Usability-based caching of query results in OLAP systems

Park, Chang-Sup; Kim, Myoung Ho; Lee, Yoon-Joon

doi:10.1016/s0164-1212(02)00142-5

Cited by 7 publications

(4 citation statements)

References 23 publications

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“…For example, the heuristic algorithms update the cache with regards to user data [6], storage of important user queries in a cache [7], storage of the cached data on multiple servers [8]. This paper solves the problem of the best use of a cache for execution of the user's queries.…”

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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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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“…A commonly used approach to process the OLAP queries efficiently is to exploit materialized views (MVs), i.e. the results of pre‐selected or previously issued queries are stored in DWs (Park et al , 2003). However, there is a trade‐off between response times and the storage requirements of pre‐aggregated data.…”

Section: Lessons Learned From Practicementioning

confidence: 99%

Understanding management data systems for enterprise performance management

Bose

2006

Industrial Management &Amp; Data Systems

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PurposeManaging enterprise performance is an important, yet a difficult process due to its complexity. The process involves monitoring the strategic focus of an enterprise, whose performance is measured from the analysis of data generated from a wide range of interrelated business activities performed at different levels within the enterprise. This study aims to investigate management data systems technologies in terms of how they are used and the issues that are related to their effective management within the broader context of enterprise performance management (EPM).Design/methodology/approachA range of recently published research literature on data warehousing, online analytic processing and EPM is reviewed to explore their current state, issues and challenges learned from their practice.FindingsThe findings of the study are reported in two parts. The first part discusses the current business practices of these technologies, and the second part identifies and discusses the issues and challenges the business managers dealing with these technologies face for gaining competitive advantage for their businesses.Originality/valueThe study findings are intended to assist the business managers to effectively understand the issues and technologies behind EPM implementation.

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“…Finally, pro-active proposals, with cache prefetching or restructuring (with dynamic recalculation of future needed subcubes) are two possible ways for finding solutions in this proposals class (Belo, 2000;Sapia, 2000). Moreover, the subsumption of future appraisal of subcubes (or fragments) in the admission and substitution cache politics is proposed in (Park, Kim, and Lee, 2003), being classified as pro-active proposals too. To completely characterize them we need an extra dimension that shows whose method is used to gain insight into the future.…”

Section: Related Workmentioning

confidence: 99%

Swarm Quant' Intelligence for Optimizing Multi-Node OLAP Systems

Loureiro

Belo

Progressive Methods in Data Warehousing and Business Intelligence

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Globalization and market deregulation has increased business competition, which imposed OLAP data and technologies as one of the great enterprise’s assets. Its growing use and size stressed underlying servers and forced new solutions. The distribution of multidimensional data through a number of servers allows the increasing of storage and processing power without an exponential increase of financial costs. However, this solution adds another dimension to the problem: space. Even in centralized OLAP, cube selection efficiency is complex, but now, we must also know where to materialize subcubes. We have to select and also allocate the most beneficial subcubes, attending an expected (changing) user profile and constraints. We now have to deal with materializing space, processing power distribution, and communication costs. This chapter proposes new distributed cube selection algorithms based on discrete particle swarm optimizers; algorithms that solve the distributed OLAP selection problem considering a query profile under space constraints, using discrete particle swarm optimization in its normal(Di-PSO), cooperative (Di-CPSO), multi-phase (Di-MPSO), and applying hybrid genetic operators.

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Usability-based caching of query results in OLAP systems

Cited by 7 publications

References 23 publications

Truth Space Method for Caching Database Queries

Truth Space Method for Caching Database Queries

Understanding management data systems for enterprise performance management

Swarm Quant' Intelligence for Optimizing Multi-Node OLAP Systems

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