Storing Files: Database vs. File System
As a developer tasked with implementing a Document Management System, it is crucial to determine the optimal storage approach between storing files in a database or on a file system. This decision hinges on factors such as security, retrieval speed, and scalability.
For scenarios involving large volumes of documents in diverse formats, storing files directly in the file system is often preferred for performance reasons. Fast retrieval is a key requirement in this case, and file system storage provides faster access compared to retrieving files from a database.
Securing Files on the File System
While file system storage offers speed benefits, it necessitates careful security precautions:
- Confidentiality: Protect sensitive documents by storing them outside the Apache Document Root and controlling access through a PHP Controller.
- Sharded Path: Divide storage into multiple directories to prevent bottlenecks and improve performance. Consider hashing the filename to distribute files across directories.
- Inode Number: Monitor inode usage to avoid running out of available directory pointers, especially when storing numerous small files.
Using a Database for Metadata
If search capabilities are desired based on file attributes such as date or title, it may be beneficial to store metadata in a database. This approach enables efficient searches without compromising the performance of file retrieval.
It is worth noting that MySQL does not offer a direct equivalent to MS SQL Server's FILESYSTEM column type, which acts as a hybrid between file systems and databases. However, external file storage with supplemental metadata stored in a database remains a viable and effective solution.
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MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

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To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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