How to use a SQL Server database with your PHP web site

本文为不熟悉SQL Server的Web开发者提供指南,介绍如何将SQL Server数据库与PHP网站结合使用。内容涵盖环境搭建、连接数据库、数据存取及使用PDO等。

Intended audience: Web developers who are not familiar with SQL Server, yet want to learn how to use a SQL Server database with their PHP web sites.

The links below are external links and provide information and guidance on creating dynamic web pages using PHP, SQL Server and IIS as part of web site development. This information assumes that you are already familiar with PHP development. If you are not familiar with PHP and are looking for information or additional programming resources for this language, visit http://www.php.net/.

Setting up your environment

Connecting to SQL Server from PHP

Storing and Retrieving Data

PHP Data Object (PDO) Support

 

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Read the latest version of this Wiki article here, including lists of articles about Improving Performance and Security Concerns.

内容概要:本文介绍了一个基于MATLAB实现的无人机三维路径规划项目,采用蚁群算法(ACO)与多层感知机(MLP)相结合的混合模型(ACO-MLP)。该模型通过三维环境离散化建模,利用ACO进行全局路径搜索,并引入MLP对环境特征进行自适应学习与启发因子优化,实现路径的动态调整与多目标优化。项目解决了高维空间建模、动态障碍规避、局部最优陷阱、算法实时性及多目标权衡等关键技术难题,结合并行计算与参数自适应机制,提升了路径规划的智能性、安全性和工程适用性。文中提供了详细的模型架构、核心算法流程及MATLAB代码示例,涵盖空间建模、信息素更新、MLP训练与融合优化等关键步骤。; 适合人群:具备一定MATLAB编程基础,熟悉智能优化算法与神经网络的高校学生、科研人员及从事无人机路径规划相关工作的工程师;适合从事智能无人系统、自动驾驶、机器人导航等领域的研究人员; 使用场景及目标:①应用于复杂三维环境下的无人机路径规划,如城市物流、灾害救援、军事侦察等场景;②实现飞行安全、能耗优化、路径平滑与实时避障等多目标协同优化;③为智能无人系统的自主决策与环境适应能力提供算法支持; 阅读建议:此资源结合理论模型与MATLAB实践,建议读者在理解ACO与MLP基本原理的基础上,结合代码示例进行仿真调试,重点关注ACO-MLP融合机制、多目标优化函数设计及参数自适应策略的实现,以深入掌握混合智能算法在工程中的应用方法。
### SQL Tracing Tools and Techniques SQL tracing tools are essential for diagnosing performance issues in SQL queries. These tools provide detailed insights into the execution of SQL statements, helping database administrators (DBAs) and developers optimize query performance. Below is a comprehensive overview of SQL tracing techniques and tools. #### Overview of SQL Tracing SQL tracing involves capturing detailed information about the execution of SQL statements to identify bottlenecks or inefficiencies. Oracle Database provides several mechanisms for enabling SQL tracing, including the use of `DBMS_MONITOR` and `ALTER SESSION` commands. Once enabled, the trace files generated can be analyzed using tools like TKPROF[^2]. #### Enabling SQL Trace To enable SQL tracing at the session level, the following command can be used: ```sql ALTER SESSION SET TRACEFILE_IDENTIFIER = 'my_trace'; ALTER SESSION SET TIMED_STATISTICS = TRUE; ALTER SESSION SET SQL_TRACE = TRUE; ``` This configuration ensures that all SQL statements executed within the session are traced with timing information. The `TRACEFILE_IDENTIFIER` parameter helps in identifying the trace file among multiple sessions[^1]. #### Analyzing Trace Files with TKPROF Once the trace file is generated, it can be processed using TKPROF, which formats the raw trace data into a more readable form. The following command demonstrates how to use TKPROF: ```bash tkprof <trace_file> <output_file> sort=exeela,fchela ``` The `sort` option allows sorting the output based on elapsed time or fetch time, aiding in pinpointing inefficient queries[^2]. #### Automatic SQL Tuning Advisor Oracle Database includes an automated maintenance task called SQL Tuning Advisor, which identifies high-load SQL statements and provides tuning recommendations. This advisor can be run manually or as part of scheduled maintenance windows to improve the execution plans of problematic SQL queries[^1]. #### Manual vs. Automatic Tuning While automatic tuning mechanisms such as SQL Tuning Advisor offer significant benefits, manual tuning remains a critical skill for advanced users. Participants in Oracle training courses learn to compare the steps involved in manual tuning versus the capabilities of new automatic tuning features in Oracle 10g[^2]. Manual tuning often involves modifying the physical schema or altering SQL statement syntax to influence optimizer behavior. #### Security Considerations in SQL Tracing When performing SQL tracing, it is important to consider security implications. Manipulating HTTP headers, cookies, or other user-supplied data can expose vulnerabilities such as SQL Injection or Cross-Site Scripting (XSS). Ensuring proper validation and sanitization of input data is crucial when implementing tracing mechanisms[^3]. ###
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