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A Comprehensive Study of HBase Storage Architecture—A Systematic Literature Review [PDF]
Symmetry, 2021 According to research, generally, 2.5 quintillion bytes of data are produced every day. About 90% of the world’s data has been produced in the last two years alone. The amount of data is increasing immensely.
Muhammad Umair Hassan, Ibrahim A Hameed
exaly +2 more sources
An Efficient Row Key Encoding Method With ASCII Code for Storing Geospatial Big Data in HBase
ISPRS International Journal of Geo-Information, 2020 Recently, increasing amounts of multi-source geospatial data (raster data of satellites and textual data of meteorological stations) have been generated, which can play a cooperative and important role in many research works.
Xiaochuang Yao, Quan Xiong, Diyou Liu
exaly +2 more sources
The Temporal mechanisms in HBase
Journal of Computer Science and Technology, 1996The research on Temporal Databases (TDB) has been a hot topic for quite a long time, but few implementations have been reported. The authors have developed a prototype of temporal DBMS in DOS/Windows environment, called HBase. This paper discusses its temporal structure, temporal syntax and semantics, as well as the special techniques used in the ...
Changjie Tang, Min Xiong
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Efficient Historical Query in HBase for Spatio-Temporal Decision Support [PDF]
International Journal of Computers, Communications and Control, 2016 Comparing to last decade, technologies to gather spatio-temporal data are more and more developed and easy to use or deploy, thus tens of billions, even trillions of sensed data are accumulated, which poses a challenge to spatio-temporal Decision Support
Xiaoying Chen, Weidong Xiao
exaly +1 more source
Spatio-temporal queries in HBase
2015 IEEE International Conference on Big Data (Big Data), 2015Geoscience gives insights into our surroundings and benefits many aspects of our life. Nowadays, with massive sensors deployed to sense all kinds of parameters for environments, tens of billions, even trillions of sensed data are collected and need to be analyzed for surveillance or other purposes.
Xiaoying Chen +3 more
openaire +1 more source
Information Sciences, 2015
Mining large graphs using distributed platforms has attracted a lot of research interests. Especially, large graph mining on Hadoop has been researched extensively, due to its simplicity and massive scalability. However, the design principle of Hadoop to maximize scalability often limits the efficiency of the graph algorithms.
Lee, H Lee, Ho +2 more
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Mining large graphs using distributed platforms has attracted a lot of research interests. Especially, large graph mining on Hadoop has been researched extensively, due to its simplicity and massive scalability. However, the design principle of Hadoop to maximize scalability often limits the efficiency of the graph algorithms.
Lee, H Lee, Ho +2 more
openaire +2 more sources
Modeling fuzzy relational database in HBase
Journal of Intelligent & Fuzzy Systems, 2016With the increase of massive data, a large number of business applications began to seek effective and scalable frameworks for data storages and processing. Under this background, emerging technologies for big data, such as Hadoop-based systems that use scalable distributed storage system HBase, become available.
Jian Liu 0028, X. X. Zhang
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Enumeration System on HBase for Low-Latency
2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2015HBase is a popular distributed Key/Value storage system based on the idea of BigTable. It is being used in many data-centers, such as Facebook and Twitter, for their portability and scalability. For the system, low-latency and large storage is expected when used in industry. However, it is time consuming when retrieving one column via another one. Many
Hang Chen +5 more
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