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• W2406681410 abstract "This talk will survey some results on join processing that use inequalities from convex geometry. Recently, Ngo, Porat, Rudra, and Re (NPRR) discovered the first relational join algorithm with worst-case optimal running time [8]. Since the seminal System R project [12], the dominant database optimizer paradigm optimizes a join query by examining each pair of joins and then combining these estimates using dynamic programming. In contrast, NPRR examines all relations at the same time. This change to the “one-join-at-a-time” dogma is important for performance: there are classes of queries for which any join-project plan is destined to be slower than the best possible run time by a polynomial factor in size of the data. NPRR’s analysis makes a link from database theory to a pair of beautiful inequalities: one due to Atserias, Grohe, and Marx from computer science [2] and one due to Bollobas and Thomason from geometry [4, Theorem 2]. In a recent survey with Ngo and Rudra [9], we simplified the algorithms and the arguments for such worst-case optimal join algorithms, and I plan to present these simplified results. Additionally, I plan to describe the LeapFrog TrieJoin, a worst-case optimizer from LogicBlox [14]. Similar inequalities also underpin recent efforts to optimize join algorithms on parallel infrastructures like MapReduce [1, 3]." @default.
• W2406681410 created "2016-06-24" @default.
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• W2406681410 date "2014-01-01" @default.
• W2406681410 modified "2023-09-24" @default.
• W2406681410 title "Links between Join Processing and Convex Geometry." @default.
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