A Query Beehive Algorithm for Data Warehouse Buffer Management and Query Scheduling

Kerkad, Amira; Bellatreche, Ladjel; Richard, Pascal; Ordóñez, Carlos; Geniet, Dominique

doi:10.4018/ijdwm.2014070103

Cited by 5 publications

(5 citation statements)

References 24 publications

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“…In addition, do not use other optimization structures. Karkad et al [8] applied the buffer management and scheduling technique to three optimization structures (index, materialized views, and fragmentation). This approach requires caching, planning, and is not dynamic.…”

Section: Optimization Techniquesmentioning

confidence: 99%

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Queries Processing in Wireless Sensor Network

Abbassi¹,

Ezzedine²

2021

Wireless Sensor Networks - Design, Deployment and Applications

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For the super-excellence applications used to control the water level in rivers, temperature handles a very large volume of information and does not stop constantly changing. These spatio-temporal data collected by a network of sensors form a set of thematic, integrated, non-volatile and historical data organized to help decision-making. Usually this process is performed with temporal, spatial and spatiotemporal queries. This in turn increases the execution time of the query load. In the literatures, several techniques have been identified such as materialized views (MV), indexes, fragmentation, scheduling, and buffer management. These techniques do not consider the update of the request load and the modification at the database level. In this chapter, we propose an optimal dynamic selection solution based on indexes and VMs. the solution is optimal when it meets the entire workload with a reasonable response time. The proposed approach supports modification at the database level and at the workload level to ensure the validity of the optimal solution for this the knapsack algorithm was used.

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Section: Optimization Techniquesmentioning

confidence: 99%

“…In Dynamat [8] the authors have removed the least used VMs to free space for new creations. In this approach the authors limit themselves to use only the MV optimization structure.…”

Section: End If 9 End For Endmentioning

confidence: 99%

Queries Processing in Wireless Sensor Network

Abbassi¹,

Ezzedine²

2021

Wireless Sensor Networks - Design, Deployment and Applications

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“…Hill & Ross (2009) suggested transforming outer joins into inner joins to improve performance and response time. Carey et al (1989) and Kerkad et al (2014) investigated the problem of priority scheduling in a database management system to shift resources to more critical queries than load jobs. Beszedes et al (2003) presented the technique of program-code compression to have a positive impact on network traffic and embedded system costs such as memory requirements and power consumption.…”

Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

“…Most data warehouse systems have priority scheduling (Kerkad et al, 2014) techniques to grant maximum resources to analytical tools and queries, but this can only operate within system resource constraints. A second typical technique to schedule non-critical applications or lower-priority jobs to times when the system running lower in resource utilization.…”

Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

SQL Scorecard for Improved Stability and Performance of Data Warehouses

Rahman

2016

International Journal of Software Innovation

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Scorecard-based measurement techniques are used by organizations to measure the performance of their business operations. A scorecard approach could be applied to a database system to measure performance of SQL (Structured Query Language) being executed and the extent of resources being used by SQL. In a large data warehouse, thousands of jobs run daily via batch cycles to refresh different subject areas. Simultaneously, thousands of queries by business intelligence tools and ad-hoc queries are being executed twenty-four by seven. There needs to be a controlling mechanism to make sure these batch jobs and queries are efficient and do not consume database systems resources more than optimal. The authors propose measurement of SQL query performance via a scorecard tool. The motivation behind using a scorecard tool is to make sure that the resource consumption of SQL queries is predictable and the database system environment is stable. The experimental results show that queries that pass scorecard evaluation criteria tend to utilize optimal level of database systems computing resources. These queries also show improved parallel efficiency (PE) in using computing resources (CPU, I/O and spool space) that demonstrate the usefulness of SQL scorecard.

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“…Starting from the candidate attributes in the encoding schema, a partitioning schema needs to be generated while reducing workload cost. EQA is inspired from our algorithm "Queen-bee" proposed in (Kerkad et al 2014) proposed in the context of simultaneous resolution of query scheduling and buffer management. The Queen-bee algorithm looks over join nodes in the MVPP in order to divide the search space by making subsets of correlated queries and optimize locally each group by electing important queries to propagate benefit.…”

Section: Figure 5 Incremental Encoding By Horizontal and Vertical Spl...mentioning

confidence: 99%

Query Interaction Based Approach for Horizontal Data Partitioning

Bellatreche

Kerkad

2015

International Journal of Data Warehousing and Mining

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With the explosion of data, several applications are designed around analytical aspects, with data warehousing technology at the heart of the construction chain. The exploitation of this data warehouse is usually performed by the use of complex queries involving selections, joins and aggregations. These queries bring the following characteristics: (1) their routinely aspects, (2) their large number, and (3) the high operation sharing between queries. This interaction has been largely identified in the context of multi-query optimization, where graph data structures were proposed to capture it. Also during the physical design, the structures have been used to select redundant optimization structures such as materialized views and indexes. Horizontal data partitioning (HDP) is another non-redundant optimization structure that can be selected in the physical design phase. It is a pre-condition for designing extremely large databases in several environments: centralized, distributed, parallel and cloud. It aims to reduce the cost of the above operations. In HDP, the optimization space of potential candidates for partitioning grows exponentially with the problem size making the problem NP-hard. This paper proposes a new approach based on query interactions to select a partitioning schema of a data warehouse in a divide and conquer manner to achieve an improved trade-off between the optimization algorithm's speed and the quality of the solution. The effectiveness of our approach is proven through a validation using the Star Schema Benchmark (100 GB) on Oracle11g.

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A Query Beehive Algorithm for Data Warehouse Buffer Management and Query Scheduling

Cited by 5 publications

References 24 publications

Queries Processing in Wireless Sensor Network

Queries Processing in Wireless Sensor Network

SQL Scorecard for Improved Stability and Performance of Data Warehouses

Query Interaction Based Approach for Horizontal Data Partitioning

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