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Delivery: <= 3 days. True-PDF full-copy in English will be manually translated and delivered via email. GB/T 35589-2017: Information technology -- Big data -- Technical reference model Status: Valid
Basic dataStandard ID: GB/T 35589-2017 (GB/T35589-2017)Description (Translated English): Information technology -- Big data -- Technical reference model Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: L67 Classification of International Standard: 35.240.70 Word Count Estimation: 10,132 Date of Issue: 2017-12-29 Date of Implementation: 2018-07-01 Regulation (derived from): National Standard Announcement 2017 No. 32 Issuing agency(ies): General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China GB/T 35589-2017: Information technology -- Big data -- Technical reference model---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.Information technology - Big data - Technical reference model ICS 35.240.70 L67 National Standards of People's Republic of China Information technology big data technology reference model 2017-12-29 released 2018-07-01 implementation General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China Issued by the National Standardization Administration of China Table of contentsForeword Ⅰ 1 Scope 1 2 Normative references 1 3 Terms and definitions 1 4 Abbreviations 2 5 Purpose and Objectives of Big Data Reference Architecture 2 6 Overview of Big Data Reference Architecture 2 7 Composition of Big Data Reference Architecture 4 7.1 System Coordinator 4 7.2 Data provider 4 7.3 Big Data Application Provider 4 7.3.1 Overview 4 7.3.2 Collection 4 7.3.3 Pretreatment 4 7.3.4 Analysis 4 7.3.5 Visualization 4 7.3.6 Access 4 7.4 Big Data Framework Provider 5 7.4.1 Overview 5 7.4.2 Infrastructure 5 7.4.3 Platform 5 7.4.4 Processing Framework 5 7.4.5 Information exchange/communication 5 7.4.6 Resource Management 5 7.5 Data Consumer 5 7.6 Security and privacy 5 7.7 Management 6ForewordThis standard was drafted in accordance with the rules given in GB/T 1.1-2009. Please note that some of the contents of this document may involve patents. The issuing agency of this document is not responsible for identifying these patents. This standard was proposed and managed by the National Information Technology Standardization Technical Committee (SAC/TC28). Drafting organizations of this standard. China Electronics Standardization Institute, Inspur Software Group Co., Ltd., Huawei Technologies Co., Ltd., Chengdu Qin Smart Digital Technology Co., Ltd., China Internet Network Information Center, National Information Center, Tongfang Co., Ltd., China Bidder Software Co., Ltd. Company, Tsinghua University, Shandong Zhongchuang Software Commercial Middleware Co., Ltd., Inspur Electronic Information Industry Co., Ltd., IGRS Information Technology Engineering Center Co., Ltd., East China Normal University, Beijing Century Internet Broadband Data Center Co., Ltd., Beijing AsiaInfo Smart Data Technology Co., Ltd. The company, Peking University, Renmin University of China, ZTE Corporation, Beijing Baixin Information Technology Co., Ltd. The main drafters of this standard. Mei Hong, Gao Lin, Dai Hong, Wu Dongya, Du Xiaoyong, Che Pinjue, Wu Jianming, Zhao Jinghua, Chen Hai, Zhang Qun, Wei Fenglin, Zhao Junfeng, Huang Xianzhi, Wang Jianhua, Yang Lili, Fu Yusheng, Kong Ning, Lu Xin, Wu Chen, Dong Junping, Wu Jiqing, Wang Chaokun, Wang Jianmin, He Zhongsheng, Su Zhiyuan, Wu Nan, Zhao Jiang, Zhang Weihua, Wu Yonghe, Zhou Xingjian, Chen Licang, Li Bing, Cao Haojia, Wang Jing, Xu Yang, Zhang Zhanxin, Li Yiang, Fu Haifang, Zhu Song, Liu Yufeng, Wu Zhigang, Zhang Anwen, Wang Dong, Hu Xuanlai. Information technology big data technology reference model1 ScopeThis standard describes the reference architecture of big data, including roles, activities and functional components and the relationship between them. This standard applies to the understanding of the complex operations of big data, and can provide a basis for the formulation of a series of big data standards.2 Normative referencesThe following documents are indispensable for the application of this document. For dated reference documents, only the dated version applies to this article Pieces. For undated reference documents, the latest version (including all amendments) is applicable to this document. GB/T 35295 Information Technology Big Data Terminology3 Terms and definitionsThe following terms and definitions defined in GB/T 35295 apply to this document. 3.1 Big Data Reference Architecture bigdatareferencearchitecture A high-level conceptual model used as a tool to facilitate open discussions on the inherent requirements, design structure, and operation of big data. Note. The generally recognized big data reference architecture generally includes system coordinators, data providers, big data application providers, big data framework providers and Five logical functional components such as data consumers. 3.2 System coordinator systemorchestrator A logical functional component in the big data reference architecture that defines the required data application activities and integrates them into a runnable vertical In the system. Note. The system coordinator can be human, software or both. 3.3 Dataprovider A logical functional component in the big data reference architecture that introduces new data or information into the big data system. 3.4 Bigdataapplicationprovider A logical functional component in the big data reference architecture that performs data life cycle operations to meet the requirements defined by the system coordinator And security and privacy protection needs. 3.5 Big data framework provider bigdataframeworkprovider A logical functional component in the big data reference architecture that establishes a computing framework in which to execute transformation applications while protecting Data integrity and privacy. 3.6 Dataconsumer A logical functional component in the big data reference architecture is the end user or other users who use the application provided by the big data application provider. system. 