Robust heuristic algorithms for exploiting the common tasks of relational cloud database queries

Dökeroğlu, Tansel; Bayır, Murat Ali; Çoşar, Ahmet

doi:10.1016/j.asoc.2015.01.026

Cited by 31 publications

(13 citation statements)

References 40 publications

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“…Related work is presented by Safaeei A et al [18] that optimize overlapping queries with common sub-expressions using multiple sliding windows. Executing and caching the shared sub-queries at the sites with the lowest communication cost and shipping the output to the sites that need them as input are important factors that improve the total execution time [24]. EARL supports for processing part of input data instead of entire data by using early results for the analytical queries in MapReduce.…”

Section: Catching Intermediate Queries or Resultsmentioning

confidence: 99%

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Query Optimization for Databases in Cloud Environment: A Survey

Bachhav¹,

Kharat²,

Shelar³

2017

IJDTA

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Section: Catching Intermediate Queries or Resultsmentioning

confidence: 99%

“…Dokeroglu et al [24] has proposed a system in which alternative query plans are generated. Robust heuristic algorithms e.g.…”

Section: Overview Of Traditional Sql and Mapreducementioning

confidence: 99%

Query Optimization for Databases in Cloud Environment: A Survey

Bachhav¹,

Kharat²,

Shelar³

2017

IJDTA

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“…Using cloud storages one can afford a lot of computational resources for a short time to execute complicated queries effectively on large data with a help of virtual machine clusters [15,16,17,18]. A set of reliable heuristic algorithms is used.…”

Section: Existing Solutions Overview and Comparisonmentioning

confidence: 99%

Truth Space Method for Caching Database Queries

Мосин¹,

Зыкин²

2015

Model. anal. inf. sist.

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We propose a new method of client-side data caching for relational databases with a central server and distant clients. Data are loaded into the client cache based on queries executed on the server. Every query has the corresponding DB tablethe result of the query execution. These queries have a special form called "universal relational query" based on three fundamental Relational Algebra operations: selection, projection and natural join. We have to mention that such a form is the closest one to the natural language and the majority of database search queries can be expressed in this way. Besides, this form allows us to analyze query correctness by checking lossless join property. A subsequent query may be executed in a client's local cache if we can determine that the query result is entirely contained in the cache. For this we compare truth spaces of the logical restrictions in a new user's query and the results of the queries execution in the cache. Such a comparison can be performed analytically , without need in additional Database queries. This method may be used to define lacking data in the cache and execute the query on the server only for these data. To do this the analytical approach is also used, what distinguishes our paper from the existing technologies. We propose four theorems for testing the required conditions. The first and the third theorems conditions allow us to define the existence of required data in cache. The second and the fourth theorems state conditions to execute queries with cache only. The problem of cache data actualizations is not discussed in this paper. However, it can be solved by cataloging queries on the server and their serving by triggers in background mode.

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“…Given a set of rectangular items and 2D bins of fixed width and Q4 variable length, the 2D bin packing problem (2DBPP) consists of orthogonally placing all the pieces within the bin, without overlapping, such that the overall number of the bins is minimized [1][2][3][4][5][6]. The 2DBPP is an intractable combinatorial optimization problem and widely faced during the industrial manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%