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NEW QUESTION: 1
Which of the following is the SHORTEST way to write 2001:0000:0d58:0000:0000:0095:7565:0001 in
proper IPv6 shorthand?
A. 2001:0:d58:0:0:95:7565:1
B. 2001:0:d58::95:7565:1
C. 2001:0:0d58::95:7565:1
D. 2001::d58::95:7565:1
Answer: B

NEW QUESTION: 2

A. Cisco Nexus 2248TP-E
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C. Cisco Nexus 2232TM
D. Cisco Nexus 2248TP
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NEW QUESTION: 3
회사는 Amazon EC2에서 상용 Apache Hadoop 클러스터를 실행하고 있습니다. 이 클러스터는 매일 Amazon S3에서 대용량 파일을 쿼리하는데 사용됩니다. Amazon S3의 데이터는 큐 레이션되었으며 추가 변환 단계가 필요하지 않습니다. 회사는 Amazon EC2에서 상용 비즈니스 인텔리전스 (BI) 도구를 사용하여 Hadoop 클러스터에 대한 쿼리를 실행하고 데이터를 시각화합니다.
회사는 Hadoop 클러스터 및 BI 도구를 관리하는 것과 관련된 오버 헤드 비용을 줄이거나 없애기를 원합니다. 회사는 최소한의 노력으로보다 비용 효율적인 솔루션을 제거하고자합니다. 시각화는 간단하며 몇 가지 기본 집계 단계만 수행하면 됩니다.
어떤 옵션이 회사의 요구 사항을 충족합니까?
A. Amazon Athena를 사용하여 Amazon S3에서 파일을 쿼리하고 분석하는 스크립트를 개발 하십시오. 그런 다음 Amazon QuickSight를 사용하여 Athena에 연결하고 시각화를 수행하십시오.
B. 일시적인 Amazon EMR 클러스터를 매일 실행하고 Apache Hive 스크립트를 개발하여 Amazon S3의 파일을 분석합니다. 작업이 완료되면 Amazon EMR 클러스터를 종료하십시오. Amazon QuickSight를 사용하여 Amazon EMR에 연결하고 시각화를 수행하십시오.
C. Amazon EC2에서 실행되는 상용 추출, 변환,로드 (ETL) 도구를 사용하여 처리 할 데이터를 준비합니다. 그런 다음 Amazon EC2에서 실행되는보다 빠르고 저렴한 Bl 도구로 전환하여 Amazon S3에서 데이터를 시각화 하십시오.
D. Amazon EC2에서 실행되는 MySQL 데이터베이스에서 호출 된 저장 프로 시저를 개발하여 EC2를 분석하여 Amazon S3의 파일을 분석합니다. 그런 다음 Amazon EC2에서 실행되는 빠른 인 메모리 BL 도구를 사용하여 데이터를 시각화 하십시오.
Answer: A