3.7 Data scientist Data science professionals; they have sufficient knowledge of business requirements management mechanisms, domain knowledge, analytical skills, and Software and systems engineering knowledge to manage the end-to-end data process at each stage of the data life cycle.4 AbbreviationsThe following abbreviations apply to this document. BDRA. Big Data Reference Architecture (BigDataReference Architecture) POSIX. Portable Operating System Interface (PortableOperatingSystemInterface)5 The purpose and objectives of the big data reference architectureBDRA in this standard provides an architecture for effectively describing big data roles, activities and functional components. The purposes of BDRA include. ---Provide a common language for communicating big data technology for various stakeholders; --- Encourage big data practitioners to comply with common standards, norms and models; ---Provide a consistent technical implementation method for solving similar problem sets. The purpose of BDRA is to facilitate the understanding of the complex operations of big data. It does not represent a specific big data system Architecture; instead, it is a tool that uses a general architecture to describe, discuss, and develop the architecture of a specific system. BDRA is a general conceptual model of big data system. It is an effective tool for discussing big data requirements, structure and operation. With. The model does not depend on any specific product and service providers, nor does it define standardized solutions. BDRA supports the following standardization goals. ---In the context of a high-level conceptual model of big data that has nothing to do with suppliers and technology, enhance the understanding of big data components, processing and systems Systematic understanding; ---Provide technology for government departments, related institutions and other users in the process of understanding, discussing, categorizing and comparing big data solutions Technical reference; ---Promote the analysis of candidate standards for big data interoperability, portability, reusability and scalability.6 Overview of Big Data Reference ArchitectureThe BDRA defined in this standard provides a basic reference point for big data standardization, and provides the basic concepts and principles of big data systems An overall architecture is shown in Figure 1. BDRA is organized around two dimensions representing the big data value chain. the information value chain (horizontal axis) and the information technology value chain (vertical Straight shaft). The information value chain represents the information flow realized by big data as a data science method in the process of processing from data to knowledge value. The core value of the information value chain is realized through activities such as data collection, preprocessing, analysis, visualization, and access. Information technology value The chain represents the value of big data as an emerging data application paradigm to the new demand for information technology. Information Technology Value Chain The core value of big data applications is to provide big data applications with networks, infrastructure, platforms, application tools and other information for storing and running big data. Technical service realization. The big data application provider is located at the intersection of the two value chains, and big data analysis and its realization are on the two value chains Of big data stakeholders provide specific value. BDRA provides a component-level classification system, which is used to describe the logical components in BDRA and define the classification of logical components. The logical components in BDRA are divided into three levels, from high to low, they are roles, activities and components. The logical component at the top level is the generation Table 5 roles in the big data system, including system coordinator, data provider, big data application provider, and big data framework provider The five roles of the user and the data consumer. The other two very important logical components are security and privacy and management. Five roles provide services and functions. The logical components of the second level are the activities performed by each role. The third level of logic is execution The functional components required for each activity. This architecture can be used to represent a stacked or chained system composed of multiple big data systems, where the data consumers of one system can As a data provider for the next system. The architecture supports a variety of business environments, including tightly integrated enterprise systems and loosely coupled vertical industries, which helps to understand big data systems How to supplement and distinguish it from the existing analysis, business intelligence, database and other traditional data application systems.7 Composition of Big Data Reference Architecture7.1 System Coordinator The responsibility of the system coordinator is to standardize and integrate various required data application activities to build a runnable vertical system. The specific functions of the system coordinator include. configuration and management of other components in BDRA to perform one or more workloads to ensure that each The project can run normally. Responsible for assigning corresponding physical or virtual nodes to other components and monitoring the operation of each component, and communicate Through dynamic allocation of resources, etc., to ensure that the service quality level of each component meets the required requirements. The function of the system coordinator can be implemented in a centralized or distributed form by an administrator, software or a combination of the two. 7.2 Data provider The responsibility of the data provider is to introduce data and information into the big data system for discovery, access and conversion. Its specific activities include. ---Collect and solidify data. ---Create metadata describing the data source. ---The availability and access method of the published information. ---Ensure the quality of data transmission. The interface between the data provider and the big data application provider involves three stages. start, data transmission and termination. 7.3 Big Data Application Provider 7.3.1 Overview The responsibility of the big data application provider is to meet the requirements of the system coordinator through a set of specific operations performed in the data life cycle. Specific requirements, as well as security and privacy requirements. Big data application providers include five activities. collection, preprocessing, analysis, visualization, and access. 7.3.2 Collection Responsible for handling the interface and data import with the data provider. 7.3.3 Pretreatment Including data verification, cleaning, standardization, formatting and storage. 7.3.4 Analysis Based on the needs of data scientists or the needs of vertical applications, determine the algorithm for processing data to generate new analysis and solve technical goals. So as to realize the technology of extracting knowledge from data. 7.3.5 Visualization Provide the final data consumer with the processing data elements and present the output of the analysis function. 7.3.6 Access Interact with visualization and analysis functions, respond to application requests, retrieve data by using processing and platform frameworks, and respond to data Consumer request. 