A Comprehensive Study of HBase Storage Architecture—A Systematic Literature Review

Hassan, Muhammad Umair; Yaqoob, Irfan; Zulfiqar, Sidra; Hameed, Ibrahim A.

doi:10.3390/sym13010109

Cited by 14 publications

(5 citation statements)

References 39 publications

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“…The insert operation was applied to the Kudu table using the Apply method of the KuduSession object, ensuring consistent execution. [16] Errors or exceptions were handled gracefully using the status() method of the KuduSession object. These steps allowed for effective interaction with Kudu tables using the C++ library.…”

Section: ) Kudu Write Operationmentioning

confidence: 99%

IDify - Distributed Database System for Digital Identification

Wickramasinghe,

Ranaweera,

Pathirage

et al. 2024

CONTRE

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”IDify” Distributed database system for digital identification is a big data handling system to centralize the important services provided by the government to make the facilities efficient and reliable. It has integrated services such as digital authentication, E-Banking, Personal Information Management, and Government Surveys to provide users with a centralized and digitized platform to make their lives easier. In this system there is a distributed database platform to carry out all the data storing and data processing tasks to facilitate a large user count and to avoid the drawbacks of monolithic systems. The database system has been designed by integrating several modern database technologies to make the system efficient and coherent as the facilities provided by the system are extremely mission-critical. To make the system low latent on data ingestion and data reading tasks a special library is also implemented in collaboration with modern query processing engines. It is proposed to utilize the thread system of a processor to implement parallelism to enhance the performance of data read/write tasks. Apart from that a fault-tolerant framework has been implemented to free the system from any erroneous scenario taking place.

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Section: ) Kudu Write Operationmentioning

confidence: 99%

IDify - Distributed Database System for Digital Identification

Wickramasinghe,

Ranaweera,

Pathirage

et al. 2024

CONTRE

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“…Hadoop Distributed File System (HDFS) can store and read massive amounts of data in a distributed manner and provide high-throughput data access. Therefore, Hadoop is well suited for building a mass data storage platform [21,22].…”

Section: Hbase Databasementioning

confidence: 99%

An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval

et al. 2023

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In medical services, the amount of data generated by medical devices is increasing explosively, and access to medical data is also put forward with higher requirements. Although HBase-based medical data storage solutions exist, they cannot meet the needs of fast locating and diversified access to medical data. In order to improve the retrieval speed, the recognition model S-TCR and the dynamic management algorithm SL-TCR, based on the behavior characteristics of access, were proposed to identify the frequently accessed hot data and dynamically manage the data storage medium as to maximize the system access performance. In order to improve the search performance of keys, an optimized secondary index strategy was proposed to reduce I/O overhead and optimize the search performance of non-primary key indexes. Comparative experiments were conducted on real medical data sets. The experimental results show that the optimized retrieval model can meet the needs of hot data access and diversified medical data retrieval.

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“…It can support real-time data reading and can be used to develop distributed storage systems. Using HBase technology, a large-scale structured storage cluster can be built on a PC server [13].…”

Section: Distributed Hadoop Database (Hbase)mentioning

confidence: 99%

Smart Management Platform for Landfilling of Waste after Mechanical Biological Treatment

Wang

Zhang

Wang

et al. 2022

Advances in Civil Engineering

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With the rapid development of the economy and society, the production of municipal solid waste is continuously increasing worldwide. Therefore, harmless treatments and the disposal of municipal solid waste should be improved. This study combined the concept of Internet of things and smart environment protection with a “cloud, network, end” platform architecture to construct a smart management platform for the planning and management of landfills. The platform was developed for the mechanical biological treatment (MBT) of landfills and was divided into seven modules, landfill design, municipal solid waste production prediction, MBT waste microbial volume reduction, stability analysis, result analysis, remote monitoring, and sharing and communication, which can effectively improve the operation and management of waste, enhance the effective storage volume of a landfill, extend its service life, and thereby improve the sustainable development of the city. This study can be used as a reference for applications in similar projects worldwide.

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A Comprehensive Study of HBase Storage Architecture—A Systematic Literature Review

Cited by 14 publications

References 39 publications

IDify - Distributed Database System for Digital Identification

IDify - Distributed Database System for Digital Identification

An HBase-Based Optimization Model for Distributed Medical Data Storage and Retrieval

Smart Management Platform for Landfilling of Waste after Mechanical Biological Treatment

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