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)
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Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,189 | An Intermediate Representation for Optimizing Machine Learning Pipelines | 2019 | VLDB | 9.0524569e-05 |
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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 |
|---|---|---|---|---|
| 282 | LINQ: Reconciling Objects, Relations and XML in the .NET Framework | 2006 | SIGMOD | 0.00022538522 |
| 2,668 | Implicit Parallelism through Deep Language Embedding | 2015 | SIGMOD | 8.3379414e-05 |
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