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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
* Implement table partitioning to improve the manageability of the data warehouse and to avoid the need
* to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.
* Partition the Fact.Order table and retain a total of seven years of data.
* Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
* Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.
* Incrementally load all tables in the database and ensure that all incremental changes are processed.
* Maximize the performance during the data loading process for the Fact.Order partition.
* Ensure that historical data remains online and available for querying.
* Reduce ongoing storage costs while maintaining query performance for current data.
You are not permitted to make changes to the client applications.
You need to implement the data partitioning strategy.
How should you partition the Fact.Order table?
A. Create 2,557 partitions.
B. Create 17,520 partitions.
C. Use a granularity of two days.
D. Create 730 partitions.
Answer: A
Explanation:
Explanation
We create on partition for each day. 7 years times 365 days is 2,555. Make that 2,557 to provide for leap years.
From scenario: Partition the Fact.Order table and retain a total of seven years of data.
Maximize the performance during the data loading process for the Fact.Order partition.
NEW QUESTION: 2
고객은 시장 전체에서 이용 가능한 모든 거래를 보여주는 웹 사이트를 가지고 있습니다. 이 사이트에는 일반적으로 5 개의 큰 EC2 인스턴스가 로드됩니다.
그러나 추수 감사절 휴가 일주일 전에 거의 20 개의 큰 인스턴스가 발생합니다. 해당 기간 동안의 부하는 사무실 시간에 따라 하루 종일 다릅니다.
아래에 언급 된 솔루션 중 비용 효율적이며 웹 사이트의 성능을 향상시키는 데 도움이 되는 것은 무엇입니까?
A. 사전 휴가 기간 동안 20 개의 인스턴스가 연속적으로 실행되도록 설정합니다.
B. 사전 휴가 기간 동안 10 개의 인스턴스를 실행하도록 설정하고 AutoScaling 일정을 사용하여 10 개의 인스턴스를 더 시작하여 근무 시간 동안 만 확장 할 수 있습니다.
C. 사전 휴가 기간 동안 네트워크 I / O 정책에 따라 Auto Scaling을 사용하여 조직에서 15 개의 인스턴스가 실행되고 5 개의 인스턴스가 확장 및 축소되는 시나리오가 있는 시나리오.
D. 근무 시간 동안 매일 10 개의 인스턴스 만 실행하고 매일 10 개의 인스턴스를 수동으로 시작하십시오.
Answer: C
Explanation:
설명:
AWS는 확장 가능한 온 디맨드 인프라를 제공합니다. AWS EC2를 통해 사용자는 온 디맨드 인스턴스를 시작할 수 있으며 조직은 실행중인 인스턴스의 AMI를 생성해야 합니다. 조직에 다양한로드가 발생하고 로드 시간이 알려지지 않았지만 일반 트래픽보다 높은 경우, 조직은 사전에 몇 개의 인스턴스를 시작한 다음에 따라 확장 및 축소되는 정책으로 AutoScaling을 설정하는 것이 좋습니다. 네트워크 I / O 또는 CPU 사용률과 같은 EC2 메트릭 조직에서 AutoScaling 정책의 일부로 10 개의 추가 인스턴스를 모두 유지하는 경우 가끔 로드가 급증하는 경우 인스턴스를 시작하는 데 시간이 걸리고 최적의 성능을 제공하지 못할 수 있습니다. 따라서 비용 효율성을 위해 조직에서 추가 5 개의 인스턴스를 실행하고 AutoScaling 정책에 따라 다음 5 개의 인스턴스를 예약하는 것이 좋습니다.
http://media.amazonwebservices.com/AWS_Web_Hosting_Best_Practices.pdf
NEW QUESTION: 3
What does a transparent LAN switch use to build its CAM table?
A. BPDU messages exchanged with neighbor bridges
B. dynamic routing protocol updates from neighbor bridges
C. STP messages exchanged with neighbor bridges
D. analysis of the source MAC address of incoming frames on the bridge ports
Answer: D