FlexPushdownDB: Hybrid Pushdown and Caching in a Cloud DBMS
FlexPushdownDB: Hybrid Pushdown and Caching in a Cloud DBMS
复制标题
DOI：
10.14778/3476249.3476265
复制
发表时间：
2021-07
期刊：
影响因子：
--
通讯作者：
Yifei Yang;Matt Youill;M. Woicik;Yizhou Liu;Xiangyao Yu;M. Serafini;Ashraf Aboulnaga;M. Stonebraker
中科院分区：
文献类型：
--
作者：
Yifei Yang;Matt Youill;M. Woicik;Yizhou Liu;Xiangyao Yu;M. Serafini;Ashraf Aboulnaga;M. Stonebraker
现代云数据库采用存储分解架构，将计算管理和存储管理分开。这种架构的主要瓶颈是连接计算层和存储层的网络。为了缓解瓶颈，人们探索了两种解决方案：缓存和计算下推。虽然这两种技术都可以显着减少网络流量，但现有的 DBMS 将它们视为正交技术，并且仅支持其中一种，从而未充分利用潜在的性能优势。在本文中，我们介绍了 FlexPushdownDB (FPDB)，这是一种 OLAP 云 DBMS 原型，它支持细粒度混合查询执行，以在存储分解架构中结合缓存和计算下推的优点。我们基于称为可分离运算符的新概念构建了一个混合查询执行器，以组合缓存中的数据和下推处理的结果。我们还提出了一种新颖的加权 LFU 缓存替换策略，该策略考虑了下推计算的成本。我们对星型模式基准的实验评估表明，混合执行的性能比传统的仅缓存架构和仅下推架构高出 2.2 倍。在混合架构中，我们的实验表明，Weighted-LFU 的性能比基线 LFU 提高了 37%。
Modern cloud databases adopt a storage-disaggregation architecture that separates the management of computation and storage. A major bottleneck in such an architecture is the network connecting the computation and storage layers. Two solutions have been explored to mitigate the bottleneck: caching and computation pushdown. While both techniques can significantly reduce network traffic, existing DBMSs consider them as orthogonal techniques and support only one or the other, leaving potential performance benefits unexploited. In this paper we present FlexPushdownDB (FPDB) , an OLAP cloud DBMS prototype that supports fine-grained hybrid query execution to combine the benefits of caching and computation pushdown in a storage-disaggregation architecture. We build a hybrid query executor based on a new concept called separable operators to combine the data from the cache and results from the pushdown processing. We also propose a novel Weighted-LFU cache replacement policy that takes into account the cost of pushdown computation. Our experimental evaluation on the Star Schema Benchmark shows that the hybrid execution outperforms both the conventional caching-only architecture and pushdown-only architecture by 2.2X. In the hybrid architecture, our experiments show that Weighted-LFU can outperform the baseline LFU by 37%.