Query-based Why-not Explanations for Nested Data

Authors

• Ralf Diestelkämper
• Boris Glavic
• Melanie Herschel
• Seokki Lee

Materials

Abstract

We present the first query-based approach for explaining missing answers to queries over nested relational data which is a common data format used by big data systems such as Apache Spark. Our main contributions are a novel way to define query-based why-not provenance based on repairs to queries and presenting an implementation and preliminary experiments for answering such queries in Spark.

bibtex

@inproceedings{DG19a,
  author = {Diestelk\"amper, Ralf and Glavic, Boris and Herschel, Melanie and Lee, Seokki},
  booktitle = {Proceedings of the 11th USENIX Workshop on the Theory and Practice of Provenance},
  isworkshop = {true},
  keywords = {Provenance; Missing Answers},
  pdfurl = {http://cs.iit.edu/%7edbgroup/assets/pdfpubls/DG19.pdf},
  title = {Query-based Why-not Explanations for Nested Data},
  venueshort = {TaPP},
  year = {2019}
}

Reference

Query-based Why-not Explanations for Nested Data Ralf Diestelkämper, Boris Glavic, Melanie Herschel and Seokki Lee Proceedings of the 11th USENIX Workshop on the Theory and Practice of Provenance (2019).