MorphStore: Analytical Query Engine with a Holistic Compression-Enabled Processing Model
April 20, 2020 Β· Declared Dead Β· π Proceedings of the VLDB Endowment
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Authors
Patrick Damme, Annett UngethΓΌm, Johannes Pietrzyk, Alexander Krause, Dirk Habich, Wolfgang Lehner
arXiv ID
2004.09350
Category
cs.DB: Databases
Citations
13
Venue
Proceedings of the VLDB Endowment
Last Checked
5 months ago
Abstract
In this paper, we present MorphStore, an open-source in-memory columnar analytical query engine with a novel holistic compression-enabled processing model. Basically, compression using lightweight integer compression algorithms already plays an important role in existing in-memory column-store database systems, but mainly for base data. In particular, during query processing, these systems only keep the data compressed until an operator cannot process the compressed data directly, whereupon the data is decompressed, but not recompressed. Thus, the full potential of compression during query processing is not exploited. To overcome that, we developed a novel compression-enabled processing model as presented in this paper. As we are going to show, the continuous usage of compression for all base data and all intermediates is very beneficial to reduce the overall memory footprint as well as to improve the query performance.
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