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NEW QUESTION 35
A company's data analyst needs to ensure that queries executed in Amazon Athena cannot scan more than a prescribed amount of data for cost control purposes. Queries that exceed the prescribed threshold must be canceled immediately.
What should the data analyst do to achieve this?

  • A. Configure Athena to invoke an AWS Lambda function that terminates queries when the prescribed threshold is crossed.
  • B. For each workgroup, set the control limit for each query to the prescribed threshold.
  • C. Enforce the prescribed threshold on all Amazon S3 bucket policies
  • D. For each workgroup, set the workgroup-wide data usage control limit to the prescribed threshold.

Answer: B

Explanation:
Explanation
https://docs.aws.amazon.com/athena/latest/ug/manage-queries-control-costs-with-workgroups.html

 

NEW QUESTION 36
A data analyst runs a large number of data manipulation language (DML) queries by using Amazon Athena with the JDBC driver. Recently, a query failed after It ran for 30 minutes. The query returned the following message Java.sql.SGLException: Query timeout The data analyst does not immediately need the query results However, the data analyst needs a long-term solution for this problem Which solution will meet these requirements?

  • A. Split the query into smaller queries to search smaller subsets of data.
  • B. Save the tables as compressed .csv files
  • C. In the settings for Athena, adjust the DML query timeout limit
  • D. In the Service Quotas console, request an increase for the DML query timeout

Answer: A

 

NEW QUESTION 37
A banking company is currently using an Amazon Redshift cluster with dense storage (DS) nodes to store sensitive data. An audit found that the cluster is unencrypted. Compliance requirements state that a database with sensitive data must be encrypted through a hardware security module (HSM) with automated key rotation.
Which combination of steps is required to achieve compliance? (Choose two.)

  • A. Enable Elliptic Curve Diffie-Hellman Ephemeral (ECDHE) encryption in the HSM.
  • B. Modify the cluster with an HSM encryption option and automatic key rotation.
  • C. Set up a trusted connection with HSM using a client and server certificate with automatic key rotation.
  • D. Enable HSM with key rotation through the AWS CLI.
  • E. Create a new HSM-encrypted Amazon Redshift cluster and migrate the data to the new cluster.

Answer: B,D

 

NEW QUESTION 38
A company uses Amazon Elasticsearch Service (Amazon ES) to store and analyze its website clickstream data. The company ingests 1 TB of data daily using Amazon Kinesis Data Firehose and stores one day's worth of data in an Amazon ES cluster.
The company has very slow query performance on the Amazon ES index and occasionally sees errors from Kinesis Data Firehose when attempting to write to the index. The Amazon ES cluster has 10 nodes running a single index and 3 dedicated master nodes. Each data node has 1.5 TB of Amazon EBS storage attached and the cluster is configured with 1,000 shards. Occasionally, JVMMemoryPressure errors are found in the cluster logs.
Which solution will improve the performance of Amazon ES?

  • A. Increase the number of Amazon ES shards for the index.
  • B. Increase the memory of the Amazon ES master nodes.
  • C. Decrease the number of Amazon ES shards for the index.
  • D. Decrease the number of Amazon ES data nodes.

Answer: C

 

NEW QUESTION 39
A company owns facilities with IoT devices installed across the world. The company is using Amazon Kinesis Data Streams to stream data from the devices to Amazon S3. The company's operations team wants to get insights from the IoT data to monitor data quality at ingestion. The insights need to be derived in near-real time, and the output must be logged to Amazon DynamoDB for further analysis.
Which solution meets these requirements?

  • A. Connect Amazon Kinesis Data Firehose to analyze the stream data by using an AWS Lambda function.
    Save the data to Amazon S3. Then run an AWS Glue job on schedule to ingest the data into DynamoDB.
  • B. Connect Amazon Kinesis Data Firehose to analyze the stream data by using an AWS Lambda function.
    Save the output to DynamoDB by using the default output from Kinesis Data Firehose.
  • C. Connect Amazon Kinesis Data Analytics to analyze the stream data. Save the output to DynamoDB by using the default output from Kinesis Data Analytics.
  • D. Connect Amazon Kinesis Data Analytics to analyze the stream data. Save the output to DynamoDB by using an AWS Lambda function.

Answer: B

 

NEW QUESTION 40
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