Titlebook: Big Scientific Data Management; First International Jianhui Li,Xiaofeng Meng,Zhihui Du Conference proceedings 2019 Springer Nature Switzer

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發(fā)怨言

EventDB: A Large-Scale Semi-structured Scientific Data Management System,ow to use these data efficiently to produce some scientific findings is a hot problem. There are many challenges in the use of these scientific big data, such as the storage, processing and sharing of the data. In this paper, we propose a data management system, EventDB, for scientific big data. Eve

Resection

Kinetic

Event-Oriented Caching System for ROOT Data Analysis in HEP,ced physical experimental devices can produce a large amount of Event data up?to PB level. While Compared to these massive data generation, data storage system based on files at the moment is out of date. Event data are mostly random accessed, but searching a few specific Event in large files is an

POWER

Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems,ormance data access and large volume of data storage as well. Some enterprises and research organizations are beginning to use tiered storage architectures, using tapes, disks or solid drives at the same time to reduce hardware purchase costs and power consumption. Tiered storage requires data manag

Obscure

Using Hadoop for High Energy Physics Data Analysis,rithms/frameworks and High IO throughput are key to meet the scalability and performance requirements of HEP offline data analysis. Though Hadoop has gained a lot of attention from scientific community for its scalability and parallel computing framework for large data sets, it’s still difficult to

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Ascendancy

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Big Scientific Data Management978-3-030-28061-1Series ISSN 0302-9743 Series E-ISSN 1611-3349