SQL Server性能优化的技术分析

随着客户端/服务器技术和多层架构的进步,系统效率问题日益引发广泛讨论。由于缺乏数据库管理系统(DBMS)提供的优化方法和工具,以及基于微软技术的数据库管理员和应用程序开发人员的知识,无法对设计和服务执行系统进行优化。文章回顾了提高SQL Server实例性能时需要考虑的目标,并阐述了用于优化查询的技术。

Python Server Page Performance Analysis and Modeling

Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.

FedAdaSS: Federated Learning with Adaptive Parameter Server Selection Based on Elastic Cloud Resources

The rapid expansion of artificial intelligence(AI)applications has raised significant concerns about user privacy,prompting the development of privacy-preserving machine learning(ML)paradigms such as federated learning(FL).FL enables the distributed training of ML models,keeping data on local devices and thus addressing the privacy concerns of users.However,challenges arise from the heterogeneous nature of mobile client devices,partial engagement of training,and non-independent identically distributed(non-IID)data distribution,leading to performance degradation and optimization objective bias in FL training.With the development of 5G/6G networks and the integration of cloud computing edge computing resources,globally distributed cloud computing resources can be effectively utilized to optimize the FL process.Through the specific parameters of the server through the selection mechanism,it does not increase the monetary cost and reduces the network latency overhead,but also balances the objectives of communication optimization and low engagement mitigation that cannot be achieved simultaneously in a single-server framework of existing works.In this paper,we propose the FedAdaSS algorithm,an adaptive parameter server selection mechanism designed to optimize the training efficiency in each round of FL training by selecting the most appropriate server as the parameter server.Our approach leverages the flexibility of cloud resource computing power,and allows organizers to strategically select servers for data broadcasting and aggregation,thus improving training performance while maintaining cost efficiency.The FedAdaSS algorithm estimates the utility of client systems and servers and incorporates an adaptive random reshuffling strategy that selects the optimal server in each round of the training process.Theoretical analysis confirms the convergence of FedAdaSS under strong convexity and L-smooth assumptions,and comparative experiments within the FLSim framework demonstrate a reduction in training round-to-accuracy by 12%–20%compared to the Federated Averaging(FedAvg)with random reshuffling method under unique server.Furthermore,FedAdaSS effectively mitigates performance loss caused by low client engagement,reducing the loss indicator by 50%.

A Design of an SMTP Email Server

This study developed a mail server program using Socket API and Python.The program uses the Hypertext Transfer Protocol(HTTP)to receive emails from browser clients and forward them to actual email service providers via the Simple Mail Transfer Protocol(SMTP).As a web server,it handles Transmission Control Protocol(TCP)connection requests from browsers,receives HTTP commands and email data,and temporarily stores the emails in a file.Simultaneously,as an SMTP client,the program establishes a TCP connection with the actual mail server,sends SMTP commands,and transmits the previously saved emails.In addition,we also analyzed security issues and the efficiency and availability of this server,providing insights into the design of SMTP mail servers.

Excel+SQL Server在实验成绩信息管理中的应用研究

深入探讨了如何利用Excel和SQL Server集成化地管理和分析大学物理实验成绩信息。通过建立数据库、导入导出数据、数据查询与分析及使用Excel的数据透视表和图表功能,可以高效地管理实验成绩数据,进而深入分析学生的学习情况和教学效果。

基于ArcGIS Server的网络农田地理信息系统设计

该文为提高农田信息管理智能化水平,应用ArcGIS Server应用平台,完成对网络农田地理信息系统的设计。首先,设计和搭建系统架构和系统运行环境。其次,分别设计用户登录、信息表达、查询统计、专题图制作和空间分析等模块,保证系统功能设计效果。最后,从应用层、服务层、数据层3个方面,完成对系统设计和实现。结果表明,在ArcGIS Server应用平台的应用背景下,该文所设计的网络农田地理信息系统具有操作简单、安全可靠等特点,可以实时共享和发布农田空间信息,完全符合预期设计标准和要求。希望通过这次研究,为相关人员提供有效的借鉴和参考。

