Hybrid In-Memory and On-Disk Tables for Speeding-Up Table Accesses
Identifieur interne : 000573 ( Istex/Corpus ); précédent : 000572; suivant : 000574Hybrid In-Memory and On-Disk Tables for Speeding-Up Table Accesses
Auteurs : Joan Guisado-Gámez ; Antoni Wolski ; Calisto Zuzarte ; Josep-Lluís Larriba-Pey ; Victor Muntés-MuleroSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2010.
Abstract
Abstract: Main memory database management systems have become essential for response-time-bounded applications, such as those in telecommunications systems or Internet, where users frequently access a table in order to get information or check whether an element exists, and require the response to be as fast as possible. Continuous data growth is making it unaffordable to keep entire relations in memory and some commercial applications provide two different engines to handle data in-memory and on-disk separately. However, these systems assign each table to one of these engines, forcing large relations to be kept on secondary storage. In this paper we present TwinS — a hybrid database management system that allows managing hybrid tables, i.e. tables partially managed by both engines. We show that we can reduce response time when accessing a large table in the database. All our experiments have been run on a dual-engine DBMS: IBM®SolidDB®.
Url:
DOI: 10.1007/978-3-642-15364-8_17
Links to Exploration step
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<front><div type="abstract" xml:lang="en">Abstract: Main memory database management systems have become essential for response-time-bounded applications, such as those in telecommunications systems or Internet, where users frequently access a table in order to get information or check whether an element exists, and require the response to be as fast as possible. Continuous data growth is making it unaffordable to keep entire relations in memory and some commercial applications provide two different engines to handle data in-memory and on-disk separately. However, these systems assign each table to one of these engines, forcing large relations to be kept on secondary storage. In this paper we present TwinS — a hybrid database management system that allows managing hybrid tables, i.e. tables partially managed by both engines. We show that we can reduce response time when accessing a large table in the database. All our experiments have been run on a dual-engine DBMS: IBM®SolidDB®.</div>
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<Para>Main memory database management systems have become essential for response-time-bounded applications, such as those in telecommunications systems or Internet, where users frequently access a table in order to get information or check whether an element exists, and require the response to be as fast as possible. Continuous data growth is making it unaffordable to keep entire relations in memory and some commercial applications provide two different engines to handle data in-memory and on-disk separately. However, these systems assign each table to one of these engines, forcing large relations to be kept on secondary storage.</Para>
<Para>In this paper we present TwinS — a hybrid database management system that allows managing hybrid tables, i.e. tables partially managed by both engines. We show that we can reduce response time when accessing a large table in the database. All our experiments have been run on a dual-engine DBMS: IBM<Superscript>®</Superscript>
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<abstract lang="en">Abstract: Main memory database management systems have become essential for response-time-bounded applications, such as those in telecommunications systems or Internet, where users frequently access a table in order to get information or check whether an element exists, and require the response to be as fast as possible. Continuous data growth is making it unaffordable to keep entire relations in memory and some commercial applications provide two different engines to handle data in-memory and on-disk separately. However, these systems assign each table to one of these engines, forcing large relations to be kept on secondary storage. In this paper we present TwinS — a hybrid database management system that allows managing hybrid tables, i.e. tables partially managed by both engines. We show that we can reduce response time when accessing a large table in the database. All our experiments have been run on a dual-engine DBMS: IBM®SolidDB®.</abstract>
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