Research and Application of Query Optimization Based on HBase

Lei, Kai; Xiong, Xiaoyu; Wang, Zengzhou; Shi, Fangzhou; He, Jian

doi:10.1109/iccc54389.2021.9674637

2021 7th International Conference on Computer and Communications (ICCC) 2021

DOI: 10.1109/iccc54389.2021.9674637

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Research and Application of Query Optimization Based on HBase

Kai Lei

Xiaoyu Xiong

Zengzhou Wang

et al.

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2023

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“…Hive: advantages and disadvantages It is a part of the Hadoop ecosystem that provides random real-time read/write access to data in the Hadoop File System. HBase uses the Map-Reduce framework to process aggregate queries, which requires calculating in real-time and cannot keep the calculated result[20]. The advantages and disadvantages of HBase are listed in Table4.• Cassandra :The Cassandra database was created by Facebook and its architecture is inspired by Amazon's DynamoDB database while its data model is based on Google's BigTable.…”

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confidence: 99%

A Survey of Big Data Tools for Remote Healthcare Services

Ray,

Mainuddin,

Singha

et al. 2023

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Health Data storage and analytics are the two important parts of the health or drugs business and health research. Health Data storage and management are important for storing and retrieving Health Data efficiently. The scalable and flexible infrastructure capable of efficient storing and processing the millions of Health Data generated every day must be very much needed for the industry. Big Data tools and NoSQL databases are becoming the necessary tools to store millions of data and respond to given queries efficiently. In general relational databases are used for many applications, but they are not at all efficient for storing and processing Big Data. The drawbacks of relational databases motivate the developers to use NoSQL databases and Big Data tools while creating the Health application. A comparative study must be made to find out the performance of different Big Data platforms along with the NoSQL Databases to store Health Data for a Health-related application and to respond to queries efficiently. In this paper, we have tested the performance of Hadoop, HIVE, Cassandra, MongoDB, HBASE and NGMR to respond to different queries to store Health Data for a remote health framework. Such a study helps us to come up with new ideas that can help us to store and retrieve the Health Data of a particular application using a data model that is iteratively tested and modified. It provides us with an understanding of the Big Data solution or tool as well. The key aim of the study is to make a review on the capability of data storage and the read/write performance of the tools

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mentioning

confidence: 99%

A Survey of Big Data Tools for Remote Healthcare Services

Ray,

Mainuddin,

Singha

et al. 2023

Preprint

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Research and Application of Query Optimization Based on HBase

Cited by 1 publication

References 11 publications

A Survey of Big Data Tools for Remote Healthcare Services

A Survey of Big Data Tools for Remote Healthcare Services

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