Sharing Buffer Pool Memory in Multi-Tenant Relational Database-as-a-Service

Relational database-as-a-service (DaaS) providers need to rely on multi-tenancy and resource sharing among tenants, since statically reserving resources for a tenant is not cost effective. A major consequence of resource sharing is that the performance of one tenant can be adversely affected by resource demands of other co-located tenants. One such resource that is essential for good performance of a tenant’s workload is buffer pool memory. In this paper, we study the problem of how to effectively share buffer pool memory in multi-tenant relational DaaS. We first develop a framework that allows service providers to have a precise and meaningful SLA with a tenant even when the system is overbooked, i.e. more buffer pool memory is promised to tenants in aggregate than is physically available. Next, we present a novel buffer pool page replacement algorithm MT-LRU that builds upon theoretical concepts from weighted online caching and is designed for multi-tenant scenarios involving SLAs and overbooking. MT-LRU generalizes the LRU-K algorithm which is commonly used in relational database systems. We have prototyped our techniques inside a commercial DaaS engine and extensive experiments demonstrate the effectiveness of our techniques.