scholarly journals Massive AIS data storage and query based on Hadoop platform

2021 ◽  
Vol 1948 (1) ◽  
pp. 012016
Author(s):  
Taizhi Lv ◽  
Chenyong He ◽  
Juan Zhang ◽  
Zhiyang Song
Keyword(s):  
2013 ◽  
Vol 68 (1) ◽  
pp. 488-507 ◽  
Author(s):  
Wei Kuang Lai ◽  
Yi-Uan Chen ◽  
Tin-Yu Wu ◽  
Mohammad S. Obaidat

2018 ◽  
Vol 11 (1) ◽  
pp. 98
Author(s):  
Liu Xiang Wei

In today's society has entered the era of big data, data of the diversity and the amount of data increases to the data storage and processing brought great challenges, Hadoop HDFS and MapReduce better solves the these two problems. Classical K-means algorithm is the most widely used one based on the partition of the clustering algorithm. At the completion of the cluster configuration based on, the k-means algorithm in cluster mode of operation principle and in the cluster mode realized kmeans algorithm, and the experimental results are research and analysis, summarized the k-means algorithm is run on the Hadoop platform's strengths and limitations.


2021 ◽  
Vol 11 (18) ◽  
pp. 8651
Author(s):  
Vladimir Belov ◽  
Alexander N. Kosenkov ◽  
Evgeny Nikulchev

One of the most popular methods for building analytical platforms involves the use of the concept of data lakes. A data lake is a storage system in which the data are presented in their original format, making it difficult to conduct analytics or present aggregated data. To solve this issue, data marts are used, representing environments of stored data of highly specialized information, focused on the requests of employees of a certain department, the vector of an organization’s work. This article presents a study of big data storage formats in the Apache Hadoop platform when used to build data marts.


2013 ◽  
Vol 427-429 ◽  
pp. 2273-2277 ◽  
Author(s):  
Yu Su ◽  
Wan Lin Gao ◽  
Li Na Yu ◽  
Hui Hu ◽  
Xuan Luo

With the further development of cloud computing and wireless body area network (WBAN), uploading the massive body signs parameters to the Internet for storage in real time has become possible. For the requirement of how to store the massive WBAN data, this thesis proposes the WBAN data storage method based on HBase, and elaborates how to design the storage architecture, the storage system and data query client by using HBase, a kind of tool in Hadoop platform. The WBAN data storage method based on HBase is important to efficiently manage the massive WBAN data.


Author(s):  
Richard S. Chemock

One of the most common tasks in a typical analysis lab is the recording of images. Many analytical techniques (TEM, SEM, and metallography for example) produce images as their primary output. Until recently, the most common method of recording images was by using film. Current PS/2R systems offer very large capacity data storage devices and high resolution displays, making it practical to work with analytical images on PS/2s, thereby sidestepping the traditional film and darkroom steps. This change in operational mode offers many benefits: cost savings, throughput, archiving and searching capabilities as well as direct incorporation of the image data into reports.The conventional way to record images involves film, either sheet film (with its associated wet chemistry) for TEM or PolaroidR film for SEM and light microscopy. Although film is inconvenient, it does have the highest quality of all available image recording techniques. The fine grained film used for TEM has a resolution that would exceed a 4096x4096x16 bit digital image.


Author(s):  
T. A. Dodson ◽  
E. Völkl ◽  
L. F. Allard ◽  
T. A. Nolan

The process of moving to a fully digital microscopy laboratory requires changes in instrumentation, computing hardware, computing software, data storage systems, and data networks, as well as in the operating procedures of each facility. Moving from analog to digital systems in the microscopy laboratory is similar to the instrumentation projects being undertaken in many scientific labs. A central problem of any of these projects is to create the best combination of hardware and software to effectively control the parameters of data collection and then to actually acquire data from the instrument. This problem is particularly acute for the microscopist who wishes to "digitize" the operation of a transmission or scanning electron microscope. Although the basic physics of each type of instrument and the type of data (images & spectra) generated by each are very similar, each manufacturer approaches automation differently. The communications interfaces vary as well as the command language used to control the instrument.


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