基于FreeRTOS的多连接TCP Server设计

文中提出了一种支持多客户端连接的TCP Server的嵌入式软硬件设计方案。该网络服务器以Cortex-M4芯片STM32F407VET6为核心控制器,通过RMII接口与LAN8742A以太网收发器进行网络数据交互。此外,文中将LwIP协议栈移植到FreeRTOS实时操作系统中,并根据TCP客户端连接情况,动态创建或消除相应客户端的网络通信线程。研究证明,TCP Server最大可支持4个客户端同时连接,进行稳定的网络数据传输,有效解决了嵌入式网络系统仅单点连接的问题。

基于SQL Server的教学评价管理系统设计

教学评价是教学工作中的重要环节,传统的教学评价方式难以实现对学生学习过程性评价的及时存储及更新,存在时效性不高、难以量化的问题,很难依据评价实现对学生学习行为的及时指导。文章主要针对传统教学评价存在的以上问题,综合使用SQL Server开发平台设计了一套便捷、高效的教学评价管理系统,实现了混合式教学中相关教学数据的实时增删改查基本功能以及教学评价与管理等功能,从而实现对学生学业的多维过程性评价,进而指导教学。

基于改进Apriori算法的SQL Server数据库入侵识别方法

常规的数据库入侵识别方法以识别入侵行为数据为主,各种识别模块导致数据库入侵识别的恶意操作增加。因此,设计了基于改进Apriori算法的SQL Server数据库入侵识别方法。首先,识别SQL Server数据库入侵类型,将数据库中的关键词进行条件查询判断。其次,提取入侵攻击的语句特征,避免附加语句执行恶意操作。最后,基于改进Apriori算法迭代数据库的频繁项集,通过逐层识别的形式迭代寻找SQL Server数据库中所有项集的关系,并形成识别规则,提升了数据库入侵识别性能。

基于Java和SQL Server的仓库管理系统的设计与开发

本文针对依靠大量人力、物力的传统管理模式存在的缺陷,以药品的仓库管理为例,采用Java语言和SQL Server数据库,设计并开发了一套精准、高效、便捷的仓库管理系统。分析了系统的业务需求和功能需求,从功能设计和数据库设计两个方面设计了系统的总体方案,实现了系统的可视化图形用户界面、数据库功能、入库功能、出库功能。

Mobile Edge Computing Servers Deployment with Improved Genetic Algorithm in Cellular Internet of Things

Mobile edge computing(MEC)provides services to devices and reduces latency in cellular internet of things(IoT)networks.However,the challenging problem is how to deploy MEC servers economically and efficiently.This paper investigates the deployment problem of MEC servers of the real-world road network by employing an improved genetic algorithm(GA)scheme.We first use the threshold-based K-means algorithm to form vehicle clusters according to their locations.We then select base stations(BSs)based on clustering center coordinates as the deployment locations set for potential MEC servers.We further select BSs using a combined simulated annealing(SA)algorithm and GA to minimize the deployment cost.The simulation results show that the improved GA deploys MEC servers effectively.In addition,the proposed algorithm outperforms GA and SA algorithms in terms of convergence speed and solution quality.

基于SQL server的生产管理系统数据库设计研究

计算机市场瞬息万变,信息的收集、综合和分析至关重要。无法实时评估公司的销售和卖家的销售结果可能会导致公司高管在决策和分析过程中出现延误或误解,从而对公司的底线和增长产生重大影响。销售管理也是公司ERP的重要组成部分,是企业信息化的标志。本文以SQL server为基础,提出一种生产管理系统数据库设计方法,以供参考。

Adaptive Load Balancing for Parameter Servers in Distributed Machine Learning over Heterogeneous Networks

In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth.To address this problem,a network-aware adaptive PS load distribution scheme is proposed,which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states.We evaluate the proposed scheme on MXNet,known as a realworld distributed training platform,and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.

