Partitioning Technology and Fast Content Movements of Big Data
Date Issued
2013
Date
2013
Author(s)
Lin, Te-Yuan
Abstract
Database storage storing abundant data usually accompanies slow performance of query and data manipulation. This thesis presents a model and methodology of faster query and data manipulation of mass data rows stored in a big table. In this thesis, it depicts the solution to manipulate large data sets of one table which moves into and out of another logical table with outstanding efficiency compared with traditional transactional way. With this idea, the table structure needs to be redesigned to accommodate and keep data, in other words, the table needs to be "partitioned".
It also covers partitioning strategies which are applied to various scenarios such as the data sliding window scenario, data archiving, and partition consolidation and movement practice.
Subjects
巨量資料
大資料
海量資料
資料分割
資料庫
快速
數據庫
Type
thesis
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ntu-102-R00944051-1.pdf
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