STAR: scaling transactions through asymmetric replication
Name
3342263.3342270.pdf
Description
Published version
Size
756.43 KB
Format
Adobe PDF
Checksum (MD5)
6a77891b50f65774dbac5318eeb5d3c3
Author(s)
Lu, Yi
Yu, Xiangyao
Madden, Samuel
Date Issued
2019
Journal
Proceedings of the VLDB Endowment
Publisher
VLDB Endowment
Version
Final published version
Abstract
© 2019, is held by the owner/author(s). In this paper, we present STAR, a new distributed in-memory database with asymmetric replication. By employing a singlenode non-partitioned architecture for some replicas and a partitioned architecture for other replicas, STAR is able to efficiently run both highly partitionable workloads and workloads that involve cross-partition transactions. The key idea is a new phase-switching algorithm where the execution of single-partition and cross-partition transactions is separated. In the partitioned phase, single-partition transactions are run on multiple machines in parallel to exploit more concurrency. In the single-master phase, mastership for the entire database is switched to a single designated master node, which can execute these transactions without the use of expensive coordination protocols like twophase commit. Because the master node has a full copy of the database, this phase-switching can be done at negligible cost. Our experiments on two popular benchmarks (YCSB and TPC-C) show that high availability via replication can coexist with fast serializable transaction execution in distributed in-memory databases, with STAR outperforming systems that employ conventional concurrency control and replication algorithms by up to one order of magnitude.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.14778/3342263.3342270
