网格数据库访问和集成服务DAIS.ppt

网格数据库访问和集成服务 DAIS,Data Grids,DataGrid : A dynamic logical namespace that enables coordinated sharing of heterogeneous distributed storage resources and digital entities based on local and global policies across administrative domains in a virtual enterprise. DataGrid Logical name space for location independent identifiers Abstractions for storage repositories, information repositories, and access APIs Latency management,Data Characteristics in Grid,Mostly unstructured data, heterogeneous resources Images, files, semi-structured, databases, streams, File systems, SAN, FTP sites, web servers, archives Community-Based Shared amongst one or more communities Meta-data Different meta-data schemas for the same data Different notations, ontologies Sensitive to Sharing,Data Grid Transparencies,Access data without knowing the type of storage Storage repository abstraction Find data without knowing the identifier Descriptive attributes Access data without knowing the location Logical name space Retrieve data using your preferred API Access abstraction Provide transformations for any data collection Data behavior abstraction,Logical Layers (bits,data,information,),Storage Resource Transparency,Storage Location Transparency,Data Identifier Transparency,Data Replica Transparency,Virtual Data Transparency,Semantic data Organization (with behavior),Inter-organizational Information Storage Management,Storage Resource Transparency,Standard operations at storage repositories POSIX like operations on all resources Storage specific operations Databases - bulk metadata access Object ring buffers - object based access Hierarchical resource managers - status and staging requests,DAIS- Requirements & Functionalities,Key Access & Integration Functionalities: Publication and Discovery Statements (Data Operations) Structured Data Transport Data Transformation Transactions Metadata Management: Operation & Performance Data Replication Connections and Sessions Integration,DAIS Functional Scoping,Publishing and Discovery Service discovery via a registry Data service registry structure and content Data service description Database contents description Logical and Physical schema, physical characteristics Database capability Languages, features, characteristics Terminology and structure of descriptions,DAIS Functional Scoping,Statements Access to RDBMS, XML, other databases Operations Prepared and dynamic statements Native DML, DDL, Context, Procedures/Packages Scripted operations Synchronous & asynchronous statement interfaces Preparation/validation, application, delivery Notification Event and informational Natural Query language,DAIS Functional Scoping,Structured Data Transport Delivery from one source to one or more specified destinations along a series of channels Temporary storage during transport Alternative delivery modes Streaming, multicast Delivery monitoring and notifications Support for different protocols for delivery along different channels Systematic methods of encryption or compression on selected channels,DAIS Functional Scoping,Data Transformation Before, during, after statement execution Restructuring Formatting, sequencing Schema change Restructuring, naming, constraints Conversion Units, coordinate system, algorithmic (e.g. Fourier) Composition with computational services,DAIS Functional Scoping,Transactions DBMS capability E.g. Set transaction, commit, rollback Event and informational notification Distributed transactions Heterogeneous two-phase commit Relaxed transaction models Core activity service model, collaborations Definition of new transaction models,DAIS Functional Scoping,Authentication, Access Control, Accounting Basic cost model DBMS capability, e.g.resources used Delegation of fine grained access rights Access based role model,DAIS Functional Scoping,Metadata Technical metadata Location, physical schema, data characteristics, owner, version, access methods Database capabilities and extensions Contextual metadata Logical schema, classifications, terminologies, ontologies, derived data Context for schema mapping Schema conversion and evolution,DAIS Functional Scoping,Management: Operations and Performance Exploit DBMS capabilities RAMPS Reorganisation, backup/recovery, user management,DAIS Functional Scoping,Data Replication Exploit DBMS capabilities Replication and synchronisation features Core replication capability Data definition, manipulation, transport operations,DAIS Functional Scoping,Connections and Sessions Further investigation required,DAIS Functional Scoping,Integration Highly dynamic federation Alternate source selection form available replicas Facilitate optimisation Semantic based integration,Traditional Distributed Database Management System and Their Limitations,Challenges to Distributed Database Management System Scale Heterogeneity Distribution Autonomy Transparency,Federated DBs,Data Distribution No Common Schema A federated DBMS serves as a middleware Solved Some Problem partially: Heterogeneity transparency Distribution transparency,Traditional Distributed Data Management System and Their Limitations,Inter-Operations Using ODBC/JDBC/OLE DB,传统的分布环境下数据管理系统和 网格环境中数据管理系统的区别,Grid-enable Database,Database Requirements of Grid Application The most important requirements DBS must support the,Grid standards: relevant, existing and emerging ,for example the Grid Security Infrastructure Other important requirements Retrieval(Grid IR) Scalability Handling unpredictable usage Meta-driven access Multiple Database Federation,Grid-enable Database,Collective view of Inter-organizational data Operations on grid space Local autonomy and global state consistency Collaborative communities Multiple administrative domains or “Grid Zones” Self-describing and self-manipulating data Horizontal and vertical behavior Loose coupling between data and behavior (dynamically) Relationships between a digital entity and its Physical locations, Logical names, Meta-data, Access control, Behavior, “Grid Zones”.,Need for Standard DGL,Database,SQL,Grid-Enable Database,DDL, DML, DQL,信息技术的演变,Mainframe 大型主机,部门级服务器,“目前 IT 部门运行效率十分低下，通常只利用了总容量的小部分”,Frank E. Gillett Forrester 研究公司，2002年10月,当前IT所面临的问题,信息孤岛 为最大负载而配置 伸缩性有限 可用性 99.x% 安全控制分散 成本不断上涨 影响所有行业,降低IT 成本,昂贵的硬件设备 附加成本亦十分昂贵 单点故障 提供企业级服务成本高昂,低成本模块化设备 附加成本低 无单点故障 提供企业级服务成本低,大型专用服务器,Oracle 网格技术,企业级网格计算意味着,CEOs 降低费用 随用随付 IT 经理 提高可用性 提高服务质量 IT 管理人员 提高自动化程度和生产率 减少错误,对开发人员和独立软件商意味着,无须更改程序代码 应用系统的管理功能更强 处理过程自动化 数据库自动化管理 利用共有服务功能 如：身份认证等 硬件系统的成本更低,Oracle 网格计算结构,计算机资源共享池 虚拟与信息提供 负载均衡 高质量服务 自动化,基于规则的负载均衡技术,实现于数据库和应用服务器集群中 基于规则动态分配服务器资源 自动分派服务请求 一个服务器出现故障，处理过程自动分派到其他服务器上 处理量变化时，重新分配服务器容量,网格管理,统一管理和监控 利用标准的规则进行管理 系统配置 性能调整 安全控制 自动化处理,应用系统,多个系统,现有应用系统 不需要修改 就可以利用网格技术,套装应用系统 客户定制的应用系统 所有的应用系统,数据库集群和应用服务器集群： 经受考验的成熟技术,全球成千上万用户 运行于所有平台上,Transaction Processing Council (TPC), . As of December 8, 2003: Sixteen-node HP Integrity rx5670 server cluster, each with 4 Itanium 2 1.5 GHz processors, 1,184,893.38 tpmC, $5.52/tpmC, available April 30, 2004. HP Integrity Superdome server with 64 Itanium 2 1.5