By Amol Deshpande
Adaptive question Processing surveys the elemental concerns, concepts, expenditures, and advantages of adaptive question processing. It starts with a vast assessment of the sphere, determining the size of adaptive innovations. It then seems to be on the spectrum of techniques on hand to conform question execution at runtime - essentially in a non-streaming context. The emphasis is on simplifying and abstracting the main innovations of every strategy, instead of reproducing the entire info to be had within the papers. The authors establish the strengths and boundaries of the several ideas, exhibit after they are most respected, and recommend attainable avenues of destiny examine. Adaptive question Processing serves as a precious reference for college students of databases, offering an intensive survey of the realm. Database researchers will take advantage of a extra entire perspective, together with a few ways which they might not have excited by in the scope in their personal examine.
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Adaptive question Processing surveys the basic concerns, recommendations, expenses, and merits of adaptive question processing. It starts off with a large review of the sphere, settling on the size of adaptive innovations. It then seems on the spectrum of ways on hand to evolve question execution at runtime - basically in a non-streaming context.
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Additional resources for Adaptive Query Processing (Foundations and Trends in Databases)
Such operators dramatically reduce the number of plans considered by the query optimizer, although potentially at the cost of some runtime performance. 2 Parametric Query Optimization An alternative to finding a single robust query plan is to find a small set of plans that are appropriate for different situations. Parametric query optimizers [46, 52, 70] postpone certain planning decisions to runtime, and are especially attractive in scenarios where queries are compiled once and executed repeatedly, possibly with minor parameter changes.
This makes it hard to analyze or reason about the behavior of these systems. As an example, the commonly used “explain” feature (used to inspect the execution plan used by the DBMS for a query) would be nearly impossible to support in such systems. Throughout this survey, along with the adaptivity loop, we will also discuss how to do a retrospective analysis of an adaptive query execution, after it has finished running. 3 Post-mortem Analysis of Adaptive Techniques 41 possible, to express the query execution in terms of traditional query plans or relational algebra expressions.
Plan: Based on the analysis, an adaptive system makes certain decisions about how the system behavior should be changed. Actuate: After the decision is made, the adaptive system executes the decision, by possibly doing extra work to manipulate the system state. In the context of adaptive query processing, the Measure step involves monitoring data characteristics like cardinalities and distributions, and system characteristics like memory utilization and network bandwidth. Analysis is primarily done with respect to performance goals or estimates, although there have been some recent proposals for broader QOS-aware DBMSs that address goals like availability [14, 57, 66, 84, 106].