@inproceedings{4431fd4ec55349bebaea64366fa9d48d,
title = "New techniques to curtail the tail latency in stream processing systems ∗ ",
abstract = "This paper presents a series of novel techniques for reducing the tail latency in stream processing systems like Apache Storm. Concretely, we present three mechanisms: (1) adaptive timeout coupled with selective replay to catch straggler tuples; (2) shared queues among different tasks of the same operator to reduce overall queueing delay; (3) latency feedback-based load balancing, intended to mitigate het-erogenous scenarios. We have implemented these techniques in Apache Storm, and present experimental results using sets of micro-benchmarks as well as two topologies from Yahoo! Inc. Our results show improvement in tail latency up to 72.9%.",
keywords = "Apache Storm, Stream Processing Systems, Tail Latency",
author = "Guangxiang Du and Indranil Gupta",
note = "Publisher Copyright: {\textcopyright} 2016 ACM.; 4th Annual ACM PODC Workshop on Distributed Cloud Computing, DCC 2016 ; Conference date: 25-07-2016 Through 28-07-2016",
year = "2016",
month = jul,
day = "25",
doi = "10.1145/2955193.2955206",
language = "English (US)",
isbn = "9781450342209",
series = "Proceedings of the Annual ACM Symposium on Principles of Distributed Computing",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the 4th Workshop on Distributed Cloud Computing, DCC 2016",
address = "United States",
}