D/sup 3/G: novel approaches to data statistics, understanding and preprocessing on the grid

Wöhrer, Alexander; Nováková, Lenka; Brezány, Peter; Tjoa, A. Min

doi:10.1109/aina.2006.137

Cited by 4 publications

(6 citation statements)

References 6 publications

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“…For each schema to be included, there has to be a includeSchema entry, with the possibility to exclude certain tables from the monitoring via the excludeTables attribute. If D 3 G [25] exact continuous data statistic functionality is available in this database, the schema containing the statistics table and its name have to be specified via the continuousDS element. The extraction of the monitoring information is different for each database system and is done by the Java class defined in the DBInfoImpl element.…”

Section: Methodsmentioning

confidence: 99%

“…the connection time, to give a possible forecast (via data mining techniques) or a historical view on the relational database. Exact continuous data statistics are done via a part of D 3 G [25] which is currently only available for Oracle 10g.…”

Section: Methodsmentioning

confidence: 99%

“…We exposes available histograms of a relational database in a homogeneous way. The monitoring service builds on our earlier work done for the D 3 G framework [25] to also provide exact continuous statistics (minimum and maximum values of a column, missing values, etc.) for certain parts of a database (likely to be the ones used frequently via the Grid).…”

Section: Architecturementioning

confidence: 99%

“…The number of sources to be included in a distributed query plan can so be minimized as well as the operator distribution improved by providing similar information about candidate data sources to a distributed query processor, e.g. OGSA-DQP [4], in a unified way as centralized ones have, like histograms [16] and exact data statistics [25]. In [15], the importance of data statistics towards query optimization is described in more detail.…”

Section: Preliminaries: Novel Usage Scenariosmentioning

confidence: 99%

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A Monitoring Service for Relational Databases to Support Advanced Data Integration on the Grid

Woehrer

Brezány

2007

First International Conference on Complex, Intelligent and Software Intensive Systems (CISIS'07)

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The trend of Grid computing towards more data intensive applications, accessing more and more relational databases and requiring advanced data integration, is still upstanding. Metadata information, e.g. for selection of suitable candidates among similar sources and the exclusion of not required ones, plays a vital role for efficient data integration on the Grid.However, there is a lack of service oriented monitoring tools providing this metadata for relational data sources. We stay abreast of this development and make relational databases first class citizens in Grid computing by providing a service oriented monitoring tool tailored towards them. To the best of our knowledge, no research effort has been reported on this so far. This paper presents novel usage scenarios needing additional metadata and monitoring information about relational data sources on the Grid -in the areas of query optimization, adaptive query processing and data integration management -and requirements to be fulfilled by a monitoring service providing such information. Our approach supports coarse and fine grained information about heterogeneous relational databases via a uniform interface and provides a homogeneous view on the available metadata.We have evaluated our approach by implementing a research prototype based on the Web Service Resource Framework implementation of the current Globus Toolkit. The functionality and performance of the prototype is demonstrated for commonly used relational databases such as MySQL, PostgreSQL and Oracle.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Architecturementioning

confidence: 99%

Section: Preliminaries: Novel Usage Scenariosmentioning

confidence: 99%

See 2 more Smart Citations

A Monitoring Service for Relational Databases to Support Advanced Data Integration on the Grid

Woehrer

Brezány

2007

First International Conference on Complex, Intelligent and Software Intensive Systems (CISIS'07)

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“…The number of sources to be included in a distributed query plan can so be minimized as well as the operator distribution improved. Similar information about candidate data sources as centralized ones have, like histograms [12] and exact data statistics [13], might be used by a distributed query processor, e.g. OGSA-DQP [14].…”

Section: A Query Optimizationmentioning

confidence: 99%

Towards a Novel Metadata Information Service for Distributed Data Management

Woehrer¹,

Brezány

2007

JNW

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The trend in Grid computing towards more data intensive applications, accessing more and more relational databases and requiring advanced integration of secondhand and publicly available data sources, is still upstanding. Rich metadata information about these data sources plays a vital role for efficient distributed data management. There is a lack of service oriented monitoring tools providing a rich set of metadata for data sources, in contrast to the established usage of monitoring and metadata information tools for network and computational Grid resources. We allow the improved integration and exploitation of data sources in service-oriented architectures by providing a service oriented monitoring tool, named DSMON, for them – initially focusing on relational databases. Our approach supports coarse and fine grained information about heterogeneous relational databases via a uniform interface and provides a homogeneous view on the available metadata. This paper presents novel usage scenarios needing a monitoring service as well as important requirements to be fulfilled by such a service. Our research prototype is not bound to a specific data access middleware nor necessarily tightly coupled with other components. Therefore it can play a vital role in any service oriented infrastructure targeted towards advanced data access, integration and management. The functionality and performance of the DSMON prototype is demonstrated for commonly used relational databases such as MySQL, PostGRE and Oracle. DSMON is an essential component of a more general metadata information service, called DSMIS, for data sources providing advanced funtionalities like prediction of the future behavior of a data source and external metadata updates. We introduce its overall architecture and discuss its novel functionalities.

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Active Integration of Databases in Grids for Scalable Distributed Query Processing

Wöhrer

Brezány

2008

On the Move to Meaningful Internet Systems: OTM 2008

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D/sup 3/G: novel approaches to data statistics, understanding and preprocessing on the grid

Cited by 4 publications

References 6 publications

A Monitoring Service for Relational Databases to Support Advanced Data Integration on the Grid

A Monitoring Service for Relational Databases to Support Advanced Data Integration on the Grid

Towards a Novel Metadata Information Service for Distributed Data Management

Active Integration of Databases in Grids for Scalable Distributed Query Processing

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