Dissertation/ Thesis
Challenges of indexing multi-dimensional persistent data
| Title: | Challenges of indexing multi-dimensional persistent data |
|---|---|
| Authors: | Zahra, Rebecca (2015) |
| Publisher Information: | University of Malta Faculty of Information and Communication Technology. Department of Computer Information Systems |
| Publication Year: | 2015 |
| Collection: | University of Malta: OAR@UM / L-Università ta' Malta |
| Subject Terms: | Information retrieval, Data structures (Computer science), Database management, Dimensional analysis -- Data processing |
| Description: | M.SC.COMP.INFO.SYS. ; There is an exponential growth in the demand for high dimensional data; and example of which is spatial data. The increase in this type of data pushes for a different solution some kind of solution to be able to retrieve it efficiently compared to single dimensional data. Indexes are one of the main options which can help in efficient data retrieval. However the selection of an appropriate index for a specific use case is a complex task and only approximate solutions can be attained. This is mainly due to the variety of factors which effect the performance of an indexing structure and its costs. These include namely data characteristics, types of queries and memory parameters. Environmental weather data is considered as the main use case throughout this research. A domain expert from the Maltese meteorological office, Mr J. Schiavone, identified the generic datasets required and the main operational and tactical queries involved in meteorology with a local context. This expertise provided the basis for the selection of adequate meteorological data sets and how queries need to be developed. The analysis process involved the execution of many queries on raster and vector data. The performance of such queries was evaluated before and after indexing structures were introduced. Besides, additional adjustments such as the usage of partial or expressional indexes and other memory tweaking were taken into account. To ensure that all queries are treated equally the data server was restarted before every query. After considering the above factors a top-down, holistic approach is adopted to select appropriate indexes for meteorological queries based on the previous analysis evaluation and a cost benefit analysis. Although query optimisation per statement might be used the procedure adopted for this research was adopted for the set of data queries as a whole. The analysis showed that particular indexes are more targeted towards particular que1y types. Moreover, the functions chosen when formulating an ... |
| Document Type: | master thesis |
| Language: | English |
| Relation: | https://www.um.edu.mt/library/oar/handle/123456789/78380 |
| Availability: | https://www.um.edu.mt/library/oar/handle/123456789/78380 |
| Rights: | info:eu-repo/semantics/restrictedAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. |
| Accession Number: | edsbas.2FF80BEB |
| Database: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://www.um.edu.mt/library/oar/handle/123456789/78380# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Header | DbId: edsbas DbLabel: BASE An: edsbas.2FF80BEB RelevancyScore: 702 AccessLevel: 3 PubType: Dissertation/ Thesis PubTypeId: dissertation PreciseRelevancyScore: 701.549072265625 |
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| Items | – Name: Title Label: Title Group: Ti Data: Challenges of indexing multi-dimensional persistent data – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zahra%2C+Rebecca+%282015%29%22">Zahra, Rebecca (2015)</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: University of Malta<br />Faculty of Information and Communication Technology. Department of Computer Information Systems – Name: DatePubCY Label: Publication Year Group: Date Data: 2015 – Name: Subset Label: Collection Group: HoldingsInfo Data: University of Malta: OAR@UM / L-Università ta' Malta – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Data+structures+%28Computer+science%29%22">Data structures (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Database+management%22">Database management</searchLink><br /><searchLink fieldCode="DE" term="%22Dimensional+analysis+--+Data+processing%22">Dimensional analysis -- Data processing</searchLink> – Name: Abstract Label: Description Group: Ab Data: M.SC.COMP.INFO.SYS. ; There is an exponential growth in the demand for high dimensional data; and example of which is spatial data. The increase in this type of data pushes for a different solution some kind of solution to be able to retrieve it efficiently compared to single dimensional data. Indexes are one of the main options which can help in efficient data retrieval. However the selection of an appropriate index for a specific use case is a complex task and only approximate solutions can be attained. This is mainly due to the variety of factors which effect the performance of an indexing structure and its costs. These include namely data characteristics, types of queries and memory parameters. Environmental weather data is considered as the main use case throughout this research. A domain expert from the Maltese meteorological office, Mr J. Schiavone, identified the generic datasets required and the main operational and tactical queries involved in meteorology with a local context. This expertise provided the basis for the selection of adequate meteorological data sets and how queries need to be developed. The analysis process involved the execution of many queries on raster and vector data. The performance of such queries was evaluated before and after indexing structures were introduced. Besides, additional adjustments such as the usage of partial or expressional indexes and other memory tweaking were taken into account. To ensure that all queries are treated equally the data server was restarted before every query. After considering the above factors a top-down, holistic approach is adopted to select appropriate indexes for meteorological queries based on the previous analysis evaluation and a cost benefit analysis. Although query optimisation per statement might be used the procedure adopted for this research was adopted for the set of data queries as a whole. The analysis showed that particular indexes are more targeted towards particular que1y types. Moreover, the functions chosen when formulating an ... – Name: TypeDocument Label: Document Type Group: TypDoc Data: master thesis – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://www.um.edu.mt/library/oar/handle/123456789/78380 – Name: URL Label: Availability Group: URL Data: https://www.um.edu.mt/library/oar/handle/123456789/78380 – Name: Copyright Label: Rights Group: Cpyrght Data: info:eu-repo/semantics/restrictedAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. – Name: AN Label: Accession Number Group: ID Data: edsbas.2FF80BEB |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English Subjects: – SubjectFull: Information retrieval Type: general – SubjectFull: Data structures (Computer science) Type: general – SubjectFull: Database management Type: general – SubjectFull: Dimensional analysis -- Data processing Type: general Titles: – TitleFull: Challenges of indexing multi-dimensional persistent data Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zahra, Rebecca (2015) IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2015 Identifiers: – Type: issn-locals Value: edsbas |
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