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Choosing a Computing Architecture Chapter 8 Architectural Requirements Scalability Manageability Flexibility User Budget Availability Extensibility Integration Business Technology 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 Hardware Architecture Involve all experts New technology Old technology Networking Hardware Architectures Robust Available Reliable Extensible Scalable Supportable Recoverable Parallel VLM 64-bit Connective Open Hardware Architectures SMP Cluster MPP NUMA Hybrids use SMP and MPP Evaluation Criteria Determine the platform for your needs SMP Clusters NUMA MPP High Scalability Low High Maturity Low Parallel Processing Parallel daily operations Shared resources - Memory - Disk - Nothing Loosely or tightly coupled Database Application Hardware Operating system Making the Right Choice Requirements differ from operational systems Benchmark - Available from vendors - Develop your own - Use realistic queries Scalability important SMP Communication by shared memory Disk controllers accessible to all CPUs Proven technology CPU CPU CPU CPU Common bus Shared memory Shared disks SMP Benefits: - High concurrency - Workload balancing - Moderate scalability - Easy administration Limitations: - Memory (cluster for improvements) - Bandwidth NUMA Loosely coupled shared memory CPU CPU CPU CPU CPU CPU Shared bus Shared memory Disk Nonuniform memory access Shared memory Disk 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 Clusters Node 1 CPU CPU CPU Node 2 CPU CPU CPU Node 3 CPU CPU CPU Shared memory Shared memory Shared memory Common high-speed bus Common high-speed bus 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 MPP CPU CPU CPU CPU Memory Memory Memory Memory Disk Disk Disk Disk MPP A shared nothing architecture Many nodes Fast access Exclusive memory on a node Low cost per node Scalable nCUBE configuration MPP Benefits Unlimited incremental growth Very scalable Fast access Low cost per node Good for DSS MPP Limitations Rigid partitioning Cache consistency Restricted disk access High memory cost per nodes High management burden Careful data placement 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 Architectural Tiers Tiered structures: - Modular - Logical separation Distributed structures: - Two-tier - Three-tier - Four-tier (and more) Middleware Technologies for integration Gateway Database Server Requirements Robust Available Reliable Extensible Scalable Supportable Recoverable Parallel Parallelism Database Query Load Index Sort Backup Recovery Further Considerations Optimization strategy Partitioning strategy Summarization strategy Indexing techniques Hardware and software scalability Availability Administration Server Environments Operational servers •Open DBMS •Network, relational, hierarchical •Mainframe proprietary DBMS •Oracle, IMS, DB2, VSAM, Rdb, Non Stop SQL, RMS Warehouse servers •Open DBMS •Relational •General purpose and warehouse-specific DBMS •Oracle, Informix, Sybase, IBM DB2, NCR/AT&T Teradata Red Brick Data mart servers •Open DBMS •Relational and multidimensional •General purpose and warehouse specific DBMS •Oracle, Oracle Express, Arbor Essbase, MS SQL Server, NT Parallel Processing A large task broken into smaller tasks: Concurrent execution One or more processors Elapsed time Processor 1 Parallel Processor 1 Processor 2 Processor 3 Processor 4 Not parallel Parallel Database Increased speed Improved scalability Performance gains - Availability - Flexibility - More users Processor 1 Processor 2 Processor 3 Processor 4 Parallel Parallel Query SQL code split among server processes. SubQuery Query SubQuery SubQuery Parallel Load Bypass SQL processing to speed throughput. Parallel Processing Reduces the time to create Allocates memory in cache efficiently Runs simultaneously from any node - Offline - Online Recovery Runs simultaneously from redo logs Summaries Uses the CREATE TABLES AS SELECT statement Index Sort Backup 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