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resp-benchmark is a benchmark tool for testing databases that support the RESP protocol, such as Redis, Valkey, and Tair.

Project description

resp-benchmark

Python - Version PyPI - Version PyPI - Downloads License

English | 中文

一个基于 Rust 构建的 RESP (Redis 序列化协议) 数据库基准测试工具,提供 Python 绑定。用于测试 Redis、Valkey、Tair 等 RESP 兼容数据库的性能。

主要功能

  • 支持自定义命令模板和占位符
  • 多线程并发测试
  • 支持连接池和管道操作
  • 支持 Redis 集群模式
  • 提供 CLI 工具和 Python 库接口
  • 内置 QPS 限流控制

安装

需要 Python 3.9 或更高版本。

pip install resp-benchmark

快速开始

命令行使用

# 基础基准测试
resp-benchmark -s 10 "SET {key uniform 100000} {value 64}"

# 加载数据然后测试
resp-benchmark --load -n 1000000 "SET {key sequence 100000} {value 64}"
resp-benchmark -s 10 "GET {key uniform 100000}"

# 自定义连接数和管道
resp-benchmark -c 128 -P 10 -s 30 "SET {key uniform 1000000} {value 128}"

Python 库使用

from resp_benchmark import Benchmark

# 初始化基准测试
bm = Benchmark(host="127.0.0.1", port=6379)

# 加载测试数据
bm.load_data(
    command="SET {key sequence 1000000} {value 64}", 
    count=1000000, 
    connections=128
)

# 运行基准测试
result = bm.bench(
    command="GET {key uniform 1000000}", 
    seconds=30, 
    connections=64
)

print(f"QPS: {result.qps}")
print(f"平均延迟: {result.avg_latency_ms}ms")
print(f"P99 延迟: {result.p99_latency_ms}ms")

命令语法

resp-benchmark 使用强大的占位符系统来生成多样化和真实的测试数据:

键占位符

  • {key uniform N}: 从 0 到 N-1 的随机键

    • 示例: {key uniform 100000}key_0000099999
  • {key sequence N}: 从 0 到 N-1 的顺序键(适用于加载数据)

    • 示例: {key sequence 100000}key_0000000000, key_0000000001, ...
  • {key zipfian N}: Zipfian 分布键(模拟真实世界的访问模式)

    • 示例: {key zipfian 100000} → 遵循指数为 1.03 的 Zipfian 分布

值占位符

  • {value N}: N 字节的随机字符串

    • 示例: {value 64}a8x9mK2p... (64 字节)
  • {rand N}: 0 到 N-1 的随机数

    • 示例: {rand 1000}742
  • {range N W}: 范围 N 内相差 W 的两个数字

    • 示例: {range 100 10}45 55

命令示例

# 字符串操作
SET {key uniform 1000000} {value 64}
GET {key uniform 1000000}
INCR {key uniform 100000}

# 列表操作
LPUSH {key uniform 1000} {value 64}
LINDEX {key uniform 1000} {rand 100}

# 集合操作
SADD {key uniform 1000} {value 64}
SISMEMBER {key uniform 1000} {value 64}

# 有序集合操作
ZADD {key uniform 1000} {rand 1000} {value 64}
ZRANGEBYSCORE {key uniform 1000} {range 1000 100}

# 哈希操作
HSET {key uniform 1000} {key uniform 100} {value 64}
HGET {key uniform 1000} {key uniform 100}

命令行选项

选项 描述 默认值
-h 服务器主机名 127.0.0.1
-p 服务器端口 6379
-u 认证用户名 ""
-a 认证密码 ""
-c 连接数(0 为自动) 0
-n 总请求数(0 为无限) 0
-s 持续时间(秒)(0 为无限) 0
-t 目标 QPS(0 为无限) 0
-P 管道深度 1
--cores 使用的 CPU 核心(逗号分隔) 全部
--cluster 启用集群模式 false
--load 仅加载数据,不进行基准测试 false
--short-connection 短连接模式:每次命令都创建新连接 false

高级特性

连接自动扩展

当指定 -c 0 时,resp-benchmark 根据系统资源和目标 QPS 自动确定最优连接数。

CPU 核心绑定

将基准测试线程绑定到特定 CPU 核心以获得一致的性能:

# 使用核心 0, 1, 2, 3
resp-benchmark --cores 0,1,2,3 -s 10 "SET {key uniform 100000} {value 64}"

速率限制

控制请求速率进行渐进式负载测试:

# 目标 10,000 QPS
resp-benchmark -t 10000 -s 30 "SET {key uniform 100000} {value 64}"

管道操作

使用管道进行批量操作:

# 每个连接管道 10 个请求
resp-benchmark -P 10 -c 128 -s 30 "SET {key uniform 100000} {value 64}"

集群模式

使用自动槽位分布测试 Redis 集群:

resp-benchmark --cluster -h cluster-endpoint -p 7000 -s 30 "SET {key uniform 100000} {value 64}"

