SQL Server硬件选择变得轻松SQL Server Hardware Choices Made Easy下载

SQL Server硬件选择变得轻松SQL Server Hardware Choices Made Easy

通过提供一系列特定的技巧或建议，可以在选择和配置与SQL Server一起使用的硬件时快速“了解”最重要的问题。

Virtualizing SQL Server with VMware_English

Virtualizing SQL Server with VMware_English,

Absolute Database for D7

这个数据库看性能不错，哪位能破解一下。Overview Absolute Database: Delphi database with SQL support.Absolute Database lets you forget the Borland Database Engine (BDE). This BDE replacement is the compact, high-speed, robust and easy-to-use database engine. With Absolute Database you will not need special installation and configuration, it compiles right into your EXE. Make your application faster and smaller with Absolute Database BDE alternative!An individual may use Absolute Database Personal in a project if he / she is the only user of this project. If your project is public or if you represent a company, you must order commercial edition of Absolute Database.Key Features: No BDE; no DLLs Single-file database SQL‘92 (DDL & DML) support Single-user and multi-user mode (file-server) Unmatched ease-of-use 100% compatibility with standard DB-aware controls Strong encryption BLOB compression Free for personal use Full source code available Royalty-free Specification Ease of Deployment No BDE, no DLLs No special installation or configuration required Database engine compiles right into EXE Single-file database format Database file could be merged with the application EXE file High Speed Advanced cache management and buffering architecture Sophisticated SQL query and filter optimizer Special optimized database engine for temporary results of SQL queries Fast B*-Tree indexes with high-speed on thousands and on millions of records Buffered transactions for batch inserts, updates and deletes In-memory tables for fast operations with data loaded into memory Optimization for read-only databases, such as databases on CD High-concurrency design for multi-threaded applications Multi-User Zero-admin file-server Automatic record and table locking Automatic detection of changes made by other users Configurable limit of concurrent connections Easy switching between single-user and multi-user mode Full transactions support with ReadCommited isolation level SQL Support SELECT with DISTINCT, INNER LEFT, RIGTH, FULL and OUTER JOIN, GROUP BY and ORDER BY clauses CREATE TABLE, DROP TABLE, ALTER TABLE statements CREATE INDEX, DROP INDEX statements INSERT, UPDATE, DELETE statements BETWEEN, IN, LIKE, IS NULL, EXISTS operators Aggregate functions COUNT,SUM,MIN,MAX,AVG Most of all SQL‘92 arithmetic, logical, date-time and string functions and operators Data types conversion by function CAST SQL scripts (multiple commands separated by ‘;‘) Parameters in queries SELECT from several databases in one query Correlated and non-correlated subqueries Compactness Small size of code added into the application by the database engine units Small database file size achieved by customizable page size, compression of table metadata and other special means Automatic free space recycling for data records, index pages, and BLOB blocks Fast BLOB data compression Short indexes for string fields Low memory consumption Compatibility Support of most of TTable field data types, including BLOB fields Full compatibility with standard DB-aware visual controls such as QuickReport, DBGrid, DBNavigator, DBImage, DBMemo, DBRichEdit and others Calculated and lookup fields Most of TTable functions including Key and Range methods Support for the IProvider interface (TClientDataSet) Functionality