A Systematic Review on Materialized View Selection

Gosain, Anjana; Sachdeva, Kavita

doi:10.1007/978-981-10-3153-3_66

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…A materialized view is a database entity containing the query results. For example, it may be a local copy of remotely located data, or it may be a subset of a table's rows and/or columns, or it may be a description that uses an aggregate function [25].…”

Section: Overview Of Data Warehousing Materialized Viewmentioning

confidence: 99%

Hybrid e-Government Framework based on Datawarehousing and MAS for Data Interoperability

Oumkaltoum¹,

Omar²,

Aris³

et al. 2021

IJACSA

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Section: Overview Of Data Warehousing Materialized Viewmentioning

confidence: 99%

Hybrid e-Government Framework based on Datawarehousing and MAS for Data Interoperability

Oumkaltoum¹,

Omar²,

Aris³

et al. 2021

IJACSA

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“…Extensive research has been conducted around the materialized view selection problem, as evidenced in several systematic reviews on the topic by [13], [14], and [15] to mention some of them. The approaches surveyed in these works consist in general of two main steps:…”

Section: Related Workmentioning

confidence: 99%

A Workload-Driven Approach for View Selection in Large Dimensional Datasets

et al. 2020

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The information explosion the world has witnessed in the last two decades has forced businesses to adopt a data-driven culture for them to be competitive. These data-driven businesses have access to countless sources of information, and face the challenge of making sense of overwhelming amounts of data in a efficient and reliable manner, which implies the execution of readintensive operations. In the context of this challenge, a framework for the dynamic read-optimization of large dimensional datasets has been designed, and on top of it a workload-driven mechanism for automatic materialized view selection and creation has been developed. This paper presents an extensive description of this mechanism, along with a proof-of-concept implementation of it and its corresponding performance evaluation. Results show that the proposed mechanism is able to derive a limited but comprehensive set of views leading to a drop in query latency ranging from 80% to 99.99% at the expense of 13% of the disk space used by the base dataset. This way, the devised mechanism enables speeding up query execution by building materialized views that match the actual demand of query workloads.

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Exploiting Shared Sub-Expression and Materialized View Reuse for Multi-Query Optimization

Gurumurthy,

Bidarkar,

Broneske

et al. 2024

Inf Syst Front

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Querying in isolation lacks the potential of reusing intermediate results, which ends up wasting computational resources. Multi-Query Optimization (MQO) addresses this challenge by devising a shared execution strategy across queries, with two generally used strategies: batched or cached. These strategies are shown to improve performance, but hardly any study explores the combination of both. In this work we explore such a hybrid MQO, combining batching (Shared Sub-Expression) and caching (Materialized View Reuse) techniques. Our hybrid-MQO system merges batched query results as well as caches the intermediate results, thereby any new query is given a path within the previous plan as well as reusing the results. Since caching is a key component for improving performance, we measure the impact of common caching techniques such as FIFO, LRU, MRU and LFU. Our results show LRU to be the optimal for our usecase, which we use in our subsequent evaluations. To study the influence of batching, we vary the factor - - which represents the similarity of the results within a query batch. Similarly, we vary the cache sizes to study the influence of caching. Moreover, we also study the role of different database operators in the performance of our hybrid system. The results suggest that, depending on the individual operators, our hybrid method gains a speed-up between 4x to a slowdown of 2x from using MQO techniques in isolation. Furthermore, our results show that workloads with a generously sized cache that contain similar queries benefit from using our hybrid method, with an observed speed-up of 2x over sequential execution in the best case.

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A Systematic Review on Materialized View Selection

Cited by 3 publications

References 33 publications

Hybrid e-Government Framework based on Datawarehousing and MAS for Data Interoperability

Hybrid e-Government Framework based on Datawarehousing and MAS for Data Interoperability

A Workload-Driven Approach for View Selection in Large Dimensional Datasets

Exploiting Shared Sub-Expression and Materialized View Reuse for Multi-Query Optimization

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