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Proceedings of the 34th International Conference on Scientific and Statistical Database Management

作者： Peter Baumann Larev-Scale Scientific Information Systems Jacobs University Germany

ISBN: (纸本)9781450396677

arrays as a fundamental data category have found their way into the orchestration of data models supported by databases. While OLAP "datacubes" can be emulated relationally to some extent it was in particular applications in science and engineering that have prompted support for arrays regardless of sparsity and with dedicated powerful array operators supporting n-D Tensor *** pioneer array DBMS, rasdaman ("raster data manager"), is a clean-slate DBMS implementation which, based on an algebraic foundation for query language, storage, architecture, and optimization, aiming at large-scale practical use. To satisfy the needs of datacube providers and users solutions had to be found which sometimes are driven by formalized concepts and sometimes by pragmatism, ultimately addressed through a fruitful collaboration of science and industry. Among such challenges addressed are: Novel algorithms for (distributed) array joins; deep support for space and time semantics in geo datacubes which has led to novel data and language concepts meantime adopted as standards; access control on regions within a cube, given the sheer datacube size; automated query splitting in federations of autonomous instances requires combining of global authentication with local authorization; last but not least, combining AI and datacubes is a current topic of active *** present the rasdaman array DBMS in a brief overview and discuss selected challenges, with emphasis on applications in the Earth sciences. Live demos will illustrate our talk.

关键词： OGC WCPS rasdaman array databases SQL/MDA

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HOW databases NO S QL HELPS TEACHING databases, GEOMETRY, AND REMOTE SENSING SIMULTANEOUSLY

HOW DATABASES NO S QL HELPS TEACHING DATABASES, GEOMETRY, AN...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Baumann, Peter Jacobs Univ Rasdaman GmbH Bremen Germany

ISBN: (纸本)9781728163741

array databases, offering actionable datacubes, are increasingly used for flexible,s callable Earth data services. Technically, array databases converge several concepts that are also taught - separately - in science ang engineering: Linear Algebra as in Analytical Geometry, query languages as in databases, and image processing as in remote sensing. This begs the question: can such a tool be used for such diverse teaching in a meaningful way, thereby also provoking possibly surprising new correlations with students? In following this idea, in this contribution we explore how array databases can serve for educational purposes in undergraduate education.

关键词： array databases teaching rasdaman WCPS

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arrays in databases from Underdog to First-Class Citizen 2020

Arrays in Databases from Underdog to First-Class Citizen

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32nd International Conference on Scientific and Statistical Database Management (SSDBM)

作者： Baumann, Peter Jacobs Univ Comp Sci Bremen Germany

ISBN: (纸本)9781450388146

array databases close a gap in the database ecosystem by adding modelling, storage, and processing support for multi-dimensional arrays. Built into "datacubes" such structures are known since long in OLAP and statistics, but they also appear as spatio-temporal sensor, image, simulation, and statistics data in all science and engineering *** our research we address array databases in all aspects, from concepts over architecture to applications. Our full-stack implementation rasdaman ("raster data manager"), which effectively has pioneered array databases, is in operational use on multi-Petabyte, federated Earth data assets. Based on this experience, the rasdaman team has initiated and shaped datacube standards such as ISO SQL/MDA (Multi-Dimensional arrays) and the OGC Earth datacube standards *** our talk we present concepts and implementation of rasdaman and show its application to Earth datacubes, illustrated by live demonstration of operational services.

关键词： array databases datacubes rasdaman SQL/MDA

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REMOTE SENSING ANALYTICS IN databases WITH ISO SQL/MDA 39

REMOTE SENSING ANALYTICS IN DATABASES WITH ISO SQL/MDA

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Misev, Dimitar Baumann, Peter Jacobs Univ Bremen Comp Sci & Elect Engn Campus Ring 1 D-28759 Bremen Germany

ISBN: (纸本)9781538691540

Database systems are essential components of modern services and applications. The remote sensing domain has predominantly been an exception to this trend so far, however, as common data types did not fit as well into the standard database model. Instead, various data management challenges have been addressed ad-hoc with custom proprietary / non-portable solutions. This is finally changing with the recent standardization of ISO SQL/MDA which extends SQL, the standard database query language, with support for data cube storage, management, and processing. This paper gives a high-level overview of SQL/MDA and how it can be used for building flexible, high-performance, and scalable remote sensing applications.

