Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol. 9, Issue 7 , 2022
A System for Query Processing and Optimization Using Variable Length Encoding

Author : Akshita S. Khoriya 1 Madhuri S. Madeshi 2 Anand V. Saurkar 3 Payal S. Chirde 4 Shreya S. Kandekar 5 Chiranjeev D. Garhwani 6

Date of Publication :7th March 2016

Abstract: In data warehousing and OLAP applications, large amount of data are processed. To perform operations of predicates in SQL, large amount of data become highly inadequate which requires supporting to compare a tuples of group with a number of values. Currently available queries are complex, complex to write and create as well as challenging for database engine to optimize, which results in costly evaluation. Many of the available query processing algorithms does not take the advantage of the smallresult-set property, which incurs intensive disk accesses as well as needed computations, which results in long processing time. Optimized query processing approach achieved by various studied algorithms shows very good performance to processing set predicates. We presented here bitmap index and developed a very effective bitmap pruning strategy by using Huffman coding which is variable length compression technique for processing queries, which completely removes the necessity of scanning and processing the entire data set (table), which results in efficient execution of the query processing. Experiments verified our technique is much more efficient than existing algorithms in processing queries and retrieving data from large datasets.

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