Learn about Alibaba Blink caching technology

Alibaba Blink is a high-performance caching technology released by Alibaba Cloud Computing Department. It is based on memory and uses multiple technologies for caching, including LRU, LFU, LIRS, ARC, etc. Among them, the LIRS algorithm is the most important feature of Blink. It can show more advantages than other algorithms in memory management. Let’s take a deeper look at Alibaba Blink caching technology.

1. Background and development of Alibaba Blink

In the era of cloud computing, caching technology has become a more important technology because it can reduce disk I/O and increase application response speed. Alibaba Blink caching technology is a high-performance caching technology for distributed web applications. Compared with traditional caching technology, Blink uses a more advanced memory management algorithm, making the memory used by the cache more efficient.

Since 2011, Alibaba Blink’s open source code has been released on GitHub, and in 2015 it officially became an incubation project of the Apache Software Foundation. In June 2018, Blink successfully entered the Apache Software Foundation's top open source project and became an official Apache project. This marks that Blink has become one of the largest open source communities in the world.

2. Alibaba Blink’s technical architecture

The implementation of Blink’s caching function is based on the following algorithms:

1.LRU (Least Recently Used), which is more commonly used An algorithm that caches objects in memory based on their recent use. Once there is insufficient space, the least frequently used data is removed.

2.LFU (Least Frequently Used), it believes that unused objects may be remembered, so frequent access will occur. The caching system using the LFU algorithm limits the number of objects that will be cached in memory, thereby removing the least frequently used objects when there is insufficient memory.

3.LIRS (Lowest Inter-reference Recency Set), this is a newly added algorithm in Blink, mainly used to solve scenarios where LRU is not applicable. LIRS can quickly find objects that need to be eliminated in memory, reduce the cost of clearing the cache, and reduce CPU overhead.

4.ARC (Adaptive Replacement Cache), which is an adaptive algorithm, dynamically adjusts the objects stored in the memory according to cache hits, avoiding the defects of LRU, LFU, and LIRS algorithms.

Blink’s architecture is divided into two parts: cache client and cache server. The client is mainly responsible for transmitting the request to the cache server, and the cache server returns the response to the client. The client and server communicate through the TCP/IP protocol. The Blink cache server can adopt a distributed mode to store cache data on multiple servers, thus improving the reliability and scalability of the system.

In addition, Blink also supports a variety of caching protocols, including Memcached, Redis, Tango and other protocols. In different deployment scenarios, different caching protocols can be selected and dynamic switching is supported.

3. Performance advantages of Alibaba Blink

As a high-performance caching technology, Alibaba Blink can perform powerful memory management and optimize the structure of stored objects in memory, thus making caching The operation is more resource-saving and the operation is more stable. Compared with other caching systems, Blink has the following three main performance advantages:

1. Faster caching speed

Compared with other caching technologies, Alibaba Blink’s faster. This is because the cloud cache uses advanced algorithms such as LRU, LFU, LIRS, and ARC to efficiently cache data items. Before caching operations, Blink will warm up data to speed up application response and improve user experience.

2. Simpler management method

In actual deployment, Blink can be deployed using a single server or distributed server. For the distributed server deployment model, Blink can avoid cache hot spots through a variety of sharding mechanisms, allowing the physical server to decouple the logical cache nodes, effectively reducing the warm-up time and improving the cache hit rate.

3. Higher scalability

Blink adopts distributed technology, supports multiple caching protocols, and can be flexibly changed in a variety of applications. This This makes the application of caching technology in different scales more scalable. In high-concurrency scenarios, caching technology can dynamically increase or decrease server nodes, so that it can be deployed according to current caching needs.

Summary:

Alibaba Blink is a high-performance cache technology that uses a variety of memory management algorithms, including LRU, LFU, LIRS, ARC, etc. Using Blink can improve cache response speed, simplify management methods and improve scalability, providing an efficient solution for actual distributed web applications. With the rapid development of cloud computing technology, Alibaba Blink will surely become an important technology for more and more enterprises to apply it to actual business.

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