关键词： sql data cubes array databases standards

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Spatiotemporal Data-Cube Retrieval and Processing with xWCPS 4

Spatiotemporal Data-Cube Retrieval and Processing with xWCPS

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4th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM)

作者： Kakaletris, George Koltsida, Panagiota Kouvarakis, Manos Apostolopoulos, Konstantinos Commun & Informat Technol Experts SA Athens Greece Univ Athens Dept Informat & Telecommun Athens Greece

ISBN: (纸本)9789897582943

Management and processing of big data is inherently interweaved with the exploitation of their metadata, also "big" on their own, not only due to the increased number of datasets that get generated with continuously increased rates, but also due to the need for deeper and wider description of those data, which yields metadata of higher complexity and volume. Taking into account that generally data cannot be processed unless enough description is provided on their structure, origin, etc, accessing those metadata becomes crucial not only for locating the appropriate data but also for consuming them. The instruments to access those metadata shall be tolerant to their heterogeneity and loose structure. In this direction, xWCPS (XPath-enabled WCPS) is a novel query language that targets the spatiotemporal data cubes domain and tries to bring together metadata and multidimensional data processing under a single syntax paradigm limiting the need of using different tools to achieve this. It builds on the domain-established WCPS protocol and the widely adopted XPath language and yields new facilities to spatiotemporal datacubes analytics. Currently in its 2nd release, xWCPS, represents a major revision over its predecessor aiming to deliver improved, clearer, syntax and to ease implementation by its adopters.

关键词： Query Language array databases Coverages Metadata

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Location and Processing Aware Datacube Caching 17

Location and Processing Aware Datacube Caching

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29th International Conference on Scientifc and Statistical Database Management (SSDBM)

作者： Liaukevich, Veranika Misev, Dimitar Baumann, Peter Merticariu, Vlad Google Inc Montreal PQ Canada Jacobs Univ Bremen Germany

ISBN: (纸本)9781450352826

array databases are used to manage and query large N-dimensional arrays, such as sensor data, simulation models and imagery, as well as various time-series. Modern database systems and database applications make extensive use of caching techniques to improve performance. Research on array databases on the other hand has not explored the potential benefits of caching in query processing on big arrays. In this work we propose a design for a content-aware cache for array databases which allows to reuse results of previously evaluated queries. Besides identical query matching, our method also takes into account spatially overlapping queries and queries with common subexpressions. We evaluate performance of the query cache implementation by varying data and query parameters and show that it decreases query execution time by up to 93%, with a potential for even higher savings with increasing query complexity.

关键词： array databases query caching datacubes

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Interpolation as a Bridge Between Table and array Representations of Geofields in Spatial databases

Interpolation as a Bridge Between Table and Array Representa...

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11th International Conference on Beyond databases, Architectures and Structures (BDAS)

作者： Bajerski, Piotr Silesian Tech Univ Inst Informat Akad 16 PL-44101 Gliwice Poland

ISBN: (纸本)9783319184227;9783319184210

Development of database technology facilitates wider integration of diverse data types, which in turn increases opportunities to ask ad hoc queries, and gives new possibilities of declarative queries optimization. For more than a decade, work on supporting multidimensional arrays in databases has been carried out, which led to such DBMSs as rasdaman, SciDB and SciQL. However, the DBMSs lack the ability to handle queries concerning geographic phenomena varying continuously over space (called geofields) which were measured in irregularly distributed nodes (e.g. air pollution). This paper addresses this issue by presenting an extension of SQL making possible to write declarative queries referencing geofields, called geofield queries. Geofield query optimization opportunities are also shortly discussed.