Unicode support in String and Memo fields Multiple-fields indexes with descending, ascending, case-sensitive and insensitive options Shareable tables Default values support Min, max and not null constraints on field values Export to SQL script (reverse engineering) Security Strong encryption of database file Variety of supported encryption algorithms: Rijndael, the Advanced Encryption Standard (AES) winner 128 bit key, Rijndael 256 bit key, Blowfish 448 bit key, Twofish 128 bit key, Twofish 256 bit key, Square, Single DES and Triple DES Reliability Repair database in case of hardware failure or operating system error caused by another application Auto-detect of database corruption and automatic repair of database file Convenience Table restructuring being performed in the easiest way keeping all the existing data Data importing from and exporting to any dataset Internationalization / localization support by use of current system locale Displaying progress during potentially slow operations with the tables and databases Utilities DBImportExport utility to transfer your existing tables from database systems with BDE driver, such as Paradox, Interbase, Access, Oracle, SQL Server to Absolute Database format and vice versa. Absolute Database Manager to manage a database easily and to perform all supported operations with tables and database file Absolute Database Manager also provides you an easy way of executing SQL queries All utilities come with full source code and can be used as an advanced examples Ease of Development Full compatibility with TTable, TQuery, TSession and TDatabase components Extensive documentation: Developer‘s Guide and Reference covering every development issue. Large number of demos illustrating wide range of use cases Prompt and responsive technical support Cost-Effectiveness 100% royalty-free, i.e. there is no additional licensing fees no matter how many times you deploy the application Flexible licensing: source code and no source code versions, multi-developers licenses Comparison with other Databases You can see here Comparision with other databases Maximum Capacity SpecificationsObject Maximum sizes / numbers Multi-User Edition Single-User Edition Bytes per string field 64,000 (also limited by page size) 64,000 (also limited by page size) Bytes per BLOB field 2GB 2GB Bytes per index 64,000 (also limited by page size) 64,000 (also limited by page size) Bytes per row 65,400 (also limited by page size) 65,400 (also limited by page size) Columns per index 10,000 10,000 Columns per table 65,000 65,000 UNIQUE indexes or constraints per table 30,000 30,000 Database size 32 TB (also limited by file system and OS) 32 TB (also limited by file system and OS) Identifier length (in characters) 255 255 Locks per connection 2,147,483,647 N/A Rows per table 2,147,483,647 2,147,483,647 Tables per database 2,147,483,647 2,147,483,647 Bytes per page 65,536 65,536 Pages per database file 2,147,483,647 2,147,483,647 Connections per database Maximum value of configured connections before creating database file (up to 2,147,483,647) 1 Records in transaction 2,147,483,647 (also limited by available RAM) 2,147,483,647 (also limited by available RAM) In-memory table size 2,147,483,647 (also limited by available RAM) 2,147,483,647 (also limited by available RAM) Requirements Target Development Environment:Delphi 4, Delphi 5, Delphi 6, Delphi 7 and C++ Builder 4, C++ Builder 5, C++ Builder 6. Trial and Personal editions of Delphi are not supported.Target OS:Windows 95/98/ME, Windows NT, 2000, XP

