choosing a computing architecture chapter 8. architectural requirements...
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Choosing a Computing Architecture
Chapter 8
Architectural Requirements
Scalability Manageability Availability Extensibility
Flexibility Integration
User Business
Budget Technology
Strategy for Architecture Definition
Obtain existing architecture plansObtain existing capacity plansDocument existing interfacesPrepare capacity planPrepare technical architectureDocument operating system requirementsDevelop recovery plansDevelop security and control plansCreate architectureCreate technical risk assessment
Hardware Architecture
Involve all expertsNew technologyOld technologyNetworking
Hardware Architectures
RobustAvailableReliableExtensibleScalableSupportableRecoverableParallel
VLM64-bitConnectiveOpen
Hardware Architectures
SMPClusterMPPNUMAHybrids use SMP and MPP
Evaluation Criteria
Determine the platform for your needs
SMP Clusters NUMA MPP
HighLow Scalability
Maturity Low
High
Parallel Processing
Parallel daily operations
Shared resources - Memory - Disk - NothingLoosely 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 queriesScalability important
SMP
Communication by shared memoryDisk controllers accessible to all CPUsProven technology
Shared memory
CPU CPU CPUCPU
Common bus
Shared disks
SMP
Benefits: - High concurrency - Workload balancing - Moderate scalability - Easy administrationLimitations: - Memory (cluster for improvements) - Bandwidth
NUMA
Loosely coupled shared memory
CPU CPU CPU CPU CPU CPU
Sharedmemory
Sharedmemory
Disk Disk
Nonuniformmemory access
Shared bus
NUMABenefits: - Fully scalable, incremental additions to disk, CPU, and bandwidth - Performs better than MPP - Suited for Oracle serverLimitations: - The technology is new and less proven - You need new tools for easy system management - NUMA is more expensive than SMP
Clusters
CPU CPU CPU
Sharedmemory
Node 1CPU CPU CPU
Sharedmemory
Node 2CPU CPU CPU
Sharedmemory
Node 3
Common high-speed busCommon 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 architectureMany nodesFast accessExclusive memory on a nodeLow cost per nodeScalablenCUBE configuration
MPP Benefits
Unlimited incremental growthVery scalableFast accessLow cost per nodeGood for DSS
MPP Limitations
Rigid partitioningCache consistencyRestricted disk accessHigh memory cost per nodesHigh management burdenCareful 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 separationDistributed structures: - Two-tier - Three-tier - Four-tier (and more)
Middleware
Technologies for integration
Gateway
Database Server Requirements
RobustAvailableReliableExtensibleScalableSupportableRecoverableParallel
Parallelism
DatabaseQueryLoadIndexSortBackupRecovery
Further Considerations
Optimization strategyPartitioning strategySummarization strategyIndexing techniquesHardware and software scalabilityAvailabilityAdministration
Server Environments
Operationalservers
Warehouseservers
Data martservers
•Open DBMS•Network, relational, hierarchical•Mainframe proprietary DBMS•Oracle, IMS, DB2, VSAM, Rdb, Non Stop SQL, RMS
•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
Parallel Processing
A large task broken into smaller tasks:Concurrent executionOne or more processors
Processor 1
Processor 1Processor 2Processor 3Processor 4
Parallel
Elapsed timeNot parallel
Parallel Database
Increased speedImproved scalability
Performance gains - Availability - Flexibility - More users
Processor 1Processor 2Processor 3Processor 4
Parallel
Parallel Query
SQL code split among server processes.Sub-Query
Sub-Query
Sub-Query
Query
Parallel Load
Bypass SQL processing to speed throughput.
Parallel Processing
Index Reduces the time to createSort Allocates memory in cache efficientlyBackup Runs simultaneously from any node - Offline - OnlineRecovery Runs simultaneously from redo logsSummaries Uses the CREATE TABLES AS SELECT statement
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
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