Building a Two-Level Cache Framework to Solve Spring-Cache Problems

This article introduces a two-level cache framework designed to address issues with Spring-Cache, providing enhanced caching strategies and improved performance in Java-based backend systems.

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Building a Two-Level Cache Framework to Solve Spring-Cache Problems

1. Introduction

The article discusses the limitations of Spring-Cache and presents a two-level cache framework to overcome them, focusing on local and remote caching strategies.

2. Framework Architecture

The framework uses annotations for configuration, with a CacheManagerContainer managing cache implementations. It supports local (Caffeine) and remote (Redis) caches, and includes features like automatic refresh and distributed locks.

3. Key Features

The framework offers TTL, refresh time, cache type selection, and SpEL-based key generation. It also includes a two-level cache approach to reduce remote cache load and improve performance.

auto:
cache:
local:
type: caffeine
remote:
type: redis
host: localhost
port: 6379
timeout: 2000
pool:
min-idle: 2
max-idle: 10
max-active: 20
max-wait: 200
key-serializer: org.springframework.data.redis.serializer.StringRedisSerializer
value-serializer: org.springframework.data.redis.serializer.GenericJackson2JsonRedisSerializer
namespace: testCache
allow-null-values: true

4. Conclusion

The framework enhances caching efficiency and addresses Spring-Cache limitations, with future plans for additional features like distributed locks and monitoring.

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javaperformance optimizationbackend-developmentcachingFrameworkSpring Cache
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