impala-2.8

Impala provides fast, interactive SQL queries directly on your Apache Hadoop data stored in HDFS, HBase, or the Amazon Simple Storage Service (S3). In addition to using the same unified storage platform, Impala also uses the same metadata, SQL syntax (Hive SQL), ODBC driver, and user interface (Impala query UI in Hue) as Apache Hive. This provides a familiar and unified platform for real-time or batch-oriented queries. Impala is an addition to tools available for querying big data. Impala does not replace the batch processing frameworks built on MapReduce such as Hive. Hive and other frameworks built on MapReduce are best suited for long running batch jobs, such as those involving batch processing of Extract, Transform, and Load (ETL) type jobs. Note: Impala was accepted into the Apache incubator on December 2, 2015. In places where the documentation formerly referred to “Cloudera Impala”, now the official name is “Apache Impala (incubating)”.

Proxy Pattern Informatization Research Based On SaaS

Abstract—Based on demands in proxy pattern, this article proposes informatization solution of proxy pattern which includes enterprise management, proxy management, franchisee management and supply chain management, then discusses basic functions, system architecture of the platform as well as metadata services, security strategies, and finally gives a multi-user data model -shared database, shared architecture. Keywords-Proxy Pattern; Informatization; Multi-User Data Model I. INTRODUCTION SaaS is the abbreviation of software as a service. It is a brand innovative software application pattern which starts in the 21st century along with the development and application of Internet technology. Through providing the software services over the Internet, manufactures deploy the application software on his own server, while the user customizes the services over the Internet according to the actual demand, at the same time defrays the expense according to the kind and hours of service used. What is a proxy pattern? It refers to that someone obtains the sale proxy of production enterprise or purchase proxy of users through a form of contract, and gets the commission after finishing the transaction [1]. Generally speaking, it is suitable for a new market or marketing of specialized product, such as jewelry industry, they always need special supply chain management, technology and local market, some requirements should be possessed by distributor. But it is not easy to find such one, so using a proxy pattern and establishing a proxy service center is very useful to open the target market rapidly, meanwhile fully control the logistics of both supply and demand, as shown in Figure 1: Figure 1. Proxy pattern service schema As a public service platform of the supply chain, the proxy service center is an extremely important intermediate link. On one hand, it enables every enterprise in each link of the proxy pattern to be a node in the supply chain network; on the other hand it realizes the exchange and sharing of data, information and knowledge among supply, product, and sales enterprises. The proxy service center which carries on the product logistics between supplier and franchisee has a function of managing retailers and franchisees. So this pattern can grasps the supply condition quickly, control the logistics flexibly. At present, there are already relatively mature networks in many industries. Therefore, it has a very vital practical significance to promote the informatization platform based on the proxy pattern. II. FUNCTION STUDIES OF INFORMATIZATION PLATFORM The proxy pattern informatization mainly provides a stable, completely functional service platform which integrates application systems configuring on the unified service architecture. The service vendor who is responsible for maintenance and management of the software provides the software service over the Internet for users. Users need not purchase, construct and maintain infrastructure and the application procedure. According to informatization demands in proxy industry, functions of this platform includes enterprise informatization, franchisee informatization, proxy service center informatization, supply chain informatization and SaaS website service, which is shown in Figure 2: Figure 2. Proxy pattern informatization platform A. Enterprise informatization Enterprise informatization will be realized in this module which is mainly composed of general information management systems and management information systems for specific industry. The former includes OA system, personnel management system, attendance system, human resources management system and financial system .etc; the latter are suitable for the different industries, such as production management, workshop management, inventory management etc. Each system can realize seamless integration through web services; users in different industries can customize a combination of modules, share the synthesis statistical report, and establish basic data set .etc. This has fully manifested the superiorities of the SaaS application, which not only meets individual demands of various enterprises, but also makes these enterprises to be a link in the industry chain as well as realize its own informatization. Thus, every enterprise can share the information in upstream and downstream which is a great advantage for enterprise development. B. Proxy service center informatization As one important part of the informatization platform, the proxy service center carries on the product logistics between suppliers and franchisees. The realization of proxy pattern informatization may break the phenomenon of information island, which makes the proxy service center to be an important information channel on the entire industrial chain, thus it is more advantageous for information communication and sharing among enterprises. Informatization management for the proxy service center includes functions like statistics, inquiry, finance, user management. The center requires comprehensive statistic