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Advantages of Anytime Algorithm for Multi-Objective Query Optimization

EasyChair Preprint no. 8331

4 pagesDate: June 21, 2022


Data is becoming an important source of information these days. According to the recent Forbes survey, there are 2.5 quintillion bytes of data created each day at our current pace. While getting these amounts of data, it is necessary to process them in order to extract information. These data can be accessed in many ways in order to get meaningful information. This paper only deals with the query plans model through multi-objective optimization process using anytime algorithm. Query plans is an ordered stairway used for accessing data in SQL relational database systems. Query plans provides diverse tradeoff between conflicting cost matrices. The cost matrices are execution time, energy consumption and execution fees in multi-objective aspects. When SQL database run the queries by choosing an optimum query execution plan then it minimizes the query cost, which is very crucial for the query optimizer. Multi-objective query optimization and anytime algorithm possess very specific properties in order to support an interactive process which dynamically add various constraints and then finally select the best plan based on the continuously refined visualization of optimal cost tradeoffs. First, the anytime algorithms generate the multiple result plan sets which increase the quality with low latency rate between consecutive results. Second, the consecutive results will be incremented to avoid regenerating query plans when being invoked several times for the same query but with different user constraints. This paper deals with the advantages of anytime algorithm for the multi objective query optimization to analyze the complexity which offers an attractive tradeoff between the results. It can be used to update frequency, single invocation time complexity and multiple time over invocations. These properties make anytime algorithm suitable to be used within an interactive query optimization process.

Keyphrases: anytime algorithm, cost matrix, execution fee, execution time, multi-objective, Multi-Objective Query Optimization, multiple cost matrix, optimization process, Pareto frontier, query optimization, query optimization process, Query Plan, run-time

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Rituraj Rituraj and Annamária Várkonyi Kóczy},
  title = {Advantages of Anytime Algorithm for Multi-Objective Query Optimization},
  howpublished = {EasyChair Preprint no. 8331},

  year = {EasyChair, 2022}}
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