论文标题
养蜂场:DBMS集成的交易函数-AS-A-Service框架
Apiary: A DBMS-Integrated Transactional Function-as-a-Service Framework
论文作者
论文摘要
开发人员越来越多地使用功能-AS-Service(FAAS)平台来对数据进行低延迟和交易操作,例如对微服务或Web服务进行数据。不幸的是,现有的FAAS平台支持这些应用程序很差,因为它们在云功能中在云函数中执行,从数据管理中执行,在访问远程存储的交互交易中执行的应用程序逻辑。物理分离会损害性能,而逻辑分离使有效地提供交易保证和容错性。 本文介绍了Apiary,这是一种新型DBMS集成的FAA平台,用于部署和组成容忍性交易功能。养蜂场通过包装分布式DBMS引擎并将其用作功能执行,数据管理和操作日志记录的统一运行时,通过包装分布式DBMS引擎将功能执行和数据管理整合到逻辑上,从而提供了功能执行和数据管理,从而提供了相似或更强大的交易保证,同时提供了可比的系统,同时可以大大提高性能和可观察性和可观察性。为了允许开发人员编写复杂的状态程序,我们利用此集成来启用高效且容易耐受的功能组成,建立一个前端,以协调功能的工作流程,并确保每个工作流程都可以完成,并且工作流中的每个功能都会完全执行一次。我们对研究和生产FAAS平台进行评估,并通过减少沟通开销来表明其在微服务工作负载上以2--68倍的优于它们。
Developers increasingly use function-as-a-service (FaaS) platforms for data-centric applications that perform low-latency and transactional operations on data, such as for microservices or web serving. Unfortunately, existing FaaS platforms support these applications poorly because they physically and logically separate application logic, executed in cloud functions, from data management, done in interactive transactions accessing remote storage. Physical separation harms performance while logical separation complicates efficiently providing transactional guarantees and fault tolerance. This paper introduces Apiary, a novel DBMS-integrated FaaS platform for deploying and composing fault-tolerant transactional functions. Apiary physically co-locates and logically integrates function execution and data management by wrapping a distributed DBMS engine and using it as a unified runtime for function execution, data management, and operational logging, thus providing similar or stronger transactional guarantees as comparable systems while greatly improving performance and observability. To allow developers to write complex stateful programs, we leverage this integration to enable efficient and fault-tolerant function composition, building a frontend for orchestrating workflows of functions with the guarantees that each workflow runs to completion and each function in a workflow executes exactly once. We evaluate Apiary against research and production FaaS platforms and show it outperforms them by 2--68x on microservice workloads by reducing communication overhead.