACID compliant) Yes MySQL front end Yes Logical data compression Yes High-Speed bulk loader w/ no blocking queries while loading Yes Multi-threaded engine (queries/writes will use all CPU’s/cores on box) Yes Crash-recovery Yes Terabyte database capable Yes High concurrency supported Yes Alter Table with online add column capability  Yes MVCC support – snapshot read (readers don’t block writers) Yes Automatic vertical (column) and logical horizontal partitioning of data Yes No indexing necessary Yes Column-oriented InfiniDB Enterprise Core Database Server Features
For More Information ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],www.infinidb.org www.calpont.com

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Making MySQL Great For Business Intelligence

  • 1. Making MySQL Great for Business Intelligence Robin Schumacher VP Products Calpont
  • 2.
  • 3. A Quick Overview of Business Intelligence
  • 4. What is Business Intelligence? Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making. BI technologies provide historical, current, and predictive views of business operations. Common functions of Business Intelligence technologies are reporting, online analytical processing, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics.
  • 5.
  • 6. Overview of Most BI Frameworks OLTP Files/XML Log Files Operational Source Data Staging or ODS ETL Final ETL Reporting, BI, Notification Layer Ad-Hoc Dashboards Reports Notifications Users Staging Area Data Warehouse Warehouse Archive Purge/Archive Data Warehouse and Metadata Management
  • 7. Simple Reporting Databases OLTP Database Read Shard One Reporting Database Application Servers End Users ETL Data Archiving Link Replication
  • 8. Building the Right Technical Foundation
  • 9. What is the Key Component for Success? In other words, what you do with your MySQL Server – in terms of physical design, schema design, and performance design – will be the biggest factor on whether a BI system hits the mark… * Philip Russom, “Next Generation Data Warehouse Platforms”, TDWI, 2009. *
  • 10. What Technology Decisions are Being Made? * Philip Russom, “Next Generation Data Warehouse Platforms”, TDWI, 2009. *
  • 11. What General MySQL Design Decisions Help Success?
  • 12. First – Get/Use a Modeling Tool
  • 14. Read Sharding / Horizontal Partitioning
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  • 21. Row vs. Column Engines / Databases
  • 22. Column vs. Row Orientation A column-oriented architecture looks the same on the surface, but stores data differently than legacy/row-based databases…
  • 23.
  • 24. Why a Column Database? "If you're bringing back all the columns, a column-store database isn't going to perform any better than a row-store DBMS, but analytic applications are typically looking at all rows and only a few columns. When you put that type of application on a column-store DBMS, it outperforms anything that doesn't take a column-store approach ." - Donald Feinberg, Gartner Group
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  • 26. What is Calpont’s InfiniDB? InfiniDB is an open source, column-oriented database architected to handle data warehouses, data marts, analytic/BI systems, and other read-intensive applications. It delivers true scale up (more CPU’s/cores, RAM) and massive parallel processing (MPP) scale out capabilities for MySQL users. Linear performance gains are achieved when adding either more capabilities to one box or using commodity machines in a scale out configuration. Scale up Scale Out
  • 27. InfiniDB vs. a Leading Row RDBMS 2 TB’s of raw data; 16 CPU 16GB RAM 14 SAS 15K RPM RAID-0 512MB Cache
  • 28. Percona’s Test of Column Databases 610 GB of raw data; 8 Core Machine http://www.mysqlperformanceblog.com/2010/01/07/star-schema-bechmark-infobright-infinidb-and-luciddb/
  • 29. Calpont Solutions Calpont Analytic Database Server Editions Calpont Analytic Database Solutions InfiniDB Community Server Column-Oriented Multi-threaded Terabyte Capable Single Server InfiniDB Enterprise Server Scale out / Parallel Processing Automatic Failover InfiniDB Enterprise Solution Monitoring 24x7 Support Auto Patch Management Alerts & SNMP Notifications Hot Fix Builds Consultative Help
  • 30. InfiniDB Community & Enterprise Server Comparison Yes No Multi-Node, MPP scale out capable w/ failover Formal Production Support Forums Only Support Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes InfiniDB Community Yes INSERT/UPDATE/DELETE (DML) support Yes Transaction support (ACID compliant) Yes MySQL front end Yes Logical data compression Yes High-Speed bulk loader w/ no blocking queries while loading Yes Multi-threaded engine (queries/writes will use all CPU’s/cores on box) Yes Crash-recovery Yes Terabyte database capable Yes High concurrency supported Yes Alter Table with online add column capability Yes MVCC support – snapshot read (readers don’t block writers) Yes Automatic vertical (column) and logical horizontal partitioning of data Yes No indexing necessary Yes Column-oriented InfiniDB Enterprise Core Database Server Features
  • 31.