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Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb

Summary: Breadcrumb provides query-based explanations for missing Spark results on nested data, pinpointing the operators responsible for the absence. It scales to big data and handles schema-semantic errors in nested/de-normalized queries, guiding fixes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12458
Venue
VLDB
Year
2021
Pagerank
4.3005882e-05
Overall Rank
9,704 | 32.50%
DOI
10.14778/3476311.3476331

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
5,826 Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals 2023 VLDB 5.3124507e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
487 Why Not? 2009 SIGMOD 0.00022050218
611 Lineage Tracing for General Data Warehouse Transformations 2001 VLDB 0.00019231115
968 Schema and Ontology Matching with COMA++ 2005 SIGMOD 0.0001495703
6,975 NLProveNAns: Natural Language Provenance for Non-Answers 2018 VLDB 4.8772572e-05
7,678 To Not Miss the Forest for the Trees - A Holistic Approach for Explaining Missing Answers over Nested Data 2021 SIGMOD 4.6813062e-05
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