Show simple item record

dc.contributor.author
Hentschel, Martin
dc.contributor.author
Kossmann, Donald
dc.contributor.author
Florescu, Daniela
dc.contributor.author
Haas, Laura
dc.contributor.author
Kraska, Tim
dc.contributor.author
Miller, Renée J.
dc.date.accessioned
2017-11-30T14:00:50Z
dc.date.available
2017-06-10T19:33:30Z
dc.date.available
2017-11-30T14:00:50Z
dc.date.issued
2009
dc.identifier.uri
http://hdl.handle.net/20.500.11850/69832
dc.identifier.doi
10.3929/ethz-a-006835897
dc.description.abstract
The goal of a data integration system is to allow users to query diverse information sources through a schema that is familiar to them. However, there may be many different users who may have dif- ferent preferred schemas, and the data may be stored in data sources which use still other schemas. To integrate data, mapping rules must be defined to map entities of the data sources to entities of the users’ schemas. In large information systems with many data sources which serve sophisticated applications, there can be many such mapping rules and they can be complex. The purpose of this paper is to study the per- formance of alternative query processing techniques for data integration systems with many complex mapping rules. A new approach, mapping data to queries (MDQ), is presented. Through extensive performance experiments, it is shown that this approach performs well for complex mapping rules and queries, and scales significantly better with the num- ber of rules than the state of the art, which is based on query rewrite. In fact, the performance is close to that of an ideal system in which there is only a single schema used by all sources and queries.
en_US
dc.format
application/pdf
dc.language.iso
en
en_US
dc.publisher
Swiss Federal Institute of Technology
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
INFORMATION STORAGE + INFORMATION RETRIEVAL (INFORMATION SYSTEMS)
en_US
dc.subject
INFORMATIONSSPEICHERUNG + INFORMATIONSGEWINNUNG (INFORMATIONSSYSTEME)
en_US
dc.subject
SPECIAL PROGRAMMING METHODS
en_US
dc.subject
ABFRAGEN (INFORMATIONSSYSTEME)
en_US
dc.subject
SPEZIELLE PROGRAMMIERMETHODEN
en_US
dc.subject
QUERIES (INFORMATION SYSTEMS)
en_US
dc.title
Scalable Data Integration by Mapping Data to Queries
en_US
dc.type
Report
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2011
ethz.journal.title
Technical report / [ETH, Department of Computer Science
ethz.journal.volume
633
en_US
ethz.size
Online-Datei
en_US
ethz.code.ddc
DDC - DDC::0 - Computer science, information & general works::004 - Data processing, computer science
en_US
ethz.identifier.nebis
006835897
ethz.publication.place
Zürich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science
en_US
ethz.date.deposited
2017-06-10T19:34:36Z
ethz.source
ECOL
ethz.source
ECIT
ethz.identifier.importid
imp59366b19bb04397392
ethz.identifier.importid
imp593650d4af9fc24653
ethz.ecolpid
eth:5030
ethz.ecitpid
pub:110588
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-12T14:42:30Z
ethz.rosetta.lastUpdated
2020-02-15T09:58:37Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Scalable%20Data%20Integration%20by%20Mapping%20Data%20to%20Queries&rft.jtitle=Technical%20report%20/%20%5BETH,%20Department%20of%20Computer%20Science&rft.date=2009&rft.volume=633&rft.au=Hentschel,%20Martin&Kossmann,%20Donald&Florescu,%20Daniela&Haas,%20Laura&Kraska,%20Tim&rft.genre=report&
 Search print copy at ETH Library

Files in this item

Thumbnail

Publication type

Show simple item record