Declarative Error Management for Robust Data-Intensive Applications
Summary: Declarative error management for data-intensive apps using a data type: partial result with errors; operators continue on errors. Extends error-unaware operators, uses declarative semantics, and runs on a distributed engine with 20% instrumentation. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pig Latin: A Not-So-Foreign Language for Data Processing | 2008 | SIGMOD | 0.0024183614 |
| 22 | SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets | 2008 | VLDB | 0.0008456613 |
| 70 | Hive - A Warehousing Solution Over a Map-Reduce Framework | 2009 | VLDB | 0.00059533166 |
| 528 | Database Relations with Null Values (Extended Abstract) | 1982 | PODS | 0.0002084153 |
| 1,265 | Jaql: A Scripting Language for Large Scale Semistructured Data Analysis | 2011 | VLDB | 0.00012947629 |
| 1,789 | Reducing the Braking Distance of an SQL Query Engine | 1998 | VLDB | 0.00010555087 |
| 4,603 | Inspector Gadget: A Framework for Custom Monitoring and Debugging of Distributed Dataflows | 2011 | VLDB | 6.0554018e-05 |
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