BibTeX
CSL-JSON
MLA
Harvard
Technical Perspective DIAMetrics
Benchmarking Query Engines at Scale
release_2po7xbkqkbgcnc5jpledjgoqci
by
Peter Boncz
Abstract
Benchmarking database systems has a long and successful history in making industrial database systems comparable, and is also a cornerstone of quantifiable experimental data systems research. Creating good benchmarks has been described as something of an art [3]. One can inspire dataset and workload design from"representative" use cases queries, typically informed by domain experts; but also exploit technical insights from database architects in what features, operations, and data distributions should come together in order to invoke a particularly challenging task1.
In application/xml+jats
format
Archived Files and Locations
application/pdf 271.0 kB
file_6weyfpkssrfirhemzzplujkcgy
|
ir.cwi.nl (web) web.archive.org (webarchive) |
Read Archived PDF
Preserved and Accessible
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
access all versions, variants, and formats of this works (eg, pre-prints)
Cite This
Lookup Links
oaDOI/unpaywall (OA fulltext)
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar