Choosing a Computing Architecture

1. Choosing a Computing Architecture Chapter 8

2. Architectural Requirements Scalability Manageability Availability Extensibility Flexibility Integration User Business Technology Budget

3. Strategy for Architecture Definition • Obtain existing architecture plans • Obtain existing capacity plans • Document existing interfaces • Prepare capacity plan • Prepare technical architecture • Document operating system requirements • Develop recovery plans • Develop security and control plans • Create architecture • Create technical risk assessment

4. Hardware Architecture Involve all experts • New technology • Old technology • Networking

5. Hardware Architectures • Robust • Available • Reliable • Extensible • Scalable • Supportable • Recoverable • Parallel • VLM • 64-bit • Connective • Open

6. Hardware Architectures • SMP • Cluster • MPP • NUMA • Hybrids use SMP and MPP

7. Evaluation Criteria Determine the platform for your needs SMP Clusters NUMA MPP High Scalability Low High Maturity Low

8. Parallel Processing • Parallel daily operations • Shared resources - Memory - Disk - Nothing • Loosely or tightly coupled Database Application Hardware Operating system

9. Making the Right Choice • Requirements differ from operational systems • Benchmark - Available from vendors - Develop your own - Use realistic queries • Scalability important

10. SMP • Communication by shared memory • Disk controllers accessible to all CPUs • Proven technology CPU CPU CPU CPU Common bus Shared memory Shared disks

11. SMP • Benefits: - High concurrency - Workload balancing - Moderate scalability - Easy administration • Limitations: - Memory (cluster for improvements) - Bandwidth

12. NUMA Loosely coupled shared memory CPU CPU CPU CPU CPU CPU Shared bus Shared memory Shared memory Nonuniform memory access Disk Disk

13. NUMA • Benefits: - Fully scalable, incremental additions to disk, CPU, and bandwidth - Performs better than MPP - Suited for Oracle server • Limitations: - The technology is new and less proven - You need new tools for easy system management - NUMA is more expensive than SMP

14. Clusters Node 1 Node 2 Node 3 CPU CPU CPU CPU CPU CPU CPU CPU CPU Shared memory Shared memory Shared memory Common high-speed bus Common high-speed bus

15. Clusters • Shared disk, loosely coupled • Dedicated memory • High-speed bus • Shared resources • SMP node • Benefits: - High availability - Single database concept, incremental growth • Limitations: - Scalability, internode synchronization needed • - Operating system overhead

16. MPP CPU CPU CPU CPU Memory Memory Memory Memory Disk Disk Disk Disk

17. MPP • A shared nothing architecture • Many nodes • Fast access • Exclusive memory on a node • Low cost per node • Scalable • nCUBE configuration

18. MPP Benefits • Unlimited incremental growth • Very scalable • Fast access • Low cost per node • Good for DSS

19. MPP Limitations • Rigid partitioning • Cache consistency • Restricted disk access • High memory cost per nodes • High management burden • Careful data placement

20. Windows NT Architecture based on the client-server model • Benefits: - Include built-in Web services - Scalability - Ease of management and control • Limitations: - Not as secure - Cannot execute programs remotely - Lack linear scalability beyond four processors - Addressing space for applications is limited to two gigabytes

21. Architectural Tiers • Tiered structures: - Modular - Logical separation • Distributed structures: - Two-tier - Three-tier - Four-tier (and more)

22. Middleware Technologies for integration Gateway

23. Database Server Requirements • Robust • Available • Reliable • Extensible • Scalable • Supportable • Recoverable • Parallel

24. Parallelism • Database • Query • Load • Index • Sort • Backup • Recovery

25. Further Considerations • Optimization strategy • Partitioning strategy • Summarization strategy • Indexing techniques • Hardware and software scalability • Availability • Administration

26. Server Environments Operational servers Warehouse servers Data mart servers • Open DBMS • Relational • General purpose and • warehouse-specific • DBMS • Oracle, Informix, • Sybase, IBM DB2, • NCR/AT&T Teradata • Red Brick • Open DBMS • Relational and • multidimensional • General purpose • and warehouse • specific DBMS • Oracle, Oracle • Express, Arbor • Essbase, MS SQL • Server, NT • Open DBMS • Network, relational, • hierarchical • Mainframe • proprietary DBMS • Oracle, IMS, DB2, • VSAM, Rdb, Non • Stop SQL, RMS

27. Parallel Processing A large task broken into smaller tasks: • Concurrent execution • One or more processors Elapsed time Not parallel Processor 1 Parallel Processor 1 Processor 2 Processor 3 Processor 4

28. Parallel Database • Increased speed • Improved scalability • Performance gains - Availability - Flexibility - More users Parallel Processor 1 Processor 2 Processor 3 Processor 4

29. Parallel Query SQL code split among server processes. Sub- Query Sub- Query Query Sub- Query

30. Parallel Load Bypass SQL processing to speed throughput.

31. Parallel Processing • Index Reduces the time to create • Sort Allocates memory in cache efficiently • Backup Runs simultaneously from any node - Offline - Online • Recovery Runs simultaneously from redo logs • Summaries Uses the CREATE TABLES AS SELECT statement

32. Summary This lesson discussed the following topics: • Outlining the basic architecture requirements for a warehouse • Highlighting the benefits and limitations of all the different hardware architectures