A Review on Query Processing and Optimization in SQL with different Indexing Techniques

Abstract: In data warehousing and OLAP applications, large data are processed. To perform scalar-level predicates in SQL with large amount of data become highly inadequate which requires supporting set-level comparison semantics that means to compare a tuples of group with a number of values. We present here a comprehensive review of the state-of-the-art processing a tuples of group with multiple values and to optimize the queries. Currently available queries are complex, complex to write 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 small-result-set property, which incurs intensive disk accesses as well as needed computations, which results in long processing time especially when data size is too large. Optimized query processing approach achieved by various studied algorithms shows very good performance to processing set predicates.

Keywords: Data Warehousing, Bitmap index,OLAP,Query processing and optimization,Word-Aligned Hybrid(WAH),VLC, Huffman Coding.