DAS-C01 sample questions

Question 1

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?

Accepted Answer

Decrease the number of Amazon ES shards for the index.

Answer

Increase the memory of the Amazon ES master nodes.

Answer

Decrease the number of Amazon ES data nodes.

Answer

Increase the number of Amazon ES shards for the index.

Question 2

A company leverages Amazon Athena for ad-hoc queries against data stored in Amazon S3. The company wants to implement additional controls to separate query execution and query history among users, teams, or applications running in the same AWS account to comply with internal security policies.

Which solution meets these requirements?

Accepted Answer

Create an 1AM role for each given use case, assign appropriate permissions to the role for the given use case, and add the role to associate the role with Athena.

Answer

Create an S3 bucket for each given use case, create an S3 bucket policy that grants permissions to appropriate individual 1AM users, and apply the S3 bucket policy to the S3 bucket.

Answer

Create an Athena workgroup for each given use case, apply tags to the workgroup, and create an 1AM policy using the tags to apply appropriate permissions to the workgroup.

Answer

Create an AWS Glue Data Catalog resource policy for each given use case that grants permissions to appropriate individual 1AM users, and apply the resource policy to the specific tables used by Athena.

Question 3

A company stores its sales and marketing data that includes personally identifiable information (PH) 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?

Accepted Answer

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.

Answer

Create an EMR security configuration and ensure the security configuration is associated with the EMR clusters when they are created.

Answer

Enable the block public access setting for Amazon EMR at the account level before any EMR cluster is created.

Answer

Use AWS WAF to block public internet access to the EMR clusters across the board.

Question 4

A company analyzes its data in an Amazon Redshift data warehouse, which currently has a cluster of three dense storage nodes. Due to a recent business acquisition, the company needs to load an additional 4 TB of user data into Amazon Redshift. The engineering team will combine all the user data and apply complex calculations that require I/O intensive resources. The company needs to adjust the cluster's capacity to support the change in analytical and storage requirements.

Accepted Answer

Resize the cluster using elastic resize with dense storage nodes.

Answer

Resize the cluster using elastic resize with dense compute nodes.

Answer

Resize the cluster using classic resize with dense compute nodes.

Answer

Resize the cluster using classic resize with dense storage nodes.

Question 5

Once a month, a company receives a 100 MB .csv file compressed with gzip. The file contains 50,000 property listing records and is stored in Amazon S3 Glacier. The company needs its data analyst to query a subset of the data for a specific vendor.

What is the most cost-effective solution?

Accepted Answer

Load the data to Amazon S3 and query it with Amazon Athena.

Answer

Load the data into Amazon S3 and query it with Amazon S3 Select.

Answer

Query the data from Amazon S3 Glacier directly with Amazon Glacier Select.

Answer

Load the data to Amazon S3 and query it with Amazon Redshift Spectrum.

Question 6

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?

Accepted Answer

Add more memory and CPU capacity to the streaming application.

Answer

Merge the files in Amazon S3 to form larger files.

Answer

Increase the number of shards in Kinesis Data Streams.

Answer

Write the files to multiple S3 buckets.

Free DAS-C01 sample questions

Once a month, a company receives a 100 MB .csv file compressed with gzip. The file contains 50,000 property listing records and is stored in Amazon S3 Glacier. The company needs its data analyst to query a subset of the data for a specific vendor. What is the most cost-effective solution?

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