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NEW QUESTION 52
A media company has been performing analytics on log data generated by its applications. There has been a recent increase in the number of concurrent analytics jobs running, and the overall performance of existing jobs is decreasing as the number of new jobs is increasing. The partitioned data is stored in Amazon S3 One Zone-Infrequent Access (S3 One Zone-IA) and the analytic processing is performed on Amazon EMR clusters using the EMR File System (EMRFS) with consistent view enabled. A data analyst has determined that it is taking longer for the EMR task nodes to list objects in Amazon S3.
Which action would MOST likely increase the performance of accessing log data in Amazon S3?
- A. Increase the read capacity units (RCUs) for the shared Amazon DynamoDB table.
- B. Redeploy the EMR clusters that are running slowly to a different Availability Zone.
- C. Use a hash function to create a random string and add that to the beginning of the object prefixes when storing the log data in Amazon S3.
- D. Use a lifecycle policy to change the S3 storage class to S3 Standard for the log data.
Answer: A
Explanation:
https://docs.aws.amazon.com/emr/latest/ManagementGuide/emrfs-metadata.html
NEW QUESTION 53
A marketing company has data in Salesforce, MySQL, and Amazon S3. The company wants to use data from these three locations and create mobile dashboards for its users. The company is unsure how it should create the dashboards and needs a solution with the least possible customization and coding.
Which solution meets these requirements?
- A. Use Amazon Redshift federated queries to join the data sources. Use Amazon QuickSight to generate the mobile dashboards.
- B. Use AWS Lake Formation to migrate the data sources into Amazon S3. Use Amazon QuickSight to generate the mobile dashboards.
- C. Use Amazon QuickSight to connect to the data sources and generate the mobile dashboards.
- D. Use Amazon Athena federated queries to join the data sources. Use Amazon QuickSight to generate the mobile dashboards.
Answer: A
NEW QUESTION 54
A data analyst is using Amazon QuickSight for data visualization across multiple datasets generated by applications. Each application stores files within a separate Amazon S3 bucket. AWS Glue Data Catalog is used as a central catalog across all application data in Amazon S3. A new application stores its data within a separate S3 bucket. After updating the catalog to include the new application data source, the data analyst created a new Amazon QuickSight data source from an Amazon Athena table, but the import into SPICE failed.
How should the data analyst resolve the issue?
- A. Edit the permissions for the AWS Glue Data Catalog from within the AWS Glue console.
- B. Edit the permissions for the AWS Glue Data Catalog from within the Amazon QuickSight console.
- C. Edit the permissions for the new S3 bucket from within the Amazon QuickSight console.
- D. Edit the permissions for the new S3 bucket from within the S3 console.
Answer: C
NEW QUESTION 55
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