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pro vyhledávání: '"Damme, Patrick"'
Hybrid memory systems consisting of DRAM and NVRAM offer a great opportunity for column-oriented data systems to persistently store and to efficiently process columnar data completely in main memory. While vectorization (SIMD) of query operators is s
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https://tud.qucosa.de/id/qucosa%3A76671
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https://tud.qucosa.de/api/qucosa%3A76671/attachment/ATT-0/
Autor:
Habich, Dirk, Damme, Patrick, Ungethüm, Annett, Pietrzyk, Johannes, Krause, Alexander, Hildebrandt, Juliana, Lehner, Wolfgang
In this demo, we present MorphStore, an in-memory column store with a novel compression-aware query processing concept. Basically, compression using lightweight integer compression algorithms already plays an important role in existing in-memory colu
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80634
https://tud.qucosa.de/api/qucosa%3A80634/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80634/attachment/ATT-0/
Autor:
Zarubin, Mikhail, Damme, Patrick, Kissinger, Thomas, Habich, Dirk, Lehner, Wolfgang, Willhalm, Thomas
Lightweight integer compression algorithms play an important role in in-memory database systems to tackle the growing gap between processor speed and main memory bandwidth. Thus, there is a large number of algorithms to choose from, while different a
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80547
https://tud.qucosa.de/api/qucosa%3A80547/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80547/attachment/ATT-0/
Data as well as hardware characteristics are two key aspects for efficient data management. This holds in particular for the field of in-memory data processing. Aside from increasing main memory capacities, efficient in-memory processing benefits fro
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82179
https://tud.qucosa.de/api/qucosa%3A82179/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82179/attachment/ATT-0/
The exploitation of data as well as hardware properties is a core aspect for efficient data management. This holds in particular for the field of in-memory data processing. Aside from increasing main memory capacities, in-memory data processing also
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80629
https://tud.qucosa.de/api/qucosa%3A80629/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80629/attachment/ATT-0/
In-memory column-store database systems are state of the art for the efficient processing of analytical workloads. In these systems, data compression as well as vectorization play an important role. Currently, the vectorized processing is done using
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A86044
https://tud.qucosa.de/api/qucosa%3A86044/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A86044/attachment/ATT-0/
Lightweight integer compression algorithms are frequently applied in in-memory database systems to tackle the growing gap between processor speed and main memory bandwidth. In recent years, the vectorization of basic techniques such as delta coding a
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A81377
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https://tud.qucosa.de/api/qucosa%3A81377/attachment/ATT-0/
In-memory database systems have to keep base data as well as intermediate results generated during query processing in main memory. In addition, the effort to access intermediate results is equivalent to the effort to access the base data. Therefore,
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83655
https://tud.qucosa.de/api/qucosa%3A83655/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A83655/attachment/ATT-0/
Autor:
Ungethüm, Annett, Damme, Patrick, Pietrzyk, Johannes, Krause, Alexander, Habich, Dirk, Lehner, Wolfgang
Energy consumption becomes more and more a critical design factor, whereby performance is still an important requirement. Thus, a balance between performance and energy has to be established. To tackle that issue for database systems, we proposed the
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83912
https://tud.qucosa.de/api/qucosa%3A83912/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A83912/attachment/ATT-0/
Lightweight data compression techniques like dictionary or run-length compression play an important role in main memory database systems. Having decided for a compression scheme for a dataset, the transformation to another scheme is very inefficient
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83653
https://tud.qucosa.de/api/qucosa%3A83653/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A83653/attachment/ATT-0/