KallaxDB: A Table-less Hash-based Key-Value Store on Storage Hardware with Built-in Transparent Compression
KallaxDB: A Table-less Hash-based Key-Value Store on Storage Hardware with Built-in Transparent Compression
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DOI：
10.1145/3465998.3466004
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发表时间：
2021-06
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影响因子：
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通讯作者：
Xubin Chen;Ning Zheng;Shukun Xu;Yifan Qiao;Yang Liu;Jiangpeng Li;Tong Zhang
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作者：
Xubin Chen;Ning Zheng;Shukun Xu;Yifan Qiao;Yang Liu;Jiangpeng Li;Tong Zhang
本文研究了一种能充分利用现代存储硬件的、内置透明压缩能力的键值（KV）存储的设计。许多现代存储设备/驱动器实现基于硬件的数据压缩，对操作系统和应用程序透明。此外，基于硬件的压缩在云基础设施中的部署不断增长，导致内置透明压缩的基于云的存储硬件即将到来。通过将逻辑存储空间利用效率与实际物理存储使用情况解耦，透明压缩允许数据管理软件故意浪费逻辑存储空间，以换取更简单的数据结构和算法，从而降低实现复杂性，提高性能。这项工作提出了一个基于无表哈希的KV存储，其基本思想是直接将键空间哈希到逻辑存储空间上，而根本不使用哈希表。由于数据结构大大简化，这种方法会导致大量逻辑存储空间未充分利用，这可以通过具有透明压缩的存储硬件无缝地缓解。本文介绍了基本的KV存储结构，并开发了数学公式来辅助其配置和分析。我们实现了这样一个KV存储KallaxDB，并在一个内置透明压缩的商用SSD上进行了实验。结果表明，虽然消耗很少的内存资源，但在吞吐量、延迟和CPU使用方面，它与其他现代KV存储相比具有优势。
This paper studies the design of a key-value (KV) store that can take full advantage of modern storage hardware with built-in transparent compression capability. Many modern storage appliances/drives implement hardware-based data compression, transparent to OS and applications. Moreover, the growing deployment of hardware-based compression in Cloud infrastructure leads to the imminent arrival of Cloud-based storage hardware with built-in transparent compression. By decoupling the logical storage space utilization efficiency from the true physical storage usage, transparent compression allows data management software to purposely waste logical storage space in return for simpler data structures and algorithms, leading to lower implementation complexity and higher performance. This work proposes a table-less hash-based KV store, where the basic idea is to hash the key space directly onto the logical storage space without using a hash table at all. With a substantially simplified data structure, this approach is subject to significant logical storage space under-utilization, which can be seamlessly mitigated by storage hardware with transparent compression. This paper presents the basic KV store architecture, and develops mathematical formulations to assist its configuration and analysis. We implemented such a KV store KallaxDB and carried out experiments on a commercial SSD with built-in transparent compression. The results show that, while consuming very little memory resource, it compares favorably with the other modern KV stores in terms of throughput, latency, and CPU usage.