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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the block-oriented execution model in query processing for database systems, focusing on materialization and processing trade-offs. It explains how operators process input and emit output all at once, contrasting with tuple-at-a-time processing. The lecture delves into the challenges of output materialization, including naive and optimized versions, selection vectors, and tuple shuffling during joins. It also highlights the benefits of the block-oriented model, such as reduced per-tuple overhead, cache and SIMD efficiency, and the use of macros for evaluating expressions. The instructor emphasizes the importance of efficient processing models for data-intensive applications and systems.