FGCache: Accelerating Aggregation Queries for OLAP Applications via Caching.

OLAP applications often perform aggregation queries, such as sum, avg, count, max, and min, to process a large dataset for getting a small result, and the key challenge for optimizing aggregation queries is to reduce the data volume needed to be read from disks. To address this problem, this paper presents an efficient caching component called FGCache (Fine-Grained Cache) for aggregation queries. FGCache is a query-driven caching policy, which aims to maintain the results of aggregation queries in the memory according to the predicates of user queries. The query results are divided into sets with fine-grained querying intervals, which are maintained via an in-memory tree index. We experimentally evaluate the performance of FGCache on various datasets and settings. The results suggest the efficiency and effectiveness of our proposal.