TAMEX: A task-based query execution framework for mixed enterprise workloads on in-memory databases
| dc.contributor.author | Wust, Johannes | |
| dc.contributor.author | Grund, Martin | |
| dc.contributor.author | Plattner, Hasso | |
| dc.contributor.editor | Horbach, Matthias | |
| dc.date.accessioned | 2019-03-07T09:33:14Z | |
| dc.date.available | 2019-03-07T09:33:14Z | |
| dc.date.issued | 2013 | |
| dc.description.abstract | In-memory database management systems (DBMS) have been proposed to run transactional and analytical applications on a single database instance and to reduce the execution time of complex analytical queries to seconds. The two main reasons for this dramatic performance increase are massive intra-query parallelism on many-core CPUs and primary data storage in main memory. The benefits of these in-memory DBMS for enterprises are huge: analytical applications become largely independent of data staging delays, opening the way for real-time analytics. However, this promising approach will only be adopted, if DBMS can execute dynamically arriving transactional queries in a timely manner, even while complex analytical queries are executed. We believe that two system properties are key to achieve this objective: (1) splitting queries into fine granular atomic tasks and (2) efficiently assigning these tasks to a large number of processing units, thereby considering priorities of query classes. In this paper, we propose TAMEX, a framework for the execution of multiple query classes, designed for executing queries of heterogeneous workloads of enterprise applications on in-memory databases. The basic idea is to generate a task graph for each query during query compilation and assign these tasks to processing units by a user-level scheduler based on priorities. We evaluate the concept using a mix of transactional and join-heavy queries and focus on the impact of task sizes on load balancing and responsiveness of the system. | en |
| dc.identifier.isbn | 978-3-88579-614-5 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/20773 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | INFORMATIK 2013 – Informatik angepasst an Mensch, Organisation und Umwelt | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-220 | |
| dc.title | TAMEX: A task-based query execution framework for mixed enterprise workloads on in-memory databases | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 501 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 487 | |
| gi.conference.date | 16.-20. September 2013 | |
| gi.conference.location | Koblenz | |
| gi.conference.sessiontitle | Regular Research Papers |
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