性能优化

最佳实践

  1. 预加载数据: 使用 --load 在基准测试前填充测试数据
  2. 适当的连接数: 从 -c 128 开始,根据结果调整
  3. 键分布: 读取使用 uniform,写入使用 sequence
  4. 明智使用管道: 批量操作使用 -P 10,延迟测试使用 -P 1
  5. 清洁状态: 测试之间清除数据以避免干扰

示例工作流程

# 1. 清除现有数据
redis-cli FLUSHALL

# 2. 加载测试数据
resp-benchmark --load -c 256 -P 10 -n 1000000 "SET {key sequence 100000} {value 64}"

# 3. 使用不同模式进行基准测试
resp-benchmark -c 128 -s 30 "GET {key uniform 100000}"    # 随机访问
resp-benchmark -c 128 -s 30 "GET {key zipfian 100000}"    # 真实访问模式

完整示例

字符串操作

# 基本 SET/GET
resp-benchmark --load -n 1000000 "SET {key sequence 100000} {value 64}"
resp-benchmark -s 10 "GET {key uniform 100000}"

# 大值
resp-benchmark -s 10 "SET {key uniform 10000} {value 1024}"

# 递增操作
resp-benchmark -s 10 "INCR {key uniform 10000}"

列表操作

# 构建列表
resp-benchmark --load -n 1000000 "LPUSH {key sequence 1000} {value 64}"

# 随机访问
resp-benchmark -s 10 "LINDEX {key uniform 1000} {rand 1000}"

# 范围操作
resp-benchmark -s 10 "LRANGE {key uniform 1000} {range 1000 10}"

集合操作

# 填充集合
resp-benchmark --load -n 1000000 "SADD {key sequence 1000} {key sequence 1000}"

# 测试成员关系
resp-benchmark -s 10 "SISMEMBER {key uniform 1000} {key uniform 1000}"

有序集合操作

# 添加带分数的成员
resp-benchmark --load -n 1000000 "ZADD {key sequence 1000} {rand 10000} {key sequence 1000}"

# 分数查询
resp-benchmark -s 10 "ZSCORE {key uniform 1000} {key uniform 1000}"

# 范围查询
resp-benchmark -s 10 "ZRANGEBYSCORE {key uniform 1000} {range 10000 100}"

哈希操作

# 填充哈希
resp-benchmark --load -n 1000000 "HSET {key sequence 1000} {key sequence 100} {value 64}"

# 字段访问
resp-benchmark -s 10 "HGET {key uniform 1000} {key uniform 100}"

Lua 脚本

# 加载脚本
redis-cli SCRIPT LOAD "return redis.call('SET', KEYS[1], ARGV[1])"

# 基准测试脚本执行
resp-benchmark -s 10 "EVALSHA d8f2fad9f8e86a53d2a6ebd960b33c4972cacc37 1 {key uniform 100000} {value 64}"

短连接性能测试

短连接模式:每次命令都创建新连接,执行完成后立即关闭。

限制:

  • 不支持 --load-P(pipeline 必须为 1)

使用:

resp-benchmark --short-connection "PING" -c 50 -s 10

Python API:

result = bm.bench(command="PING", seconds=30, connections=50, short_connection=True)

Python 库 API

初始化

from resp_benchmark import Benchmark

# 基本连接
bm = Benchmark(host="127.0.0.1", port=6379)

# 带认证
bm = Benchmark(
    host="redis.example.com",
    port=6379,
    username="user",
    password="pass"
)

# 集群模式
bm = Benchmark(
    host="cluster-endpoint",
    port=7000,
    cluster=True
)

# 自定义配置
bm = Benchmark(
    host="127.0.0.1",
    port=6379,
    cores="0,1,2,3",  # 使用特定核心
    timeout=30        # 连接超时
)

加载数据

# 顺序加载(推荐)
bm.load_data(
    command="SET {key sequence 1000000} {value 64}",
    count=1000000,
    connections=128,
    pipeline=10
)

# 带速率限制
bm.load_data(
    command="SET {key sequence 1000000} {value 64}",
    count=1000000,
    connections=128,
    target=50000  # 50k QPS
)

基准测试

# 基于时间的基准测试
result = bm.bench(
    command="GET {key uniform 1000000}",
    seconds=30,
    connections=64
)

# 基于计数的基准测试
result = bm.bench(
    command="GET {key uniform 1000000}",
    count=1000000,
    connections=64
)

# 带管道
result = bm.bench(
    command="SET {key uniform 1000000} {value 64}",
    seconds=30,
    connections=64,
    pipeline=10
)

# 短连接模式
result = bm.bench(
    command="PING",
    seconds=30,
    connections=50,
    short_connection=True
)

结果分析

# 访问基准测试结果
print(f"QPS: {result.qps:.2f}")
print(f"平均延迟: {result.avg_latency_ms:.2f}ms")
print(f"P99 延迟: {result.p99_latency_ms:.2f}ms")
print(f"使用的连接数: {result.connections}")

贡献

欢迎贡献!请随时提交拉取请求或开启议题。

许可证

该项目基于 MIT 许可证 - 详见 LICENSE 文件。

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