7.4 Big Data Framework Provider 7.4.1 Overview The responsibility of the big data framework provider is to provide the resources and services used by the big data application provider when creating specific applications. The big data framework provider includes five activities. infrastructure, platform, processing framework, information interaction/communication and resource management. 7.4.2 Infrastructure Provide necessary resources for all other elements in the big data system. These resources are composed of a combination of some physical resources. Management resources can control/support similar virtual resources. These resources are divided into the following categories. ---Network. A resource that transmits data from one resource to another resource. ---Calculation. The actual processor and memory used to execute and maintain the software of other components. ---Storage. A resource for storing data in a big data system. ---Environment. The physical plant resources (electricity, cooling, etc.) that must be considered when establishing a big data instance. 7.4.3 Platform Contains the organization and distribution of logical data, supports file system storage and index storage methods. ---File system. implement a certain level of POSIX standards to obtain permissions and perform related file operations. ---Index storage. No need to scan the entire data set, you can quickly locate the specific elements of the data. 7.4.4 Processing Framework Provide the necessary infrastructure software to support the realization of applications that can meet the processing of data quantity, speed and diversity. Including batch Processing, stream processing, and data exchange and data manipulation between the two. 7.4.5 Information exchange/communication Contains two communication models. point-to-point transmission and store-and-forward. In the point-to-point transmission model, the sender directly transmits the The information is sent to the receiver; in the latter, the sender will first send the information to the intermediate entity, and then the intermediate entity will forward the information to the receiver one by one. Receiver. The point-to-point transmission model also includes a special communication mode of multicast. In multicast, one sender can send information to multiple Not a receiver. 7.4.6 Resource Management Computing, storage, and network connection management to realize the interconnection between the two. The main goal is to achieve distributed and flexible resource allocation, with The body includes the management of storage resources and the management of computing resources. 7.5 Data Consumer By calling the interface provided by the big data application provider, the information is accessed on demand, and the interaction with it is visible and can be checked afterwards. 7.6 Security and privacy In the security and privacy management module, through different technical means and security measures, build a big data platform security protection system to achieve Cover the security protection of hardware, software, and upper-level applications, and ensure the largest number from four aspects. network security, host security, application security, and data security. According to the security of the platform. ---Network security. through network security technology, to ensure the normal operation of data processing, storage security and maintenance. ---Host security. Ensure the normal operation of nodes by means of security reinforcement of the operating system of the nodes in the cluster. ---Application security. with identity authentication and authentication, user and authority management, database reinforcement, user password management, audit control, etc. All measures are implemented to implement a security strategy for legitimate users to reasonably access resources. ---Data security. to ensure the number of users in terms of cluster disaster recovery, backup, data integrity, data storage by role, data access control, etc. According to the security. At the same time, a reasonable disaster recovery framework should be provided to improve disaster recovery and recovery capabilities, and realize the real-time remote disaster recovery function of data, across data centers data backup. Privacy protection is mainly to conduct effective data mining without exposing sensitive user information; depending on the content that needs to be protected, It can be divided into location privacy protection, identifier anonymity protection, and connection relationship anonymity protection. 7.7 Management Provide a large-scale cluster unified operation and maintenance management system, which can perform data center, basic hardware, platform software and application software Centralized operation and maintenance, unified management, to achieve installation and deployment, parameter configuration, monitoring, alarm, user management, authority management, auditing, service management, and health inspection Functions such as investigation, problem location, upgrade and patch. With the ability to automate operation and maintenance, through the unified management of the resources of multiple data centers, reasonable allocation and scheduling of business needs The resources are automatically allocated on demand. At the same time, it provides the ability to centralize the operation and maintenance of the information technology infrastructure of multiple data centers. Automatically monitor the events, alarms, and performance of various information technology equipment in the data center, and realize the ability to perform operation and maintenance from the business latitude. A high-reliability dual-machine mechanism is implemented for the main management system node and the central management node of all business components, using active backup or load sharing Configuration to avoid the impact of single-point failure scenarios on system reliability. ......Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of GB/T 35589-2017_English be delivered?Answer: Upon your order, we will start to translate GB/T 35589-2017_English as soon as possible, and keep you informed of the progress. The lead time is typically 1 ~ 3 working days. The lengthier the document the longer the lead time.Question 2: Can I share the purchased PDF of GB/T 35589-2017_English with my colleagues?Answer: Yes. The purchased PDF of GB/T 35589-2017_English will be deemed to be sold to your employer/organization who actually pays for it, including your colleagues and your employer's intranet.Question 3: Does the price include tax/VAT?Answer: Yes. 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