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Amazon AWS Certified Data Analytics - Specialty (DAS-C01) Exam Sample Questions (Q57-Q62):

NEW QUESTION # 57
A banking company wants to collect large volumes of transactional data using Amazon Kinesis Data Streams for real-time analytics. The company uses PutRecord to send data to Amazon Kinesis, and has observed network outages during certain times of the day. The company wants to obtain exactly once semantics for the entire processing pipeline.
What should the company do to obtain these characteristics?

* A. Rely on the processing semantics of Amazon Kinesis Data Analytics to avoid duplicate processing of events.
* B. Design the data producer so events are not ingested into Kinesis Data Streams multiple times.
* C. Design the application so it can remove duplicates during processing be embedding a unique ID in each record.
* D. Rely on the exactly one processing semantics of Apache Flink and Apache Spark Streaming included in Amazon EMR.
Answer: C

NEW QUESTION # 58
A large company receives files from external parties in Amazon EC2 throughout the day. At the end of the day, the files are combined into a single file, compressed into a gzip file, and uploaded to Amazon S3. The total size of all the files is close to 100 GB daily. Once the files are uploaded to Amazon S3, an AWS Batch program executes a COPY command to load the files into an Amazon Redshift cluster.
Which program modification will accelerate the COPY process?

* A. Split the number of files so they are equal to a multiple of the number of compute nodes in the Amazon Redshift cluster. Gzip and upload the files to Amazon S3. Run the COPY command on the files.
* B. Upload the individual files to Amazon S3 and run the COPY command as soon as the files become available.
* C. Apply sharding by breaking up the files so the distkey columns with the same values go to the same file.
Gzip and upload the sharded files to Amazon S3. Run the COPY command on the files.
* D. Split the number of files so they are equal to a multiple of the number of slices in the Amazon Redshift cluster. Gzip and upload the files to Amazon S3. Run the COPY command on the files.
Answer: D

NEW QUESTION # 59
A company is using an AWS Lambda function to run Amazon Athena queries against a cross-account AWS Glue Data Catalog. A query returns the following error:
HIVE METASTORE ERROR
The error message states that the response payload size exceeds the maximum allowed payload size. The queried table is already partitioned, and the data is stored in an Amazon S3 bucket in the Apache Hive partition format.
Which solution will resolve this error?

* A. Create a separate folder in the S3 bucket. Move the data files that need to be queried into that folder. Create an AWS Glue crawler that points to the folder instead of the S3 bucket.
* B. Modify the Lambda function to upload the query response payload as an object into the S3 bucket. Include an S3 object presigned URL as the payload in the Lambda function response.
* C. Run the MSCK REPAIR TABLE command on the queried table.
* D. Check the schema of the queried table for any characters that Athena does not support. Replace any unsupported characters with characters that Athena supports.
Answer: B

NEW QUESTION # 60
An airline has .csv-formatted data stored in Amazon S3 with an AWS Glue Data Catalog. Data analysts want to join this data with call center data stored in Amazon Redshift as part of a dally batch process. The Amazon Redshift cluster is already under a heavy load. The solution must be managed, serverless, well-functioning, and minimize the load on the existing Amazon Redshift cluster. The solution should also require minimal effort and development activity.
Which solution meets these requirements?

* A. Export the call center data from Amazon Redshift using a Python shell in AWS Glue. Perform the join with AWS Glue ETL scripts.
* B. Export the call center data from Amazon Redshift to Amazon EMR using Apache Sqoop. Perform the join with Apache Hive.
* C. Create an external table using Amazon Redshift Spectrum for the call center data and perform the join with Amazon Redshift.
* D. Unload the call center data from Amazon Redshift to Amazon S3 using an AWS Lambda function.
Perform the join with AWS Glue ETL scripts.
Answer: C

Explanation:
Explanation
https://docs.aws.amazon.com/redshift/latest/dg/c-spectrum-external-tables.html

NEW QUESTION # 61
A company is migrating its existing on-premises ETL jobs to Amazon EMR. The code consists of a series of jobs written in Java. The company needs to reduce overhead for the system administrators without changing the underlying code. Due to the sensitivity of the data, compliance requires that the company use root device volume encryption on all nodes in the cluster. Corporate standards require that environments be provisioned though AWS CloudFormation when possible.
Which solution satisfies these requirements?

* A. Use a CloudFormation template to launch an EMR cluster. In the configuration section of the cluster, define a bootstrap action to enable TLS.
* B. Create a custom AMI with encrypted root device volumes. Configure Amazon EMR to use the custom AMI using the CustomAmild property in the CloudFormation template.
* C. Install open-source Hadoop on Amazon EC2 instances with encrypted root device volumes. Configure the cluster in the CloudFormation template.
* D. Use a CloudFormation template to launch an EMR cluster. In the configuration section of the cluster, define a bootstrap action to encrypt the root device volume of every node.
Answer: B

NEW QUESTION # 62
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