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Cited by 536

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

MillWheel: fault-tolerant stream processing at internet scale

Akidau, Tyler, Balikov, Alex, Bekiroğlu, Kaya, Chernyak, Slava, Haberman, Josh, Lax, Reuven, McVeety, Sam, Mills, Daniel, Nordstrom, Paul, Whittle, Sam·2013·Proceedings of the VLDB Endowment

Abstract

MillWheel is a framework for building low-latency data-processing applications that is widely used at Google. Users specify a directed computation graph and application code for individual nodes, and the system manages persistent state and the continuous flow of records, all within the envelope of the framework's fault-tolerance guarantees. This paper describes MillWheel's programming model as well as its implementation. The case study of a continuous anomaly detector in use at Google serves to motivate how many of MillWheel's features are used. MillWheel's programming model provides a notion of logical time, making it simple to write time-based aggregations. MillWheel was designed from the outset with fault tolerance and scalability in mind. In practice, we find that MillWheel's unique combination of scalability, fault tolerance, and a versatile programming model lends itself to a wide variety of problems at Google.

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Metadata

Authors
Akidau, T., Balikov, A., Bekiroğlu, K., Chernyak, S., Haberman, J., Lax, R., McVeety, S., Mills, D., Nordstrom, P., & Whittle, S.
Venue
Proceedings of the VLDB Endowment
Published
2013-08
Volume
6
Issue
11
Pages
1033-1044
ISSN
2150-8097 (ISSN-L)
OpenAlex
W2153972927
Cited by
536
References
26
FWCI
65.64
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: MillWheel: fault-tolerant stream processing at internet scale. https://app.cochat.ai/papers/10.14778/2536222.2536229
The paper
Akidau, T., Balikov, A., Bekiroğlu, K., Chernyak, S., Haberman, J., Lax, R., McVeety, S., Mills, D., Nordstrom, P., & Whittle, S. (2013). MillWheel: fault-tolerant stream processing at internet scale. Proceedings of the VLDB Endowment. https://doi.org/10.14778/2536222.2536229

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