The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Naiad: a timely dataflow system
Open accessAbstract
Naiad is a distributed system for executing data parallel, cyclic dataflow programs. It offers the high throughput of batch processors, the low latency of stream processors, and the ability to perform iterative and incremental computations. Although existing systems offer some of these features, applications that require all three have relied on multiple platforms, at the expense of efficiency, maintainability, and simplicity. Naiad resolves the complexities of combining these features in one framework.
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Kwak, H., Lee, C., Park, H., & Moon, S. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772751 · Cited by 6,652
Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing
Zaharia, M., Chowdhury, M., Das, T., Dave, A., Ma, J. H., McCauley, M., Franklin, M. J. M., Shenker, S. J., & Stoica, I. G. (2012) · Cited by 3,622
Pregel: a system for large-scale graph processing
Malewicz, G., Austern, M. H., Bik, A. J. C., Dehnert, J. C., Horn, I., Leiser, N., & Czajkowski, G. (2010) · Proceedings of the 2010 ACM SIGMOD International Conference on Management of data · doi:10.1145/1807167.1807184 · Cited by 3,515
MapReduce: Simplified Data Processing on Large Cluster
Senior Software Developer, A. U., & Dayalan, M. (2018) · International Journal of Research and Engineering · doi:10.21276/ijre.2018.5.5.4 · Cited by 2,948
Dryad: distributed data-parallel programs from sequential building blocks
Isard, M., Budiu, M., Yu, Y., Birrell, A., & Fetterly, D. (2007) · Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007 · doi:10.1145/1272996.1273005 · Cited by 2,432
Self-citationKohler, E., Morris, R., Chen, B., Jannotti, J., & Kaashoek, M. F. (2000) · ACM Transactions on Computer Systems · doi:10.1145/354871.354874 · Cited by 2,413
Alizadeh, M., Greenberg, A., Maltz, D. A., Padhye, J., Patel, P., Prabhakar, B., Sengupta, S., & Sridharan, M. (2010) · Proceedings of the ACM SIGCOMM 2010 conference · doi:10.1145/1851182.1851192 · Cited by 1,877
Dean, J., & Barroso, L. A. (2013) · Communications of the ACM · doi:10.1145/2408776.2408794 · Cited by 1,852
Improving MapReduce performance in heterogeneous environments
Zaharia, M., Konwinski, A., Joseph, A. D., Katz, R. H., & Stoica, I. G. (2008) · doi:10.5555/1855741.1855744 · Cited by 1,588
PowerGraph: distributed graph-parallel computation on natural graphs
Gonzalez, J. E., Low, Y., Gu, H., Bickson, D., & Guestrin, C. (2012) · doi:10.5555/2387880.2387883 · Cited by 1,451
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Self-citationDiscretized streams: fault-tolerant streaming computation at scale
Zaharia, M., Das, T., Li, H., Hunter, T., Shenker, S., & Stoica, I. (2013) · Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles · doi:10.1145/2517349.2522737 · Cited by 982
Scaling Distributed Machine Learning with the Parameter Server
Li, M. (2014) · Proceedings of the 2014 International Conference on Big Data Science and Computing · doi:10.1145/2640087.2644155 · Cited by 979
State management in Apache Flink®: Consistent stateful distributed stream processing
Carbone, P., Ewen, S., Fóra, G., Haridi, S., Richter, S., & Tzoumas, K. (2017) · Proceedings of the VLDB Endowment · doi:10.14778/3137765.3137777 · Cited by 285
A survey on the evolution of stream processing systems
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Metadata
- Authors
- Murray, D. G., McSherry, F., Isaacs, R., Isard, M., Barham, P., & Abadi, M.
- Venue
- Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles
- Publisher
- ACM
- Published
- 2013-11-03
- Pages
- 439-455
- OpenAlex
- W2082171780
- Cited by
- 656
- References
- 37
- FWCI
- 44.63
- Type
- conference paper
- Language
- en
- Open access
- gold
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- Murray, D. G., McSherry, F., Isaacs, R., Isard, M., Barham, P., & Abadi, M. (2013). Naiad: a timely dataflow system. Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles. https://doi.org/10.1145/2517349.2522738
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
