Abstract
Fast access of data from Data Warehouse (DW) is a need for today’s Business Intelligence (BI). In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. DW has been widely used by several organizations to manage data and use it for Decision Support System (DSS). Many methods have been used to optimize the performance of fetching data from DW. Query cache method is one of those methods that play an effective role in optimization. The proposed work is based on a cache-based mechanism that helps DW in two aspects: the first one is to reduce the execution time by directly accessing records from cache memory, and the second is to save cache memory space by eliminating non-frequent data. Our target is to fill the cache memory with the most used data. To achieve this goal aging-based Least Frequently Used (LFU) algorithm is used by considering the size and frequency of data simultaneously. The priority and expiry age of the data in the cache memory is managed by dealing with both the size and frequency of data. LFU sets priorities and counts the age of data placed in cache memory. The entry with the lowest age count and priority is eliminated first from the cache block. Ultimately, the proposed cache mechanism efficiently utilized cache memory and fills a large performance gap between the main DW and the business user query.
Highlights
Nowadays, businesses are growing rapidly, and the influence of Data Warehouses (DWs) has been increasing day by day, being used by several organizations
High customer demands are driving DWs to make fast business decisions based on the latest information [1]
There are two reasons for data not being available in the cache memory: One is when data is not fetched from the main database even once, and the second is when data is fetched once and still states that it is invalid, which means data is eliminated from cache memory for not being accessed frequently enough in order to save cache space
Summary
Businesses are growing rapidly, and the influence of Data Warehouses (DWs) has been increasing day by day, being used by several organizations. In [1], the author used the query cache algorithms for optimizing the process of data execution. To optimize the performance of accessing data, practitioners apply different approaches to make it easier and faster to access In this regard, researchers are focused on the most advanced query acceleration and cache memory techniques. We used the LFU algorithm for query caching while considering the size and frequency of the data at the same time. RELATED WORK Nowadays, fast retrieval of information from the data warehouse is the need of businesses to take timely decisions In this regard, many researchers have proposed different solutions to effectively fetch data from OLAP servers to meet the needs of BI users. Becomes where the age of data A is multiplied with frequency F(h) before cost and size calculation
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