Styx: Transactional Stateful Functions on Streaming Dataflows
CoRR(2023)
摘要
Developing stateful cloud applications, such as high-throughput/low-latency
workflows and microservices with strict consistency requirements, remains
arduous for programmers.
The Stateful-Functions-as-a-Service (SFaaS) paradigm aims to serve these use
cases. However, existing approaches either provide serializable transactional
guarantees at the level of individual functions or separate application logic
from the state and use inefficient transactional protocols. These design
choices increase the execution latency, limiting the usability of SFaaS systems
for stateful cloud applications.
In this paper, we present Styx, a novel SFaaS runtime that executes
serializable transactions across functions with exactly-once guarantees. Styx
is the first streaming dataflow-based runtime for SFaaS, offering application
logic and state co-location, coarse-grained state persistence, and incremental
checkpointing. Styx extends a deterministic transactional protocol to support
an arbitrary call graph of stateful functions. It introduces a
transaction-execution acknowledgment scheme that allows tracking a
transactional workflow's SFaaS calls, guaranteeing atomicity and exactly-once
processing. Experiments with the YCSB-T, TPC-C, and Deathstar benchmarks show
that Styx outperforms state-of-the-art approaches by achieving at least one
order of magnitude higher throughput while exhibiting near-linear scalability.
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