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Adaptive Parallelization of Queries over Dependent Web Service Calls
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (UDBL)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (UDBL)
2009 (English)In: Proc. 25th International Conference on Data Engineering, Piscataway, NJ: IEEE , 2009, 1725-1732 p.Conference paper, Published paper (Refereed)
Abstract [en]

We have developed a system to process database queries over composed data providing web services. The queries are transformed into execution plans containing an operator that invokes any web service for given arguments. A common pattern in these query execution plans is that the output of one web service call is the input for another, etc. The challenge addressed in this paper is to develop methods to speed up such dependent calls in queries by parallelization. Since web service calls incur high-latency and message set-up costs, a naïve approach making the calls sequentially is time consuming and parallel invocations of the web service calls should improve the speed. Our approach automatically parallelizes the web service calls by starting separate query processes, each managing a parameterized sub-query, a plan function, for different parameter tuples. For a given query, the query processes are automatically arranged in a multi-level process tree where plan functions are called in parallel. The parallel plan is defined in terms of an algebra operator, FF_APPLYP, to ship in parallel to other query processes the same plan function for different parameters. By using FF_APPLYP we first investigated ways to set up different process trees manually. We concluded from our experiments that the best performing query execution plan is an almost balanced bushy tree. To automatically achieve the optimal process tree we modified FF_APPLYP to an operator AFF_APPLYP that adapts a parallel plan locally in each query process until an optimized performance is achieved. AFF_APPLYP starts with a binary process tree. During execution each query process in the tree makes local decisions to expand or shrink its process sub-tree by comparing the average time to process each incoming tuple. The query execution time obtained with AFF_APPLYP is shown to be close to the best time achieved by manually built query process trees.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE , 2009. 1725-1732 p.
National Category
Computer Science Computer Science
Research subject
Computer Science with specialization in Database Technology
Identifiers
URN: urn:nbn:se:uu:diva-100901DOI: 10.1109/ICDE.2009.148ISBN: 978-1-4244-3422-0 (print)OAI: oai:DiVA.org:uu-100901DiVA: diva2:211236
Projects
SIDA and Swedish Foundation for Strategic Research under contract RIT08-0041
Available from: 2009-04-14 Created: 2009-04-10 Last updated: 2010-08-30Bibliographically approved
In thesis
1. Querying Data Providing Web Services
Open this publication in new window or tab >>Querying Data Providing Web Services
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Web services are often used for search computing where data is retrieved from servers providing information of different kinds. Such data providing web services return a set of objects for a given set of parameters without any side effects. There is need to enable general and scalable search capabilities of data from data providing web services, which is the topic of this Thesis.

The Web Service MEDiator (WSMED) system automatically provides relational views of any data providing web service operations by reading the WSDL documents describing them. These views can be queried with SQL. Without any knowledge of the costs of executing specific web service operations the WSMED query processor automatically and adaptively finds an optimized parallel execution plan calling queried data providing web services.

For scalable execution of queries to data providing web services, an algebra operator PAP adaptively parallelizes calls in execution plans to web service operations until no significant performance improvement is measured, based on monitoring the flow from web service operations without any cost knowledge or extensive memory usage.

To comply with the Everything as a Service (XaaS) paradigm WSMED itself is implemented as a web service that provides web service operations to query and combine data from data providing web services. A web based demonstration of the WSMED web service provides general SQL queries to any data providing web service operations from a browser.

WSMED assumes that all queried data sources are available as web services. To make any data providing system into a data providing web service WSMED includes a subsystem, the web service generator, which generates and deploys the web service operations to access a data source. The WSMED web service itself is generated by the web service generator.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2010. 37 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 755
Keyword
views of web service operations, web service queries, adaptive parallelization, query optimization
National Category
Computer Science
Research subject
Computer Science with specialization in Database Technology
Identifiers
urn:nbn:se:uu:diva-128928 (URN)978-91-554-7852-0 (ISBN)
Public defence
2010-10-08, Room 1211, Polacksbacken, Lägerhyddsvägen 2F, Uppsala, 13:15 (English)
Opponent
Supervisors
Projects
eSSENCE
Available from: 2010-08-30 Created: 2010-08-03 Last updated: 2011-02-17Bibliographically approved

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Sabesan, ManivasakanRisch, Tore

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