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HydraDB: a resilient RDMA-driven key-value middleware for in-memory cluster computing

Authors:

Shicong MengAuthors Info & Claims

SC '15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Article No.: 22, Pages 1 - 11

https://doi.org/10.1145/2807591.2807614

Published: 15 November 2015 Publication History

Abstract

In this paper, we describe our experiences and lessons learned from building a general-purpose in-memory key-value middleware, called HydraDB. HydraDB synthesizes a collection of state-of-the-art techniques, including continuous fault-tolerance, Remote Direct Memory Access (RDMA), as well as awareness for multicore systems, etc, to deliver a high-throughput, low-latency access service in a reliable manner for cluster computing applications.

The uniqueness of HydraDB mainly lies in its design commitment to fully exploit the RDMA protocol to comprehensively optimize various aspects of a general-purpose key-value store, including latency-critical operations, read enhancement, and data replications for high-availability service, etc. At the same time, HydraDB strives to efficiently utilize multicore systems to prevent data manipulation on the servers from curbing the potential of RDMA.

Many teams in our organization have adopted HydraDB to improve the execution of their cluster computing frameworks, including Hadoop, Spark, Sensemaking analytics, and Call Record Processing. In addition, our performance evaluation with a variety of YCSB workloads also shows that HydraDB can substantially outperform several existing in-memory key-value stores by an order of magnitude. Our detailed performance evaluation further corroborates our design choices.

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Cited By

Qiao PZhang ZLi YYuan YWang SWang GYu J(2024)AStore: Uniformed Adaptive Learned Index and Cache for RDMA-enabled Key-Value StoreIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.3355100(1-18)Online publication date: 2024
https://doi.org/10.1109/TKDE.2024.3355100
Ziegler TNelson-Slivon JLeis VBinnig C(2023)Design Guidelines for Correct, Efficient, and Scalable Synchronization using One-Sided RDMAProceedings of the ACM on Management of Data10.1145/35892761:2(1-26)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3589276
Besta MGerstenberger RFischer MPodstawski MBlach NEgeli BMitenkov GChlapek WMichalewicz MNiewiadomski HMueller JHoefler TMohror KArnold DBadia R(2023)The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of CoresProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607068(1-18)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3581784.3607068
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HydraDB: a resilient RDMA-driven key-value middleware for in-memory cluster computing

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cover image ACM Conferences

SC '15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

November 2015

985 pages

ISBN:9781450337236

DOI:10.1145/2807591

General Chair:
Jackie Kern
University of Illinois at Urbana-Champaign, Urbana, Illinois
,
Program Chair:
Jeffrey S. Vetter
Oak Ridge National Laboratory and Georgia Institute of Technology, Oak Ridge, Tennessee

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 November 2015

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SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis

November 15 - 20, 2015

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SC '15 Paper Acceptance Rate 79 of 358 submissions, 22%;

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Cited By

Qiao PZhang ZLi YYuan YWang SWang GYu J(2024)AStore: Uniformed Adaptive Learned Index and Cache for RDMA-enabled Key-Value StoreIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.3355100(1-18)Online publication date: 2024
https://doi.org/10.1109/TKDE.2024.3355100
Ziegler TNelson-Slivon JLeis VBinnig C(2023)Design Guidelines for Correct, Efficient, and Scalable Synchronization using One-Sided RDMAProceedings of the ACM on Management of Data10.1145/35892761:2(1-26)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3589276
Besta MGerstenberger RFischer MPodstawski MBlach NEgeli BMitenkov GChlapek WMichalewicz MNiewiadomski HMueller JHoefler TMohror KArnold DBadia R(2023)The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of CoresProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607068(1-18)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3581784.3607068
Han SZhang MJiang DXiong JGilad YKostic DMoatti YBiran O(2023)Exploiting Hybrid Index Scheme for RDMA-based Key-Value StoresProceedings of the 16th ACM International Conference on Systems and Storage10.1145/3579370.3594768(49-59)Online publication date: 5-Jun-2023
https://dl.acm.org/doi/10.1145/3579370.3594768
Kim TPark HLee SShin SHur JShin Y(2023)DevIOus: Device-Driven Side-Channel Attacks on the IOMMU2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179283(2288-2305)Online publication date: May-2023
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Yi YLi YXu YWang PXu YWang W(2023)BT-Duper: A Binomial-Tree Based Data Replication Offloading Method with Native RDMA Primitives2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00153(915-922)Online publication date: 21-Dec-2023
https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00153
Xiao MWang HGeng LLee RZhang X(2022)An RDMA-enabled In-memory Computing Platform for R-tree on ClustersACM Transactions on Spatial Algorithms and Systems10.1145/35035138:2(1-26)Online publication date: 12-Feb-2022
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Ma SMa TChen KWu Y(2022)A Survey of Storage Systems in the RDMA EraIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2022.318865633:12(4395-4409)Online publication date: 1-Dec-2022
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Hemmatpour MMontrucchio BRebaudengo MSadoghi M(2022)Analyzing In-Memory NoSQL LandscapeIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.300290834:4(1628-1643)Online publication date: 1-Apr-2022
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Xu YShen SHan MChen R(2022)FNotify: A Low-Latency and Scalable Publish/Subscribe System using RDMA2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys57074.2022.00074(327-336)Online publication date: Dec-2022
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