Prefetching-based metadata management in Advanced Multitenant Hadoop

Metadata management is an essential part in Apache Hadoop. Performing optimization of metadata accesses enhances big data storing, processing and analyzing, especially in multitenant environments. Nevertheless, as environmental complexity increases, metadata management is becoming more challenging a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of supercomputing 2019-02, Vol.75 (2), p.533-553
Hauptverfasser: Nguyen, Minh Chau, Won, Heesun, Son, Siwoon, Gil, Myeong-Seon, Moon, Yang-Sae
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Metadata management is an essential part in Apache Hadoop. Performing optimization of metadata accesses enhances big data storing, processing and analyzing, especially in multitenant environments. Nevertheless, as environmental complexity increases, metadata management is becoming more challenging and costly because of the heavy performance issues. In this paper, we propose a novel approach to improve the performance of metadata management for Hadoop in the multitenant environment based on the prefetching mechanism. We create metadata access graphs based on historical access values, define access patterns and then perform prefetching potential items for the near-future requests to minimize the latency. We present a formal algorithm to apply the prefetching mechanism into the Hadoop system and perform the actual implementation on a recent Hadoop system. Experimental results show that the proposed approach can enable the high performance for metadata management as well as maintain advanced multitenancy features.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-017-2019-5