Design Of Dynamic Ware House By Using Simulated Annealing Algorithm With On-Line Analytical Processing System

  • Ch. Suresh Kumar, Dr. Dhyan Chandra Yadav, Dr. D. Kiran Kumar


The Quantity Of Data Accessible To Large-Scale Businesses Is Increasing At A Breakneck Pace. Continuously, Operating Systems Produce New Data. In A Warehouse, Decision Support Services Such As Online Analytical Processing (Olap) May Include Hundreds Or Thousands Of Sophisticated Aggregate Queries Across A Huge Quantity Of Data. A Data Warehouse May Be Thought Of As A Collection Of Materialized Views That Are Specified Over A Set Of Relationships. When A Question Is Asked To Be Answered In This Document, The Appropriate Materialized Views And Tables Will Be Utilized To Generate The Finest Views And Tables For Building Any New Query. To Accomplish And Implement The Dynamic Warehouse Design, Three Complex Olap Queries With Join And Aggregation Operations Were Created, Views Were Created And Updated Via Windows Task Scheduler And Batch Files Based On Base Table Updates, Lattices Of Views Were Created Via Multiple View Processing Plant Operations, And The Simulated Annealing (Sa) Algorithm Was Developed And Introduced For Query Resolution. The Primary Objectives Of This Study Are To Demonstrate How The Usage Of Derived Data, Such As Materialized Views, For Run-Time Re-Optimization Of Aggregate Queries (Fast Response Time), Is Critical To The Success Of Any Data Warehouse.