Scaling Replicated State Machines with Compartmentalization [Technical Report]
December 31, 2020 Β· Declared Dead Β· π Proceedings of the VLDB Endowment
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Authors
Michael Whittaker, Ailidani Ailijiang, Aleksey Charapko, Murat Demirbas, Neil Giridharan, Joseph M. Hellerstein, Heidi Howard, Ion Stoica, Adriana Szekeres
arXiv ID
2012.15762
Category
cs.DC: Distributed Computing
Citations
39
Venue
Proceedings of the VLDB Endowment
Last Checked
3 months ago
Abstract
State machine replication protocols, like MultiPaxos and Raft, are a critical component of many distributed systems and databases. However, these protocols offer relatively low throughput due to several bottlenecked components. Numerous existing protocols fix different bottlenecks in isolation but fall short of a complete solution. When you fix one bottleneck, another arises. In this paper, we introduce compartmentalization, the first comprehensive technique to eliminate state machine replication bottlenecks. Compartmentalization involves decoupling individual bottlenecks into distinct components and scaling these components independently. Compartmentalization has two key strengths. First, compartmentalization leads to strong performance. In this paper, we demonstrate how to compartmentalize MultiPaxos to increase its throughput by 6x on a write-only workload and 16x on a mixed read-write workload. Unlike other approaches, we achieve this performance without the need for specialized hardware. Second, compartmentalization is a technique, not a protocol. Industry practitioners can apply compartmentalization to their protocols incrementally without having to adopt a completely new protocol.
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