Cache Layer

High-performance caching for qqq applications with Redis and in-memory support.

Overview

The Cache Layer qBit provides a unified caching interface for qqq applications. It abstracts away the complexity of different caching backends while providing a consistent API.

Features

Multiple Backends - Redis, Memcached, and in-memory caching

Query Caching - Automatic caching of database query results

TTL Support - Configurable time-to-live for cache entries

Cache Invalidation - Smart invalidation on data changes

Metrics - Built-in cache hit/miss metrics

When to Use

Use the Cache Layer qBit when you need to:

Reduce database load for frequently accessed data

Cache expensive computations

Share cached data across multiple application instances

Improve response times for read-heavy workloads

Installation

Maven

Add the following dependency to your pom.xml:

XML

<dependency>
    <groupId>io.qrun</groupId>
    <artifactId>qbit-cache-layer</artifactId>
    <version>2.1.0</version>
</dependency>

Gradle

Groovy

implementation 'io.qrun:qbit-cache-layer:2.1.0'

Requirements

qqq 1.2.0 or higher

Java 17+

Redis 6.0+ (if using Redis backend)

Configuration

Redis Backend

YAML

cache:
  backend: redis
  redis:
    host: localhost
    port: 6379
    password: ${REDIS_PASSWORD}
    database: 0
    ssl: true

In-Memory Backend

YAML

cache:
  backend: memory
  memory:
    maxSize: 10000
    expireAfterWrite: 3600

Configuration Options

Option	Default	Description
`backend`	`memory`	Cache backend (redis, memory)
`defaultTtl`	`3600`	Default TTL in seconds
`keyPrefix`	`qqq:`	Prefix for cache keys

API Reference

CacheService

The main interface for cache operations.

Java

@Inject
private CacheService cacheService;

// Get from cache
Optional<Customer> customer = cacheService.get("customer:123", Customer.class);

// Put in cache
cacheService.put("customer:123", customer, Duration.ofMinutes(5));

// Delete from cache
cacheService.delete("customer:123");

Annotations

Java

@Cacheable(key = "customer:#{id}", ttl = 300)
public Customer getCustomer(Integer id) {
    // Method implementation
}

Knowledge Base

troubleshooting

Redis Connection Issues

Troubleshoot common Redis connection problems

recipe

Cache Warming on Startup

Pre-populate cache on application startup

troubleshooting

High Cache Miss Rate

Diagnose and fix high cache miss rates