Scipediacontent: Scipediacontent moved page Draft Content 970125444 to Neumann et al 2016a

2021-02-03T18:43:14Z

Scipediacontent moved page Draft Content 970125444 to Neumann et al 2016a

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2021-02-03T18:43:11Z

Created page with " == Abstract == htmlabstractThis work aims at reducing the main-memory footprint in high performance hybrid OLTP & OLAP databases, while retaining high query performance and..."

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== Abstract ==

htmlabstractThis work aims at reducing the main-memory footprint in high performance hybrid OLTP & OLAP databases, while retaining high query performance and transactional throughput. For this purpose, an innovative compressed columnar storage format for cold data, called Data Blocks is introduced. Data Blocks further incorporate a new light-weight index structure called Positional SMA that narrows scan ranges within Data Blocks even if the entire block cannot be ruled out. To achieve highest OLTP performance, the compression schemes of Data Blocks are very light-weight, such that OLTP transactions can still quickly access individual tuples. This sets our storage scheme apart from those used in specialized analytical databases where data must usually be bit-unpacked. Up to now, high-performance analytical systems use either vectorized query execution or “just-in-time” (JIT) query compilation. The fine-grained adaptivity of Data Blocks necessitates the integration of the best features of each approach by an interpreted vectorized scan subsystem feeding into JIT-compiled query pipelines. Experimental evaluation of HyPer, our full-fledged hybrid OLTP & OLAP database system, shows that Data Blocks accelerate performance on a variety of query workloads while retaining high transaction throughput.

== Original document ==

The different versions of the original document can be found in:

* [https://ir.cwi.nl/pub/24382 https://ir.cwi.nl/pub/24382]

* [https://ir.cwi.nl/pub/24382/24382.pdf https://ir.cwi.nl/pub/24382/24382.pdf]

* [https://research.vu.nl/en/publications/820af4d9-00b5-4d74-bd8f-9f6287d4cd14 https://research.vu.nl/en/publications/820af4d9-00b5-4d74-bd8f-9f6287d4cd14]

* [http://www.scopus.com/inward/record.url?scp=84979680799&partnerID=8YFLogxK http://www.scopus.com/inward/record.url?scp=84979680799&partnerID=8YFLogxK],
: [http://dx.doi.org/10.1145/2882903.2882925 http://dx.doi.org/10.1145/2882903.2882925]

* [https://dblp.uni-trier.de/db/conf/sigmod/sigmod2016.html#LangMFB0K16 https://dblp.uni-trier.de/db/conf/sigmod/sigmod2016.html#LangMFB0K16],
: [https://research.vu.nl/en/publications/data-blocks-hybrid-oltp-and-olap-on-compressed-storage-using-both https://research.vu.nl/en/publications/data-blocks-hybrid-oltp-and-olap-on-compressed-storage-using-both],
: [https://dl.acm.org/citation.cfm?id=2882925 https://dl.acm.org/citation.cfm?id=2882925],
: [https://www.narcis.nl/publication/RecordID/oai%3Acwi.nl%3A24382 https://www.narcis.nl/publication/RecordID/oai%3Acwi.nl%3A24382],
: [https://doi.org/10.1145/2882903.2882925 https://doi.org/10.1145/2882903.2882925],
: [https://dl.acm.org/citation.cfm?doid=2882903.2882925 https://dl.acm.org/citation.cfm?doid=2882903.2882925],
: [http://oai.cwi.nl/oai/asset/24382/24382B.pdf http://oai.cwi.nl/oai/asset/24382/24382B.pdf],
: [https://academic.microsoft.com/#/detail/2439390339 https://academic.microsoft.com/#/detail/2439390339]

* [https://ir.cwi.nl/pub/24382 https://ir.cwi.nl/pub/24382],
: [http://dx.doi.org/10.1145/2882903.2882925 http://dx.doi.org/10.1145/2882903.2882925]

* [http://dl.acm.org/ft_gateway.cfm?id=2882925&ftid=1744214&dwn=1 http://dl.acm.org/ft_gateway.cfm?id=2882925&ftid=1744214&dwn=1],
: [http://dx.doi.org/10.1145/2882903.2882925 http://dx.doi.org/10.1145/2882903.2882925] under the license http://www.acm.org/publications/policies/copyright_policy#Background

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Neumann et al 2016a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 970125444 to Neumann et al 2016a

Scipediacontent: Created page with " == Abstract == htmlabstractThis work aims at reducing the main-memory footprint in high performance hybrid OLTP & OLAP databases, while retaining high query performance and..."