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Emma in Action: Declarative Dataflows for Scalable Data Analysis

Summary: Emma in Action showcases a Scala-embedded dataflow language for declarative, scalable analysis. Quoting entire analyses and separating sequential control from parallel dataflow enables context-aware optimization and offloading to Spark or Flink. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5230
Venue
SIGMOD
Year
2016
Pagerank
5.093636e-05
Overall Rank
12,041 | 17.39%
DOI
10.1145/2882903.2889396

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{alexandrov_sigmod16,
        title = {{Emma in Action: Declarative Dataflows for Scalable Data Analysis}},
        author = {Alexandrov, Alexander and Salzmann, Andreas and Krastev, Georgi and Katsifodimos, Asterios and Markl, Volker},
        series = {{SIGMOD} '16},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2882903.2889396},
        url = {https://dl.acm.org/doi/10.1145/2882903.2889396},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
2,239 An Intermediate Representation for Optimizing Machine Learning Pipelines 2019 VLDB 8.8875753e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
292 LINQ: Reconciling Objects, Relations and XML in the .NET Framework 2006 SIGMOD 0.00022259549
2,717 Implicit Parallelism through Deep Language Embedding 2015 SIGMOD 8.2102313e-05
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