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Amazon Web Services DAS-C01 Exam Dumps


Exam Code: DAS-C01
Exam Name: AWS Certified Data Analytics - Specialty

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Last Updated: 16-Apr-2024
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Amazon Web Services DAS-C01 Exam Questions


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DAS-C01 Exam Sample Questions:



A company has developed an Apache Hive script to batch process data stared in Amazon S3. The script needs to run once every day and store the output in Amazon S3. The company tested the script, and it completes within 30 minutes on a small local three-node cluster.
Which solution is the MOST cost-effective for scheduling and executing the script?

 

Create an AWS Lambda function to spin up an Amazon EMR cluster with a Hive execution step. Set
KeepJobFlowAliveWhenNoSteps to false and disable the termination protection flag. Use Amazon
CloudWatch Events to schedule the Lambda function to run daily.

 

Use the AWS Management Console to spin up an Amazon EMR cluster with Python Hue. Hive, and
Apache Oozie. Set the termination protection flag to true and use Spot Instances for the core nodes of
the cluster. Configure an Oozie workflow in the cluster to invoke the Hive script daily

 

Create an AWS Glue job with the Hive script to perform the batch operation. Configure the job to run
once a day using a time-based schedule

 

Use AWS Lambda layers and load the Hive runtime to AWS Lambda and copy the Hive script.
Schedule the Lambda function to run daily by creating a workflow using AWS Step Functions.


Create an AWS Glue job with the Hive script to perform the batch operation. Configure the job to run
once a day using a time-based schedule





A financial company uses Amazon S3 as its data lake and has set up a data warehouse using a multi-node Amazon Redshift cluster. The data files in the data lake are organized in folders based on the data source of each data file. All the data files are loaded to one table in the Amazon Redshift cluster using a separate COPY command for each data file location. With this approach, loading all the data files into Amazon Redshift takes
a long time to complete. Users want a faster solution with little or no increase in cost while maintaining the segregation of the data files in the S3 data lake.
Which solution meets these requirements?

 

Use Amazon EMR to copy all the data files into one folder and issue a COPY command to load the data into Amazon Redshift.

 

Load all the data files in parallel to Amazon Aurora, and run an AWS Glue job to load the data into
Amazon Redshift

 

Use an AWS Glue job to copy all the data files into one folder and issue a COPY command to load the
data into Amazon Redshift.

 

Create a manifest file that contains the data file locations and issue a COPY command to load the data
into Amazon Redshift.


Use Amazon EMR to copy all the data files into one folder and issue a COPY command to load the data into Amazon Redshift.





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?

 

Increase the memory of the Amazon ES master nodes.

 

Decrease the number of Amazon ES data nodes.

 

Decrease the number of Amazon ES shards for the index.

 

Increase the number of Amazon ES shards for the index.


Decrease the number of Amazon ES shards for the index.





A media analytics company consumes a stream of social media posts. The posts are sent to an Amazon Kinesis data stream partitioned on user_id. An AWS Lambda function retrieves the records and validates the content  before loading the posts into an Amazon Elasticsearch cluster. The validation process needs to receive the posts for a given user in the order they were received. A data analyst has noticed that, during peak hours, the social media platform posts take more than an hour to appear in the Elasticsearch cluster. What should the data analyst do reduce this latency?

 

Migrate the validation process to Amazon Kinesis Data Firehose.

 

Migrate the Lambda consumers from standard data stream iterators to an HTTP/2 stream consumer.

 

Increase the number of shards in the stream.

 

Configure multiple Lambda functions to process the stream.


Increase the number of shards in the stream.





A mobile gaming company wants to capture data from its gaming app and make the data available for analysis
immediately. The data record size will be approximately 20 KB. The company is concerned about achieving
optimal throughput from each device. Additionally, the company wants to develop a data stream processing
application with dedicated throughput for each consumer.
Which solution would achieve this goal?

 

Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature while consuming the data.

 

Have the app call the PutRecordBatch API to send data to Amazon Kinesis Data Firehose. Submit a
support case to enable dedicated throughput on the account.

 

Have the app use Amazon Kinesis Producer Library (KPL) to send data to Kinesis Data Firehose. Use
the enhanced fan-out feature while consuming the data.

 

Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Host the streamprocessing application on Amazon EC2 with Auto Scaling.


Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Host the streamprocessing application on Amazon EC2 with Auto Scaling.



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