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Automated Debugging of Big Data Analytics Using BigSift (Muhmammad Ali Gulzar & Miryung Kim)

547 views · Published 21 September 2018 · 26:26 · Indexed 8 November 2026

Channel: Databricks · 2018 · Science & Technology

Muhammad Ali Gulzar is a fourth year Ph.D candidate in the Programming Languages and Software Engineering (PLSE) Group at UCLA. Miryung Kim is an associate professor in the Department of Computer Science at UCLA as well as the cofounder of MK.Collective.

BigSift combines insights from automated fault isolation in software engineering and data provenance in database systems to find a minimum set of failure-inducing inputs. It redefines data provenance for the purpose of debugging using a test oracle function and implements several unique optimizations, specifically geared towards the iterative nature of automated debugging workloads. BigSift exposes an interactive web interface where a user can monitor a big data analytics job running remotely on the cloud, write a user-defined test oracle function, and then trigger the automated debugging process. BigSift also provides a set of predefined test oracle functions, which can be used for explaining common types of anomalies in big data analytics.

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Automated Debugging of Big Data Analytics Using BigSift (Muhmammad Ali Gulzar & Miryung Kim)

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