網(wǎng)格數(shù)據(jù)庫訪問和集成服務(wù)DAIS.ppt

網(wǎng)格數(shù)據(jù)庫訪問和集成服務(wù) 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,傳統(tǒng)的分布環(huán)境下數(shù)據(jù)管理系統(tǒng)和 網(wǎng)格環(huán)境中數(shù)據(jù)管理系統(tǒng)的區(qū)別,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,信息技術(shù)的演變,Mainframe 大型主機,部門級服務(wù)器,“目前 IT 部門運行效率十分低下，通常只利用了總?cè)萘康男〔糠帧?Frank E. Gillett Forrester 研究公司，2002年10月,當(dāng)前IT所面臨的問題,信息孤島 為最大負載而配置 伸縮性有限 可用性 99.x% 安全控制分散 成本不斷上漲 影響所有行業(yè),降低IT 成本,昂貴的硬件設(shè)備 附加成本亦十分昂貴 單點故障 提供企業(yè)級服務(wù)成本高昂,低成本模塊化設(shè)備 附加成本低 無單點故障 提供企業(yè)級服務(wù)成本低,大型專用服務(wù)器,Oracle 網(wǎng)格技術(shù),企業(yè)級網(wǎng)格計算意味著,CEOs 降低費用 隨用隨付 IT 經(jīng)理 提高可用性 提高服務(wù)質(zhì)量 IT 管理人員 提高自動化程度和生產(chǎn)率 減少錯誤,對開發(fā)人員和獨立軟件商意味著,無須更改程序代碼 應(yīng)用系統(tǒng)的管理功能更強 處理過程自動化 數(shù)據(jù)庫自動化管理 利用共有服務(wù)功能 如：身份認證等 硬件系統(tǒng)的成本更低,Oracle 網(wǎng)格計算結(jié)構(gòu),計算機資源共享池 虛擬與信息提供 負載均衡 高質(zhì)量服務(wù) 自動化,基于規(guī)則的負載均衡技術(shù),實現(xiàn)于數(shù)據(jù)庫和應(yīng)用服務(wù)器集群中 基于規(guī)則動態(tài)分配服務(wù)器資源 自動分派服務(wù)請求 一個服務(wù)器出現(xiàn)故障，處理過程自動分派到其他服務(wù)器上 處理量變化時，重新分配服務(wù)器容量,網(wǎng)格管理,統(tǒng)一管理和監(jiān)控 利用標(biāo)準(zhǔn)的規(guī)則進行管理 系統(tǒng)配置 性能調(diào)整 安全控制 自動化處理,應(yīng)用系統(tǒng),多個系統(tǒng),現(xiàn)有應(yīng)用系統(tǒng) 不需要修改 就可以利用網(wǎng)格技術(shù),套裝應(yīng)用系統(tǒng) 客戶定制的應(yīng)用系統(tǒng) 所有的應(yīng)用系統(tǒng),數(shù)據(jù)庫集群和應(yīng)用服務(wù)器集群： 經(jīng)受考驗的成熟技術(shù),全球成千上萬用戶 運行于所有平臺上,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