MorphStore - In-Memory Query Processing based on Morphing Compressed Intermediates LIVE
Author(s) -
Dirk Habich,
Patrick Damme,
Annett Ungethüm,
Johannes Pietrzyk,
Alexander Krause,
Juliana Hildebrandt,
Wolfgang Lehner
Publication year - 2019
Publication title -
proceedings of the 2022 international conference on management of data
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-5643-5
DOI - 10.1145/3299869.3320234
Subject(s) - computer science , morphing , compression (physics) , data compression , column (typography) , query optimization , in memory processing , parallel computing , database , algorithm , information retrieval , web search query , query by example , search engine , artificial intelligence , materials science , frame (networking) , telecommunications , composite material
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 column stores, but mainly for base data. The continuous handling of compression from the base data to the intermediate results during query processing has already been discussed, but not investigated in detail since the computational effort for compression as well as decompression is often assumed to exceed the benefits of a reduced transfer cost between CPU and main memory. However, this argument increasingly loses its validity as we are going to show in our demo. Generally, our novel compression-aware query processing concept is characterized by the fact that we are able to speed up the query execution by morphing compressed intermediate results from one scheme to another scheme to dynamically adapt to the changing data characteristics during query processing. Our morphing decisions are made using a cost-based approach.
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