and inquire abilities, so as to fully grasp upstream and downstream information of the industrial chain. C. Franchisee service informatization Under the proxy pattern, franchisee manages one or several brands through the proxy service center, technically accepts the instruction of the brands, and engages in the operating activities according to the business pattern in the contract. As a different from branch business, franchisee has independent operation system and informatization platform. Informatization management for franchisee will be realized in this module, which includes functions like inventory, statistics, sales, finance .etc. So it not only realizes franchisee informatization service, but integrates franchisees into the industry informatization process. D. SaaS website service SaaS website service is a show window of service vendor and a communication channel of users, through which users submit their informatization demands. After satisfying the demand of users, the supplier gives feedback to users, so as to interact with user on line. Functions like company introduction, product synopsis, informatization diagnosis, product experience, service support will be included in this module. III. SYSTEM ARCHITECTURE Above we discuss the basic functions of informatization platform in proxy industry, the remainder of this article will detail the system architecture that can help us plan and build SaaS application. A well-designed SaaS application is distinguished by three qualities: scalability, configurability, and multi-user efficiency [2]. • Scalability, which is maximum enhancing concurrency, so as to high-efficiently use the application resources. • Configurability, refers to that each user can configure appearance and behaviors of the application with metadata, simultaneously guarantees easy use of the configuration and no expense. • Multi-user efficiency, this requires an architecture that maximizes the sharing of resources across users, but that is still able to differentiate data belonging to different users [3]. In a SaaS application, keys to determine these characteristics are metadata service and data security service, which are also the focus of users [4]. Neither can a common B/S architecture guarantee the data security of users, nor can satisfy flexible business requirement. Therefore, this article proposes the following SaaS platform system architecture based on proxy pattern, as Figure 3 shows: Figure 3. SaaS system architecture under proxy pattern In this architecture, the service vendor hosts multiple users on a load-balanced farm of identical instances (SCM instance, ERP instance, franchisee instance, agent instance etc.) with the same code library. Each instance serves for a certain amount of users with different demands, and with configurable metadata providing a unique user experience and feature set for each user [5]. Identical instances can maximize resource sharing. From users’ perspectives, the application is used as usual. As a unified interface of users, the load-balanced server will be responsible to manage these application instances. SaaS can meet various kinds of service requirement changes as well as behavior differences of business logic, which is realized mainly through metadata services. Configurable and customizable of the metadata make the platform highly scalable. According to his own business process, the user can define his fields, menu, form of report, formulas, jurisdiction, views, workflow and business rules, customize kinds of service for him, thus fully meet enterprises' individual demands and realize fast response to demand changes. The security service is most important in SaaS architecture, which is specially concerned by users. From user access to security data itself, we give a solution through authentication, authorization and means of hybrid encryption. In order to realize logon security, we want to consider a hybrid approach that combines centralized and decentralized authentication system—using the centralized approach to authenticate and manage smaller users, and the federated approach for large enterprises that demand, and will pay for, the single sign-on experience [6]. After the user logs on, access to resources and business functions in a SaaS application is managed by using roles that map to specific job functions within an organization. Each role is given one or more permission that enable users assigned to the role to perform actions in accordance with any relevant business rules, roles are managed within the SaaS application itself; they can contain individual user accounts, as well as user groups. Individual user accounts and groups can be assigned several different roles as required [7]. When the user access data resources, we have another protection—data encryption. A key wrapping system that combines the advantages of symmetric and asymmetric methods is used in this platform. Three keys are created for each user as part of the provisioning process: a symmetric key and an asymmetric key pair consisting of a public key and a private key. The symmetric key is used to encrypt the user's critical data for storage [8].A asymmetric key pair is used to encrypt and decrypt the symmetric key, so as to add another layer of security. IV. MULTI-USER DATA MODEL The multi-user data model is a very important link in SaaS platform design. A good data model has a good scalability, can share the data and information well, and satisfy the users’ individual needs. The simplest data model is storing users’ data in separate databases. Computing resources and application code are generally shared between all the users on a server, but each user has its own set of data that remains logically isolated from data that belongs to all other users[7].This model makes it easy to extend the application’s data model to meet all users’ individual needs, and restoring a user’s data from backups in a failure is a relatively simple thing[9].But usually this model expands software and hardware investment and equipment maintenance cost, which is