Parallel "GroupBy-Before-Join" Query Processing for High Performance Parallel/Distributed Database Systems

2006 ◽  
Author(s):  
D. Taniar ◽  
W. Rahayu
Keyword(s):  
Query Processing ◽  
High Performance ◽  
Database Systems ◽  
Distributed Database ◽  
Distributed Database Systems

scholarly journals Efficient query processing in distributed database systems

2015 ◽  
Author(s):  
Αλέξανδρος Πανάρετος
Keyword(s):  
Query Processing ◽  
Database Systems ◽  
Distributed Database ◽  
Distributed Database Systems ◽  
Range Tree ◽  
Efficient Query Processing

Στο πλαίσιο της παρούσας Διδακτορικής Διατριβής χρησιμοποιήθηκε εκτενώς η Κατανεμημένη Δομή ART (Autonomous Range Tree) η οποία αποτέλεσε την βάση για την υλοποίηση μίας σειράς αποδοτικών συστημάτων κατανεμημένης διαχείρισης δεδομένων σε ποικίλα πεδία εφαρμογών, όπως: εξομοιωτές μέτρησης της απόδοσης διαφορετικών αλγορίθμων κατανεμημένης δόμησης (P2P Infrastructures or overlays), διαχείριση ψηφιακών δικαιωμάτων σε υποδομές ανταλλαγής προστατευμένου ψηφιακού υλικού, διαχείριση δεδομένων που αναπαριστούν επίπεδα ενέργειας σε δίκτυα αισθητήρων και διαχείριση χώρο-χρονικών δεδομένων που αναπαριστούν τροχιές κινούμενων αντικειμένων στο επίπεδο.

Distributed Query Plan Generation using Ant Colony Optimization

2015 ◽  
Vol 6 (1) ◽  
pp. 1-22 ◽  
Author(s):  
T.V. Vijay Kumar ◽  
Rahul Singh ◽  
Amit Kumar
Keyword(s):  
Query Processing ◽  
Ant Colony Optimization ◽  
Database Systems ◽  
Distributed Database ◽  
Ant Colony ◽  
Distributed Query Processing ◽  
Query Plan ◽  
Plan Generation ◽  
Distributed Database Systems ◽  
Distributed Query

Query processing is a critical performance evaluation parameter and has received a considerable amount of attention especially in the context of distributed database systems. The aim of distributed query processing is to effectively and efficiently process the query. This entails laying down an optimal distributed query processing strategy that generates efficient query plans Since in distributed database systems, the data is distributed and replicated at multiple sites, the number of query plans increases exponentially with increase in the number of relations accessed by the query along with increase in the number of sites containing these relations. Thus, from amongst these query plans, there is a need to generate optimal query plans involving lesser number of sites which, in turn, would entail lower site-to-site communication cost leading to faster query response times. In this paper, an attempt has been made to generate such query plans for a distributed query using Ant Colony Optimization (ACO). This ACO based distributed query plan generation (DQPG) algorithm, when compared with the GA based DQPG algorithm, is able to generate comparatively better quality Top-K query plans for a given distributed query.

Performance Evaluation of Distributed Database Systems

2014 ◽  
Vol 13 (9) ◽  
pp. 4859-4867
Author(s):  
Khaled Saleh Maabreh
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Operation Mode ◽  
Database Systems ◽  
Distributed Database ◽  
Evaluation Study ◽  
Distributed Database Systems ◽  
Different Types ◽  
Distributed Database System ◽  
Distributed Database Management

Distributed database management systems manage a huge amount of data as well as large and increasingly growing number of users through different types of queries. Therefore, efficient methods for accessing these data volumes will be required to provide a high and an acceptable level of system performance.  Data in these systems are varying in terms of types from texts to images, audios and videos that must be available through an optimized level of replication. Distributed database systems have many parameters like data distribution degree, operation mode and the number of sites and replication. These parameters have played a major role in any performance evaluation study. This paper investigates the main parameters that may affect the system performance, which may help with configuring the distributed database system for enhancing the overall system performance.

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