Pro Oracle Spatial

Kothuri, Ravi; Godfrind, Albert; Beinat, Euro

doi:10.1007/978-1-4302-0735-1

Cited by 23 publications

(13 citation statements)

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“…Our query evaluation and reevaluation algorithms have been completely implemented using PL/SQL. -Oracle Spatial [33], which defines what is essentially an abstract data type that conforms to the object-relational model and is used for modelling various spatial objects in the database. In our system, we have utilized and extended the data type to model and represent spatial-temporal trajectories and continuous queries.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…For example, Pfoser et al [28] attempt to preserve the segments that belong to the same trajectory, and the problem of obtaining an efficient splitting of the trajectory segments has been further investigated in [8], [18], [32]. In our work, we relied on the R * tree indexing mechanism that is readily available in Oracle 9i [33], for indexing the two dimensional routes of the trajectories. However, we have adopted it for various needs, e.g., indexing the trajectory segments, using the time information of trajectories in a refinement step etc.…”

Section: Related Workmentioning

confidence: 99%

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Efficient Maintenance of Continuous Queries for Trajectories

Trajcevski

Scheuermann

2007

Geoinformatica

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We address the problem of optimizing the maintenance of continuous queries in Moving Objects Databases, when a set of pending continuous queries need to be reevaluated as a result of bulk updates to the trajectories of moving objects. Such bulk updates may happen when traffic abnormalities, e.g., accidents or road works, affect a subset of trajectories in the corresponding regions, throughout the duration of these abnormalities. The updates to the trajectories may in turn affect the correctness of the answer sets for the pending continuous queries in much larger geographic areas. We present a comprehensive set of techniques, both static and dynamic, for improving the performance of reevaluating the continuous queries in response to the bulk updates. The static techniques correspond to specifying the values for the various semantic dimensions of trigger execution. The dynamic techniques include an in-memory shared reevaluation algorithm, extending query indexing to queries described by trajectories and query reevaluation ordering based on space-filling curves. We have completely implemented our system prototype on top of an existing Object-Relational Database Management System, Oracle 9i, and conducted extensive experimental evaluations using realistic data sets to demonstrate the validity of our approach.

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Section: Experimental Evaluationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Efficient Maintenance of Continuous Queries for Trajectories

Trajcevski

Scheuermann

2007

Geoinformatica

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“…Healey and J. Delve indexes to optimize star joins, as noted above (Lane 2005). The spatial data held in object-relational structures, rather than in the DW itself, are searched by means of R-tree-based spatial indexes, which may be extensible to four dimensions, to include time also (Kothuri et al 2004). While such systems currently lack query language operators that link OLAP and spatial searching, if a ROLAP approach is adopted by the database package in question, relevant operators used by the different processing modules can be combined into single yet very complex queries.…”

Section: Recent Developments In Gis and Data Warehousingmentioning

confidence: 99%

“…The spatial functionality provides basic compliance with OGC specifications and is expected broadly to keep pace with developments in this area (Kothuri et al 2004). The DW sub-system is a ROLAP-type implementation of cube and dimension table structures inside the database, and it supports a large set of OLAP extensions to SQL, which allow sub-setting of the cube table and generation of summary data/ statistics 'on-the-fly'.…”

Section: Choice Of Implementation Vehiclementioning

confidence: 99%

Integrating GIS and data warehousing in a Web environment: A case study of the US 1880 Census

Healey¹,

Delve²

2007

International Journal of Geographical Information Science

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While the business intelligence sector, involving data warehouses and online analytical processing (OLAP) technologies, is experiencing strong growth in the IT marketplace, relatively little attention has been devoted to the problem of utilizing such tools in conjunction with GIS. This study contributes to the development of this research area by examining the issues involved in the design and implementation of an integrated data warehouse and GIS system that delivers analytical OLAP and mapping results in real-time across the Web. The case study chosen utilizes individual records from the US 1880 population census, which have recently been made available by the North Atlantic Population Project. Although historical datasets of this kind present a number of challenges for data warehousing, the results indicate that the integrated approach adopted offers a much more flexible and powerful analytical methodology for this kind of large social science dataset than has hitherto been available.

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“…Take the above scenario as an example, the service system receives location updates from all tourists once every minute; it is too expensive to evaluate all location updates against the query criteria of all registered restaurants in the database server. Yet it is not necessary to do so because each query includes both spatial criteria and non-spatial criteria [8,12] and an answer update should be delivered only if both criteria are met, e.g., location updates of tourists preferring Indian cuisine need not be evaluated even if they are in the area of Chinatown; likewise, location updates of tourists that are too far away from Chinatown need not be evaluated even if they do like Chinese food. In summary, query evaluation against irrelevant updates should be avoided as much as possible to reduce database burden and average response time.…”

Section: Introductionmentioning

confidence: 99%

QACHE: Query Caching in Location-Based Services

Yalamanchi

Kothuri

Ravada

et al.

Progress in Spatial Data Handling

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Abstract. Many emerging applications of location-based services continuously monitor a set of moving objects and answer queries pertaining to their locations. Query processing in such services is critical to ensure high performance of the system. Observing that one predominant cost in query processing is the frequent accesses to the database, in this paper we describe how to reduce the number of moving object to database server round-trips by caching query information on the application server tier. We propose a novel caching framework, named QACHE, which stores and organizes spatially-relevant queries for selected moving objects. QACHE leverages the spatial indices and other algorithms in the database server for organizing and refreshing relevant cache entries within a configurable area of interest, referred to as the cache-footprint, around a moving object. QACHE contains appropriate refresh policies and prefetching algorithms for efficient cache-based evaluation of queries on moving objects. In experiments comparing QACHE to other proposed mechanisms, QACHE achieves a significant reduction (from 63% to 99%) in database accesses thereby improving the throughput of an LBS system.

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Pro Oracle Spatial

Cited by 23 publications

References 0 publications

Efficient Maintenance of Continuous Queries for Trajectories

Efficient Maintenance of Continuous Queries for Trajectories

Integrating GIS and data warehousing in a Web environment: A case study of the US 1880 Census

QACHE: Query Caching in Location-Based Services

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