PHP-FPM performance improvement tips: optimize website static resource loading

I found that the compressed package downloaded from a download website will be larger than the original compressed package after decompression. The difference is tens of Kb for a small one and several dozen Mb for a large one. If it is uploaded to a cloud disk or paid space, it does not matter if the file is small. , if there are many files, the storage cost will be greatly increased. I studied it specifically and can learn from it if necessary. Compression level: 9-Extreme compression Dictionary size: 256 or 384, the more compressed the dictionary, the slower it is. The compression rate difference is larger before 256MB, and there is no difference in compression rate after 384MB. Word size: maximum 273 Parameters: f=BCJ2, test and add parameter compression rate will be higher

Concurrency and coroutines are used in GoAPI design for: High-performance processing: Processing multiple requests simultaneously to improve performance. Asynchronous processing: Use coroutines to process tasks (such as sending emails) asynchronously, releasing the main thread. Stream processing: Use coroutines to efficiently process data streams (such as database reads).

In PHP development, the caching mechanism improves performance by temporarily storing frequently accessed data in memory or disk, thereby reducing the number of database accesses. Cache types mainly include memory, file and database cache. Caching can be implemented in PHP using built-in functions or third-party libraries, such as cache_get() and Memcache. Common practical applications include caching database query results to optimize query performance and caching page output to speed up rendering. The caching mechanism effectively improves website response speed, enhances user experience and reduces server load.

In the Go distributed system, caching can be implemented using the groupcache package. This package provides a general caching interface and supports multiple caching strategies, such as LRU, LFU, ARC and FIFO. Leveraging groupcache can significantly improve application performance, reduce backend load, and enhance system reliability. The specific implementation method is as follows: Import the necessary packages, set the cache pool size, define the cache pool, set the cache expiration time, set the number of concurrent value requests, and process the value request results.

Atomic classes are thread-safe classes in Java that provide uninterruptible operations and are crucial for ensuring data integrity in concurrent environments. Java provides the following atomic classes: AtomicIntegerAtomicLongAtomicReferenceAtomicBoolean These classes provide methods for getting, setting, and comparing values ​​to ensure that the operation is atomic and will not be interrupted by threads. Atomic classes are useful when working with shared data and preventing data corruption, such as maintaining concurrent access to a shared counter.

Unit testing concurrent functions is critical as this helps ensure their correct behavior in a concurrent environment. Fundamental principles such as mutual exclusion, synchronization, and isolation must be considered when testing concurrent functions. Concurrent functions can be unit tested by simulating, testing race conditions, and verifying results.

Redis is a powerful database solution because it provides fast performance, rich data structures, high availability and scalability, persistence capabilities, and a wide range of ecosystem support. 1) Extremely fast performance: Redis's data is stored in memory and has extremely fast read and write speeds, suitable for high concurrency and low latency applications. 2) Rich data structure: supports multiple data types, such as lists, collections, etc., which are suitable for a variety of scenarios. 3) High availability and scalability: supports master-slave replication and cluster mode to achieve high availability and horizontal scalability. 4) Persistence and data security: Data persistence is achieved through RDB and AOF to ensure data integrity and reliability. 5) Wide ecosystem and community support: with a huge ecosystem and active community,

Concurrency issues in PHP multi-threaded functions can be solved by using synchronization tools (such as mutex locks) to manage multi-threaded access to shared resources. Use functions that support mutual exclusion options to ensure that the function is not called again while another thread is executing. Wrap non-reentrant functions in synchronized blocks to protect function calls.