similar to traditional single user model. The second data model is shared database, separate schema in which houses multiple users in the same database, with each user having his own set of tables that are grouped into a schema created specifically for the user. Each user can use SQL statement to operate his own data table [10]. This model can guarantee logic independence and security of users’ data, while it will increase complexity to backup and restoring of the data. In order to solve the problem of two kinds mentioned above, shared database, shared schema will be used in our platform based on standardization, unification in proxy industry, in which the same database and the same set of tables are used to host multiple users’ data. Different users’ data are stored in the same table, and distinguished by different UserID. This approach has the lowest hardware and backup costs, but it has the highest sharing, because it allows you to serve the largest number of users per database server. Some proxy industry like jewelry, there are so many nodes (they are almost small and medium-sized enterprises) that we can obtain considerable clients if we can effectively guarantee data security which is the key issue of SaaS application. What is more important, the shared schema ensures logic independence of users’ data, fully share and use all users’ data resources, is advantageous to integrate entire operation process in proxy pattern; on the other hand, different enterprises with the same service may have a different business requirement, they can flexibly extend the data model according to their own demands. Now we will discuss how to realize the extension of the data model. Generally speaking, there are two schemes: reallocated fields and Name-Value pairs [11]. Reallocated fields was used to reserve some fields in advance for user extension, when new requirement was put forward, we use one field or several fields to storage extension data [12].This scheme well realizes scalability of the data to some extent, but how many fields are reallocated at last is a problem hard to control for a large number of clients in SaaS application, while this problem is decided in scheme design. So we give up this scheme, and use Name-Value pairs to realize data extension, as shown in Figure 4: Figure 4. Name-Value pairs for Multi-User data model The scheme Name-Value pairs separate the data for extension with original data table, the extension data is stored in a unified extension table which changes transverse column of the extension table for longitudinal data sets, each extension field of original data record is stored by one extension data line, then we associate the record in original data table with the record in configuration table. Thus, extension data records are formed [13]. We will store users’ data in original data table, which contains only RecordID in the form record of the default data model, the only RecordID corresponds with one line or several lines in configuration table. A user can create records in configuration table as many as possible according to the business needs, which associate the extension table through ConfigID; then customized field values will be stored in extension table, and the table is consistent with the main data table through UserID. The scheme above allows each user to create as many custom fields as necessary so as to fully meet its diversified business needs, and it won’t waste too much storage space. V. CONCLUSIONS At present, SaaS application is vigorously promoted in many industries which can save the cost for the users, reduce the risk, and speed up the informatization process of the entire industry. Based on the informatization demands in proxy industry, this article expands SaaS application from the common management software to informatization of the entire industry, proposes basic function and the multi-user system architecture of the SaaS platform under the proxy pattern, then designs multi-user data model as well as data security services which makes the data achieve a good sharing and scalability, and effectively guarantees the data security. REFERENCES [1] Liyun Feng, Distribution Channel Management, Economy & Management Publishing House, Beijing, 2002. [2] Frederick Chong, and Gianpaolo Carraro Roger Wolter, Multi-Tenant Data Architecture, Microsoft Corporation, Washington, June 2006. [3] Wenbin Yu, Xiaohui Huang, and Min Yu,”A Solution of Shared Database and Architecture’s SaaS Based on XML”, Computer and Modernization, 8-10, April 2008. [4] Zongzuo Chang, Yue Xu, and Gang Dai,” The multi-tenant data architecture study based on the SaaS model for the public service platform”, Computer Systems and Application, 7-11, Feb. 2008. [5] Zongzuo Chang, Yue Xu, and Gang Dai,” The multi-tenant data architecture study based on the SaaS model for the public service platform”, Computer Systems and Application, 7-11, Feb. 2008. [6] Frederick Chong, and Gianpaolo Carraro Roger Wolter, Architecture Strategies for Catching the Long Tail, Microsoft Corporation, Washington, April 2006. [7] Frederick Chong, and Gianpaolo Carraro Roger Wolter, Architecture Strategies for Catching the Long Tail, Microsoft Corporation, Washington, April 2006. [8] Frederick Chong, and Gianpaolo Carraro Roger Wolter, Multi-Tenant Data Architecture, Microsoft Corporation, Washington, June 2006. [9] Frederick Chong, and Gianpaolo Carraro Roger Wolter, Multi-Tenant Data Architecture, Microsoft Corporation, Washington, June 2006. [10] Wenbin Yu, Xiaohui Huang, and Min Yu,”A Solution of Shared Database and Architecture’s SaaS Based on XML”, Computer and Modernization, 8-10, April 2008. [11] Frederick Chong, and Gianpaolo Carraro Roger Wolter, Multi-Tenant Data Architecture, Microsoft Corporation, Washington, June 2006. [12] Wei Ye .etc,Software Revolution in Internet Age:SaaS Architecture Design,Publishing House of Electronics Industry,Beijing,2009, 102. [13] Wei Ye .etc,Software Revolution in Internet Age:SaaS Architecture Design,Publishing House of Electronics Industry,Beijing,2009,104-105.