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NEW QUESTION: 1
회사에는 현재 온-프레미스 데이터 센터에서 실행중인 2 계층 웹 응용 프로그램이 있습니다.
지난 몇 개월 동안 여러 인프라 오류가 발생하여 상당한 재정 손실이 발생했습니다. CIO는 애플리케이션을 AWS로 옮기는 것을 강력히 고려하고 있습니다. 다른 회사 임원들로부터 바이 인을 달성하기 위해 노력하는 동안 단기적으로 비즈니스 연속성을 향상시키는데 도움이 되는 재해 복구 계획을 개발하도록 요청합니다. 대상 RTO (Recovery Time Objective)는 4 시간, RPO (Recovery Point Objective)는 1 시간 이하로 지정합니다. 또한 2 주 내에 솔루션을 구현하도록 요청합니다.
데이터베이스의 크기는 200GB이고 인터넷 연결은 20Mbps입니다.
비용을 최소화하면서 어떻게 하시겠습니까?
A. 애플리케이션을 새로 설치하는 EBS 지원 프라이빗 AMI를 생성합니다.
데이터 센터에 스크립트를 설정하여 1 시간마다 로컬 데이터베이스를 백업하고 멀티 파트 업로드를 사용하여 결과 파일을 S3 버킷으로 암호화 및 복사하십시오.
B. 애플리케이션을 새로 설치하는 EBS 지원 프라이빗 AMI를 생성하십시오.
AMI 및 필수 EC2, AutoScaling 및 ELB 리소스가 포함된 CloudFormation 템플릿을 개발하여 다중 가용성 영역에 애플리케이션을 배포할수 있습니다.
안전한 VPN 연결을 통해 온 프레미스 데이터베이스에서 AWS의 데이터베이스 인스턴스로 트랜잭션을 비동기 적으로 복제합니다.
C. 애플리케이션의 평균로드를 지원할수 있는 컴퓨팅 최적화 EC2 인스턴스에 애플리케이션을 설치하십시오.
안전한 Direct Connect 연결을 통해 온 프레미스 데이터베이스에서 AWS의 데이터베이스 인스턴스로 트랜잭션을 동기적으로 복제합니다.
D. 여러 가용 영역의 Auto Scaling 그룹 내 EC2 인스턴스에 애플리케이션을 배포하십시오. 안전한 VPN 연결을 통해 온 프레미스 데이터베이스에서 AWS의 데이터베이스 인스턴스로 트랜잭션을 비동기 적으로 복제합니다.
Answer: B

NEW QUESTION: 2
You have an application that queries a database. Users report that the application is slower than expected.
You discover that several server process identifiers (SPIDs) have PAGELATCH_UP and PAGELATCH_EX waits. The resource descriptions of the SPIDs contains 2:1:1.
You need to resolve the issue.
What should you do?
A. Add data files to tempdb.
B. Add files to the file group of the application database.
C. Reduce the fill factor of all clustered indexes.
D. Allocate additional processor cores to the server.
Answer: A
Explanation:
Explanation/Reference:
Explanation:
PAGELATCH contention in tempdb is typically on allocation bitmaps and occurs with workloads with many concurrent connections creating and dropping small temporary tables (which are stored in tempdb).
Assuming that the temporary tables are needed for performance, the trick is to have multiple data files for tempdb so that the allocations are done round-robin among the files, the contention is split over multiple PFS pages, and so the overall contention goes down.
References: https://sqlperformance.com/2015/10/sql-performance/knee-jerk-wait-statistics-pagelatch

NEW QUESTION: 3
The data block density for a particular BSO database is between 10% and 90%, and data values within the block do not consecutively repeat. Which type of compression would be most appropriate to use?
A. RLE
B. No compression required
C. ZLIB
D. Bitmap
Answer: D
Explanation:
Explanation/Reference:
Bitmap is good for non-repeating data. It will use Bitmap or IVP (Index Value Pair).
Note: Bitmap compression, the default. Essbase stores only non-missing values and uses a bitmapping scheme. A bitmap uses one bit for each cell in the data block, whether the cell value is missing or non-missing. When a data block is not compressed, Essbase uses 8 bytes to store every non- missing cell. In most cases, bitmap compression conserves disk space more efficiently. However, much depends on the configuration of the data.
Incorrect answers:
RLE: You should change to RLE compression when the block density is < 3% (or if you have all the same values in the database - lots of zeros).
Note: RLE (Run Length Encoding) is a good compression type when your data has many zeros (block density low) or often repeats. RLE uses multiple compression compressions (one per block). RLE will use RLE, bitmap or IVP.