OceanBase Bacchus: 一种高性能且可扩展的多云共享存储架构
OceanBase Bacchus: a High-Performance and Scalable Cloud-Native Shared Storage Architecture for Multi-Cloud
AI总结：
OceanBase Bacchus是一种基于LSM树的多云共享存储架构，通过共享服务和异步后台服务实现高性能读写，显著提升OLTP和OLAP性能并降低存储成本。
摘要：
尽管越来越多的数据库现在采用共享存储架构，但当前的存储解耦系统尚未在成本与性能之间找到最佳平衡。在高并发读写场景中，基于B+树的共享存储难以高效吸收频繁的原地更新。现有的基于LSM树的解耦存储设计受到跨节点共享日志机制复杂实现的限制，目前尚无满意的解决方案。本文提出了OceanBase Bacchus，一种专为云供应商提供的对象存储设计的LSM树架构。该系统通过共享服务导向的PALF（基于Paxos的只追加日志文件系统）日志和异步后台服务，使计算节点无状态化，从而实现高性能的读写操作。我们采用共享块缓存服务灵活利用缓存资源。我们的设计将日志同步置于共享服务中，为存储计算分离数据库的日志共享提供了新的解决方案。该架构在模块间解耦，使计算、缓存和存储资源能够快速且独立地进行弹性扩展。通过使用多个基准测试进行实验评估，包括SysBench和TPC-H，我们确认OceanBase Bacchus在OLTP场景中性能与HBase相当或更优，在OLAP工作负载中显著优于StarRocks。利用Bacchus对多云部署和一致性能的支持，我们不仅保持了高可用性和竞争力性能，还在OLTP场景中存储成本降低了59%，在OLAP场景中降低了89%。
英文摘要：
Although an increasing number of databases now embrace shared-storage architectures, current storage-disaggregated systems have yet to strike an optimal balance between cost and performance. In high-concurrency read/write scenarios, B+-tree-based shared storage struggles to efficiently absorb frequent in-place updates. Existing LSM-tree-backed disaggregated storage designs are hindered by the intricate implementation of cross-node shared-log mechanisms, where no satisfactory solution yet exists. This paper presents OceanBase Bacchus, an LSM-tree architecture tailored for object storage provided by cloud vendors. The system sustains high-performance reads and writes while rendering compute nodes stateless through shared service-oriented PALF (Paxos-backed Append-only Log File system) logging and asynchronous background services. We employ a Shared Block Cache Service to flexibly utilize cache resources. Our design places log synchronization into a shared service, providing a novel solution for log sharing in storage-compute-separated databases. The architecture decouples functionality across modules, enabling elastic scaling where compute, cache, and storage resources can be resized rapidly and independently. Through experimental evaluation using multiple benchmark tests, including SysBench and TPC-H, we confirm that OceanBase Bacchus achieves performance comparable to or superior to that of HBase in OLTP scenarios and significantly outperforms StarRocks in OLAP workloads. Leveraging Bacchus's support for multi-cloud deployment and consistent performance, we not only retain high availability and competitive performance but also achieve substantial reductions in storage costs by 59% in OLTP scenarios and 89% in OLAP scenarios.
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