원문정보
A Study on Data Modeling for VLDB Performance
초록
영어
It has been a huge amount of capacity of 10GB data base in a decade ago so far. Nowadays, however, 10TB is the common data base and even bigger capacities are available. So, new generation of Very Large Data Base (VLDB) has begun. Moving in to the new generation of VLDB has been caused major problems like backing up, restoring, and managing especially performance. It is very hard to export necessary data rapidly now due to the huge amount of data base. In the past, such kind of problems was out of the questions because of less data. As time goes on, however, optimization of performance became a big issue when the VLDB is common. Therefore, new professional technics are urgently required to maintain and optimize the data base that has become a VLDB or one that is in the progress of becoming one.
목차
1. 서론
2. 이론적 배경
2.1 VLDB
2.2 성능 데이터 모델링
2.3 정규화
2.4 반정규화
3. 데이터베이스 성능
4. 성능 향상 전략
4.1 정규화를 통한 성능 향상
4.2 반정규화를 통한 성능 향상
4.3 데이터 모델 단순화를 통한 성능 향상
4.4 테이블 수평/수직 분할을 통한 성능 향상
4.5 슈퍼타입/서브타입 구분을 통한 성능 향상
4.6 이력 모델의 구분과 기능성 컬럼을 통한 성능 향상
4.7 PK 순서 조정을 통한 성능 향상
4.8 FK 인덱스 생성을 통한 성능 향상
4.9 CHAR 형식에서 개발 오류 제거를 통한 성능 향상
4.10 효율적인 채번 방법을 통한 성능 향상
5. 결론
6. 참고문헌