상세정보
학술대회
Sweet KIWI: Statistics-Driven OLAP Acceleration using Query Column Sets
- 발행일
- 201603
- 출처
- International Conference on Extending Database Technology (EDBT) 2016, pp.680-681
- 협약과제
- 15ZS1400, 듀얼모드 배치.쿼리 분석을 제공하는 빅데이터 플랫폼 핵심기술 개발, 원종호
- 초록
- KIWI is a SQL-on-Hadoop system enabling batch and interactive analytics for big data. In database systems, materialized views, stored pre-computed results for queries, are one of the most commonly used techniques to improve the query processing speed. However, the key challenge in using materialized views is maintaining their freshness as base data changes. This paper introduces a new approach for accelerating OLAP query processing using query workload statistics and query column sets instead of materialized views. We present an architecture of SQL-on-Hadoop system using query column sets of original tables in database. The experimental results demonstrate that our system can provide improved performance by 1.77x on average in terms of TPC-H query processing.
- KSP 제안 키워드
- Big Data, Database systems, Hadoop system, New approach, OLAP query processing, Processing speed, Query workload, SQL-on-hadoop, TPC-H, improved performance, interactive analytics