On-the-Fly Data Transformation in Action
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Published:2023-08
Issue:12
Volume:16
Page:3950-3953
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ISSN:2150-8097
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Container-title:Proceedings of the VLDB Endowment
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language:en
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Short-container-title:Proc. VLDB Endow.
Author:
Mun Ju Hyoung1,
Karatsenidis Konstantinos1,
Papon Tarikul Islam1,
Roozkhosh Shahin1,
Hoornaert Denis2,
Drepper Ulrich3,
Sanaullah Ahmed3,
Mancuso Renato1,
Athanassoulis Manos1
Affiliation:
1. Boston University
2. Technical University of Munich
3. Red Hat
Abstract
Transactional and analytical database management systems (DBMS) typically employ different data layouts: row-stores for the first and column-stores for the latter. In order to bridge the requirements of the two without maintaining two systems and two (or more) copies of the data, our proposed system
Relational Memory
employs specialized hardware that transforms the base row table into arbitrary column groups at query execution time. This approach maximizes the cache locality and is easy to use via a simple abstraction that allows transparent on-the-fly data transformation. Here, we demonstrate how to deploy and use Relational Memory via four representative scenarios. The demonstration uses the full-stack implementation of Relational Memory on the Xilinx Zynq UltraScale+ MPSoC platform. Conference participants will interact with Relational Memory deployed in the actual platform.
Publisher
Association for Computing Machinery (ACM)
Subject
General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development
Reference7 articles.
1. H2O
2. Bridging the Archipelago between Row-Stores and Column-Stores for Hybrid Workloads
3. Fatma Özcan , Yuanyuan Tian , and Pinar Tözün . 2017 . Hybrid Transactional/Analytical Processing: A Survey . In Proceedings of the ACM SIGMOD International Conference on Management of Data. 1771--1775 . Fatma Özcan, Yuanyuan Tian, and Pinar Tözün. 2017. Hybrid Transactional/Analytical Processing: A Survey. In Proceedings of the ACM SIGMOD International Conference on Management of Data. 1771--1775.
4. Relational Fabric: Transparent Data Transformation