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NEW QUESTION: 1
会社は、20のPb HDFSデータベースで大きなオンプレイスApache Hadoopクラスタを持ちます。クラスタは約200例と1 pbで4分の1に成長している。同社の目標は、Hadoopデータの弾力性を有効にし、クラスタノードを失うことの影響を制限し、コストを大幅に削減することである。現在のクラスタ
24 / 7と対話的クエリやバッチ処理を含むさまざまな分析ワークロードをサポートします。
どちらの解決策は、これらの要件を満たしています。
A. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
B. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: D
Explanation:
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.
NEW QUESTION: 2
Universal Containers has built a custom Visualforce page called "Knowledge" that is used internally to access Classic Knowledge.
Which two steps must be taken to ensure the Visualforce page continues to work after migrating to Lightning Knowledge?
Choose 2 answers
A. Configure the Visualforce page to use the Lightning Design System.
B. Remove Apex code references to the ArticleType field.
C. Rename the Visualforce page to "Lightning Knowledge"
D. Remove Apex code references to the Article RecordType field.
Answer: A,C
NEW QUESTION: 3
A. Fuzzing
B. Regression testing
C. Peer review
D. Stress testing
Answer: D
NEW QUESTION: 4
A company uses Aruba Mobility Controllers and Aruba APs. The APs incur a power outage.
Which Aruba feature should be implemented to allow the surrounding APs to provide wireless coverage for the area of the AP that lost power?
A. High Availability
B. Band Balancing
C. Adaptive Radio Management
D. Airtime Fairness
Answer: C