A general fragments allocation method for join query in distributed database

Gao, Jintao; Liu, Wenjie; Li, Zhanhuai; Zhang, Jian; Shen, Li

doi:10.1016/j.ins.2019.10.043

Cited by 9 publications

(3 citation statements)

References 13 publications

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“…Besides, Gao et al 28 proposed a common tactic for optimal allotment of segments to enhance the join queries (AlCo * ). The AlCo uses a standard algorithm depending on a GA in PostgreSQL to search the optimal allotment schematization for segments and spot the optimal layout infinite stages.…”

Section: Related Workmentioning

confidence: 99%

A cloud database route scheduling method using a hybrid optimization algorithm

Baghi

Navimipour

2023

Int J Communication

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Cloud computing has appeared as a technology allowing a company to employ computing resources such as applications, software, and hardware to calculate over the Internet. Scholars have paid great attention to cloud computing because of its cutting-edge availability, cost decrement, and boundless applications. A cloud database is a data storage site on the web where the optimal path is spotted to access the needed database. So, placing the ideal path to a database is crucial. The cloud database defined the scheduling problem to choose the perfect route. Cloud database path scheduling is a multifaceted procedure consisting of congestion control, routing list, and network flow distribution. It has a postponement in searching for the needed source route from the cloud database. Offering numerous infinite resources with the growing database workload is an NP-Hard optimization problem where the query request needs optimal schedules to respond to the required services. So, we have used a hybrid cuckoo search (CS) and genetic algorithm (GA), motivated by a social bird's phenomenon, to solve this problem. Integrating genetic operators has dramatically enhanced the balance between the capability of searching and utilization.

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Section: Related Workmentioning

confidence: 99%

A cloud database route scheduling method using a hybrid optimization algorithm

Baghi

Navimipour

2023

Int J Communication

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“…Jintao Gao et al [21] developed a partitioning methodology for scheduling the query in the distributed dataset. Here, the introduced methodology considered the TPC-H dataset for partitioning the data.…”

Section: Related Workmentioning

confidence: 99%

A Novel HVgP and OLBP approach in Distributed Transaction Partitioning

Bharati

Attar

2022

Preprint

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Data partitioning acts an important role in Online Transaction Processing (OLTP) to enhance their performance and scalability. Partitioning is important in OLTP based systems due to the increase of user populations and online transactions. Nowadays, providing scalable and reliable data organization is the main aim of database researchers. This work presented an innovative data partitioning approach and optimized load balancing for scalable transactions. Initially, the Hybrid Vertical-graph partitioning (HVgP) approach is utilized for appropriate data partitioning. After the process of data partitioning, the partitions efficiency and the average workload parameters are computed and their corresponding weight factor is computed. Subsequently, Optimized Improved Load Balancing (OLBP) algorithm is utilized for scalable OLTP data transactions on distributed database. Here, the estimated weight factor is updated for effective load balancing with data partitions. The presented approach is appropriate for various online data transaction applications. The quality of the presented approach is examined using TPC-E OLTP benchmark dataset. The performance of the improved approach is examined with the different existing approaches and proved the significant enhancement in different performance metrics like Throughput, Response time, distributed transactions, and CPU utilization.

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“…Compared with the traditional centralized database, the distributed database mainly has the following advantages [10]. On the one hand, the distributed database has a strong expansion ability, and advantages in data storage [11]. On the other hand, it can e ectively save costs [12].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Query Method Based on Distributed Database Demand Information

Luo

2022

Mathematical Problems in Engineering

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This paper proposes a real-time query method for distributed database requirement information. First, we propose to extract the database information according to the submitted query keyword. Then, we establish a real-time model of distributed database demand information query and a real-time information classification model, using a distributed multivariate hash algorithm model and a query of real-time information. When there is a query keyword, the proposed method directly reads the data above the hash ring based on the keyword to improve query efficiency. Extensive experimental results indicate that our proposed method reduces the number of queries, query pressure, and processing time of information queries in the distributed database. Moreover, the distributed database’s real-time processing rate and amount have increased.

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A general fragments allocation method for join query in distributed database

Cited by 9 publications

References 13 publications

A cloud database route scheduling method using a hybrid optimization algorithm

A cloud database route scheduling method using a hybrid optimization algorithm

A Novel HVgP and OLBP approach in Distributed Transaction Partitioning

Real-Time Query Method Based on Distributed Database Demand Information

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