Ludo Hashing: Compact, Fast, and Dynamic Key-value Lookups for Practical Network Systems

Shouqian Shi, Chen Qian
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引用次数: 7

Abstract

Key-value lookup engines running in fast memory are crucial components of many networked and distributed systems such as packet forwarding, virtual network functions, content distribution networks, distributed storage, and cloud/edge computing. These lookup engines must be memory-efficient because fast memory is small and expensive. This work presents a new key-value lookup design, called Ludo Hashing, which costs the least space (3.76 + 1.05 ι bits per key-value item for ι-bit values) among known compact lookup solutions including the recently proposed partial-key Cuckoo and Bloomier perfect hashing. In addition to its space efficiency, Ludo Hashing works well with most practical systems by supporting fast lookups, fast updates, and concurrent writing/reading. We implement Ludo Hashing and evaluate it with both micro-benchmark and two network systems deployed in CloudLab. The results show that in practice Ludo Hashing saves 40% to 80%+ memory cost compared to existing dynamic solutions. It costs only a few GB memory for 1 billion key-value items and achieves high lookup throughput: over 65 million queries per second on a single node with multiple threads.
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Ludo哈希:实用网络系统的紧凑、快速和动态键值查找
在快速内存中运行的键值查找引擎是许多网络和分布式系统(如数据包转发、虚拟网络功能、内容分发网络、分布式存储和云/边缘计算)的关键组件。这些查找引擎必须具有内存效率,因为快速内存体积小且价格昂贵。这项工作提出了一种新的键值查找设计,称为Ludo哈希,它在已知的紧凑查找解决方案(包括最近提出的部分键Cuckoo和Bloomier完美哈希)中花费最少的空间(对于ι-bit值,每个键值项3.76 + 1.05 ι比特)。除了空间效率之外,Ludo哈希通过支持快速查找、快速更新和并发写/读,在大多数实际系统中都能很好地工作。我们实现了Ludo哈希,并使用部署在CloudLab中的微基准测试和两个网络系统对其进行了评估。结果表明,在实践中,与现有的动态解决方案相比,Ludo哈希节省了40%到80%以上的内存成本。对于10亿个键值项,它只需要几GB的内存,并且实现了高查找吞吐量:在具有多个线程的单个节点上每秒超过6500万次查询。
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