Design and implementation of the OLAP cache mechanism based on incremental learning naive Bayesian algorithm

In the era of the Big Data, cache is regarded as one of the most effective technique to improve the performance of accessing data. The majority of caches save each query result as a file, thus it is difficult to reuse the data from parts of some query results in the cache, and consequently some cach...

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Bibliographic Details
Published in:2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI) pp. 459 - 462
Main Authors: Yi Man, Jiongmin Zhang
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2016
Subjects:
Algorithm design and analysis
Bayes methods
Big data
Cache mechanism
Computers
Data warehouses
History
Internet
Naive Bayesian algorithm
OLAP
OLAP cache
ISBN:146738514X, 9781467385145
Online Access:Get full text
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Summary:In the era of the Big Data, cache is regarded as one of the most effective technique to improve the performance of accessing data. The majority of caches save each query result as a file, thus it is difficult to reuse the data from parts of some query results in the cache, and consequently some cached data were wasted. Through studying domestic and foreign related technologies, this paper designs an OLAP client-side cache mechanism using the Incremental Learning Naive Bayesian algorithm. The mechanism could decide whether to cache the current query results according to user's recent operations in order to increase the performance of cache. Ultimately, experiments illustrate that the mechanism is effective and efficient with the aspects of average query time and the cache hit rate.
ISBN:146738514X
9781467385145
DOI:10.1109/CCI.2016.7778964