Zephyr: live migration in shared nothing databases for elastic cloud platforms
Zephyr: live migration in shared nothing databases for elastic cloud platforms
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DOI：
10.1145/1989323.1989356
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发表时间：
2011-06
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通讯作者：
Aaron J. Elmore;Sudipto Das;D. Agrawal;A. E. Abbadi
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作者：
Aaron J. Elmore;Sudipto Das;D. Agrawal;A. E. Abbadi
托管数十万个应用程序的大型云平台的多租户数据基础设施面临着为数据占用空间小、负载模式不可预测的应用程序提供服务的挑战。当这样的平台建立在弹性的按使用付费基础设施上时，额外的挑战是将系统的运营成本降至最低，同时保证租户的服务级别协议(SLA)。因此，弹性负载均衡是一项重要功能，可以在高负载时进行扩容，而在低负载时进行缩容。实时迁移是一种以最小的服务中断和无停机时间迁移租户的技术，对于实现轻量级弹性扩展至关重要。我们将重点讨论数据库层的实时迁移问题。我们提出了Zephar，这是一种在无共享事务数据库体系结构中高效迁移实时数据库的技术。Zephr使用按需拉入和异步推送数据的阶段，要求最低限度的同步，不会导致服务不可用，很少或没有事务中止，最大限度地减少数据传输开销，在迁移过程中提供ACID保证，并确保在出现故障时的正确性。我们概述了一个使用开源关系数据库引擎的原型实现，并给出了使用各种事务性工作负载的全面评估。从几十次失败的操作、10%-20%的平均事务延迟变化、最小的消息传递以及迁移实时数据库的正常操作期间没有开销，可以明显看出Zephr的效率。
Multitenant data infrastructures for large cloud platforms hosting hundreds of thousands of applications face the challenge of serving applications characterized by small data footprint and unpredictable load patterns. When such a platform is built on an elastic pay-per-use infrastructure, an added challenge is to minimize the system's operating cost while guaranteeing the tenants' service level agreements (SLA). Elastic load balancing is therefore an important feature to enable scale-up during high load while scaling down when the load is low. Live migration, a technique to migrate tenants with minimal service interruption and no downtime, is critical to allow lightweight elastic scaling. We focus on the problem of live migration in the database layer. We propose Zephyr, a technique to efficiently migrate a live database in a shared nothing transactional database architecture. Zephyr uses phases of on-demand pull and asynchronous push of data, requires minimal synchronization, results no service unavailability and few or no aborted transactions, minimizes the data transfer overhead, provides ACID guarantees during migration, and ensures correctness in the presence of failures. We outline a prototype implementation using an open source relational database engine and an present a thorough evaluation using various transactional workloads. Zephyr's efficiency is evident from the few tens of failed operations, 10-20% change in average transaction latency, minimal messaging, and no overhead during normal operation when migrating a live database.