关键词： Spatial databases array databases SQL GIS Geofield Coverage Interpolation

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Big Data Analytics for Earth Sciences:the EarthServer approach

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International Journal of Digital Earth 2016年第1期9卷 3-29页

作者： Peter Baumann Paolo Mazzetti Joachim Ungar Roberto Barbera Damiano Barboni Alan Beccati Lorenzo Bigagli Enrico Boldrini Riccardo Bruno Antonio Calanducci Piero Campalani Oliver Clements Alex Dumitrua,Mike Grant Pasquale Herzig George Kakaletris John Laxton Panagiota Koltsida Kinga Lipskoch Alireza Rezaei Mahdiraji Simone Mantovani Vlad Merticariu Antonio Messina Dimitar Misev Stefano Natali Stefano Nativi Jelmer Oosthoek Marco Pappalardo James Passmore Angelo Pio Rossi Francesco Rundo Marcus Sen Vittorio Sorbera Don Sullivan Mario Torrisi Leonardo Trovato Maria Grazia Veratelli Sebastian Wagner Large-Scale Scientific Information Systems Jacobs UniversityBremenGermany Rasdaman GmbH BremenGermany CNR-IIA National Research Council of ItalyInstitute of Atmospheric Pollution ResearchFlorenceItaly EOX IT Services GmbH ViennaAustria Consorzio COMETA CataniaItaly Division of Catania Italian National Institute for Nuclear PhysicsCataniaItaly Department of Physics and Astronomy University of CataniaCataniaItaly MEEO S.r.l. FerraraItaly Plymouth Marine Laboratory PlymouthUK Fraunhofer IGD DarmstadtGermany Athena Research and Innovation Center in Information Communication&Knowledge Technologies AthensGreece British Geological Survey EdinburghUK Software Engineering Italia S.r.l. CataniaItaly British Geological Survey KeyworthUK NASA Ames Research Center Moffett FieldCAUSA

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced *** and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and ***,Earth Science data and applications present specificities in terms of relevance of the geospatial information,wide heterogeneity of data models and formats,and complexity of ***,Big Earth Data Analytics requires specifically tailored techniques and *** EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets,built around a high performance array database technology,and the adoption and enhancement of standards for service interaction(OGC WCS and WCPS).The EarthServer solution,led by the collection of requirements from scientific communities and international initiatives,provides a holistic approach that ranges from query languages and scalability up to mobile access and *** result is demonstrated and validated through the development of lighthouse applications in the Marine,Geology,Atmospheric,Planetary and Cryospheric science domains.

关键词： big data Big Data Analytics array databases Earth Sciences interoperability standards

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array Database Scalability: Intercontinental Queries on Petabyte Datasets 16

Array Database Scalability: Intercontinental Queries on Peta...

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28th International Conference on Scientific and Statistical Database Management (SSDBM)

作者： Dumitru, Alex Mircea Merticariu, Vlad Baumann, Peter Jacobs Univ Bremen Campus Ring 1 D-28757 Bremen Germany

ISBN: (纸本)9781450342155

With the deluge of scientific big data affecting a large variety of research institutions, support for large multidimensional arrays has gained traction in the database community in the past decade. array databases aim to cover the gap left by traditional relational database systems in the domains of large scientific data by enabling researchers to efficiently store and process their data through rich declarative query languages. Such large amounts of data need effective systems that are able to distribute the processing at both local level, through exploitation of heterogeneous hardware as well as at network level, enabling both intra-cloud and intra-federation distribution of data and processing. In this demonstration we aim to showcase the capabilities of rasdaman by allowing users to execute queries that combine petabyte datasets stored at two institutions on different continents.

关键词： array databases rasdaman scientific databases heterogeneous-hardware exploitation cloud parallelization inter-federation parallelization distributed query processing

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Similarity Join over array Data 16

Similarity Join over Array Data

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ACM SIGMOD International Conference on Management of Data

作者： Zhao, Weijie Rusu, Florin Dong, Bin Wu, Kesheng UC Merced Merced CA 95343 USA Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9781450335317

Scientific applications are generating an ever-increasing volume of multi-dimensional data that are largely processed inside distributed array databases and frameworks Similarity join is a fundamental operation across scientific workloads that requires complex processing over an unbounded number of pairs of multi-dimensional points. In this paper, we introduce a novel distributed similarity join operator for multi-dimensional arrays. Unlike immediate extensions to array join and relational similarity join, the proposed operator minimizes the overall data transfer and network congestion while providing load-balancing, without completely repartitioning and replicating the input arrays. We define formally array similarity join and present the design, optimization strategies, and evaluation of the first array similarity join operator.

关键词： similarity join query optimization join processing integer programming array databases

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