Massively parallel numa-aware hash joins

Harald Lang, Viktor Leis, Martina Cezara Albutiu, Thomas Neumann, Alfons Kemper

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

15 Zitate (Scopus)

Abstract

Driven by the two main hardware trends increasing main memory and massively parallel multi-core processing in the past few years, there has been much research effort in parallelizing well-known join algorithms. However, the non-uniform memory access (NUMA) of these architectures to main memory has only gained limited attention in the design of these algorithms. We study recent proposals of main memory hash join implementations and identify their major performance problems on NUMA architectures. We then develop a NUMA-aware hash join for massively parallel environments, and show how the specific implementation details affect the performance on a NUMA system. Our experimental evaluation shows that a carefully engineered hash join implementation outperforms previous high performance hash joins by a factor of more than two, resulting in an unprecedented throughput of 3/4 billion join argument quintuples per second.

OriginalspracheEnglisch
TitelIn Memory Data Management and Analysis - 1st and 2nd International Workshops, IMDM 2013, IMDM 2014, Revised Selected Papers
Redakteure/-innenThomas Neumann, Andrew Pavlo, Justin Levandoski, Arun Jagatheesan
Herausgeber (Verlag)Springer Verlag
Seiten3-14
Seitenumfang12
ISBN (elektronisch)9783319139593
DOIs
PublikationsstatusVeröffentlicht - 2015
Veranstaltung1st International Workshop on In-Memory Data Management and Analytics, IMDM 2013 and 2nd International Workshop on In-Memory Data Management and Analytics, IMDM 2014 - Hongzhou, China
Dauer: 1 Sept. 20141 Sept. 2014

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band8921
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

Konferenz1st International Workshop on In-Memory Data Management and Analytics, IMDM 2013 and 2nd International Workshop on In-Memory Data Management and Analytics, IMDM 2014
Land/GebietChina
OrtHongzhou
Zeitraum1/09/141/09/14

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