高职院校计算机专业课程思政建设研究与探索——以SQL server数据库为例

目前,高职院校计算机专业课程的思政建设和推动仍然面临许多问题。本文对本校计算机应用技术专业的核心专业课程“SQL Server数据库”的思政建设进行了探索。通过探索,笔者首先提出了课程思政设计原则,明确了思政教学目标,重新设计了融入思政元素的教学内容,并采用了多元化的教学方式,从而真正将思政元素融入该课程的教学中。

大数据量ArcGIS Server地图服务源数据获取方法研究

桌面端软件在采用ArcGIS Server地图服务时只能进行简单浏览、查询操作,不能进行空间统计和分析。针对该问题,以ArcGIS Server地图服务底层接口为切入点,采用编码与Mapshaper工具相结合的方式实现了地图服务源数据的下载和格式转换。基于该方法获取的空间数据不仅包含完整的图形和属性信息,还不受地图服务源数据量大小的限制,具有较强的实用性。

Rider Optimization Algorithm Based Optimal Cloud Server Selection in E-Learning

Currently,e-learning is one of the most prevalent educational methods because of its need in today’s world.Virtual classrooms and web-based learning are becoming the new method of teaching remotely.The students experience a lack of access to resources commonly the educational material.In remote loca-tions,educational institutions face significant challenges in accessing various web-based materials due to bandwidth and network infrastructure limitations.The objective of this study is to demonstrate an optimization and queueing tech-nique for allocating optimal servers and slots for users to access cloud-based e-learning applications.The proposed method provides the optimization and queue-ing algorithm for multi-server and multi-city constraints and considers where to locate the best servers.For optimal server selection,the Rider Optimization Algo-rithm(ROA)is utilized.A performance analysis based on time,memory and delay was carried out for the proposed methodology in comparison with the exist-ing techniques.The proposed Rider Optimization Algorithm is compared to Par-ticle Swarm Optimization(PSO),Genetic Algorithm(GA)and Firefly Algorithm(FFA),the proposed method is more suitable and effective because the other three algorithms drop in local optima and are only suitable for small numbers of user requests.Thus the proposed method outweighs the conventional techniques by its enhanced performance over them.

An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

In cloud data centers,the consolidation of workload is one of the phases during which the available hosts are allocated tasks.This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement(SLA).To consolidate the workloads,the hosts are segregated into three categories:normal hosts,under-loaded hosts,and over-loaded hosts based on their utilization.It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish.Thresh-old values were proposed in the literature to detect this scenario.The current study aims to improve the existing methods that choose the underloaded hosts,get rid of Virtual Machines(VMs)from them,andfinally place them in some other hosts.The researcher proposes a Host Resource Utilization Aware(HRUAA)Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment.The mechanism presented in this study is contrasted with existing mechanisms empirically.The results attained from the study estab-lish that numerous hosts can be shut down,while at the same time,the user's workload requirement can also be met.The proposed method is energy-efficient in workload consolidation,saves cost and time,and leverages active hosts.

HIS系统SQL Server数据库死锁问题的分析与解决

SQL Server数据库锁是保证HIS系统数据安全、高速和稳定运行的重要手段,系统运行期间死锁的预防、分析、处理工作贯穿始终。文章主要讨论Microsoft SQL Server数据库在现实工作应用场景中出现死锁问题的原因,并结合自身工作经验给出常见死锁问题的处理方法,为HIS系统数据库管理人员在日常运维工作中处理此类问题提供一些思路及方法。

Application of Recursive Query on Structured Query Language Server

The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done correctly.Structured query language(SQL)is a database language and is used to manipulate data.In Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its disadvantages.Common table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive CTE.Hierarchical data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive CTEs.The recursive query is illustrated and implemented on some simple hierarchical data.In addition,one business case study is brought forward and the solution using recursive query based on CTE is shown.At the same time,stored procedures are programmed to do the recursion in SQL.Test results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax.

数学思维在SQL Server数据库应用技术教学中的运用与效果

SQL Server数据库应用技术课程在目前的计算机类课程中有着较强的基础性作用,数学思维在该学科中有着重要的引领效果。从目前的应用情况来看,数学思维在SQL Server数据库应用技术教学中的运用具有重要的效果,可以帮助学生从抽象的数学概念出发,理解和应用数据库的相关知识和技术,提高数据库应用的效率和质量。基于此,在本文的研究中,首先对SQL Server数据库应用技术教学的现状进行了分析,接着阐述了数学思维在SQL Server数据库应用技术教学中应用价值,最后结合教学实践分析了数学思维在SQL Server数据库应用技术教学中的具体运用。