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NEW QUESTION 36
A company analyzes historical data and needs to query data that is stored in Amazon S3. New data is generated daily as .csv files that are stored in Amazon S3. The company’s analysts are using Amazon Athena to perform SQL queries against a recent subset of the overall dat a. The amount of data that is ingested into Amazon S3 has increased substantially over time, and the query latency also has increased.
Which solutions could the company implement to improve query performance? (Choose two.)
- A. Run a daily AWS Glue ETL job to convert the data files to Apache Parquet and to partition the converted files. Create a periodic AWS Glue crawler to automatically crawl the partitioned data on a daily basis.
- B. Use MySQL Workbench on an Amazon EC2 instance, and connect to Athena by using a JDBC or ODBC connector. Run the query from MySQL Workbench instead of Athena directly.
- C. Run a daily AWS Glue ETL job to compress the data files by using the .lzo format. Query the compressed data.
- D. Run a daily AWS Glue ETL job to compress the data files by using the .gzip format. Query the compressed data.
- E. Use Athena to extract the data and store it in Apache Parquet format on a daily basis. Query the extracted data.
Answer: A,E
Explanation:
Reference:
https://aws.amazon.com/blogs/big-data/work-with-partitioned-data-in-aws-glue/
NEW QUESTION 37
An airline has been collecting metrics on flight activities for analytics. A recently completed proof of concept demonstrates how the company provides insights to data analysts to improve on-time departures. The proof of concept used objects in Amazon S3, which contained the metrics in .csv format, and used Amazon Athena for querying the dat a. As the amount of data increases, the data analyst wants to optimize the storage solution to improve query performance.
Which options should the data analyst use to improve performance as the data lake grows? (Choose three.)
- A. Use an S3 bucket in the same account as Athena.
- B. Use an S3 bucket in the same Region as Athena.
- C. Add a randomized string to the beginning of the keys in S3 to get more throughput across partitions.
- D. Preprocess the .csv data to Apache Parquet to reduce I/O by fetching only the data blocks needed for predicates.
- E. Compress the objects to reduce the data transfer I/O.
- F. Preprocess the .csv data to JSON to reduce I/O by fetching only the document keys needed by the query.
Answer: B,D,E
Explanation:
https://aws.amazon.com/blogs/big-data/top-10-performance-tuning-tips-for-amazon-athena/
NEW QUESTION 38
A streaming application is reading data from Amazon Kinesis Data Streams and immediately writing the data to an Amazon S3 bucket every 10 seconds. The application is reading data from hundreds of shards. The batch interval cannot be changed due to a separate requirement. The data is being accessed by Amazon Athena.
Users are seeing degradation in query performance as time progresses.
Which action can help improve query performance?
- A. Increase the number of shards in Kinesis Data Streams.
- B. Write the files to multiple S3 buckets.
- C. Merge the files in Amazon S3 to form larger files.
- D. Add more memory and CPU capacity to the streaming application.
Answer: C
Explanation:
Explanation
https://aws.amazon.com/blogs/big-data/top-10-performance-tuning-tips-for-amazon-athena/
NEW QUESTION 39
A company stores its sales and marketing data that includes personally identifiable information (PII) in Amazon S3. The company allows its analysts to launch their own Amazon EMR cluster and run analytics reports with the data. To meet compliance requirements, the company must ensure the data is not publicly accessible throughout this process. A data engineer has secured Amazon S3 but must ensure the individual EMR clusters created by the analysts are not exposed to the public internet.
Which solution should the data engineer to meet this compliance requirement with LEAST amount of effort?
- A. Enable the block public access setting for Amazon EMR at the account level before any EMR cluster is created.
- B. Create an EMR security configuration and ensure the security configuration is associated with the EMR clusters when they are created.
- C. Check the security group of the EMR clusters regularly to ensure it does not allow inbound traffic from IPv4 0.0.0.0/0 or IPv6 ::/0.
- D. Use AWS WAF to block public internet access to the EMR clusters across the board.
Answer: A
Explanation:
Explanation
https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-block-public-access.html
NEW QUESTION 40
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