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Amazon DAS-C01 Sample Questions – Free Practice Test & Real Exam Prep
Question #1
A gaming company is building a serverless data lake. The company is ingesting streamingdata into Amazon Kinesis Data Streams and is writing the data to Amazon S3 throughAmazon Kinesis Data Firehose. The company is using 10 MB as the S3 buffer size and isusing 90 seconds as the buffer interval. The company runs an AWS Glue ET L job tomerge and transform the data to a different format before writing the data back to Amazon S3.Recently, the company has experienced substantial growth in its data volume. The AWSGlue ETL jobs are frequently showing an OutOfMemoryError error.Which solutions will resolve this issue without incurring additional costs? (Select TWO.)
A. Place the small files into one S3 folder. Define one single table for the small S3 files inAWS Glue Data Catalog. Rerun the AWS Glue ET L jobs against this AWS Glue table.
B. Create an AWS Lambda function to merge small S3 files and invoke them periodically.Run the AWS Glue ETL jobs after successful completion of the Lambda function.
C. Run the S3DistCp utility in Amazon EMR to merge a large number of small S3 filesbefore running the AWS Glue ETL jobs.
D. Use the groupFiIes setting in the AWS Glue ET L job to merge small S3 files and rerunAWS Glue E TL jobs.
E. Update the Kinesis Data Firehose S3 buffer size to 128 MB. Update the buffer interval to900 seconds.
Answer: A,D
Explanation:
The groupFiles setting is a feature of AWS Glue that enables an ETL job to group
files when they are read from an Amazon S3 data store. This can reduce the
number of ETL tasks and in-memory partitions, and improve the performance and
memory efficiency of the job1. By using the groupFiles setting in the AWS Glue
ETL job, the gaming company can merge small S3 files and avoid the
OutOfMemoryError error.
The Kinesis Data Firehose S3 buffer size and buffer interval are parameters that
determine how much data is buffered before delivering it to Amazon S3. Increasing
the buffer size and buffer interval can result in larger files being delivered to
Amazon S3, which can reduce the number of small files and improve the
performance of downstream processing2. By updating the Kinesis Data Firehose
S3 buffer size to 128 MB and buffer interval to 900 seconds, the gaming company
can create fewer, larger S3 files and avoid the OutOfMemoryError error.
Question #2
A retail company has 15 stores across 6 cities in the United States. Once a month, thesales team requests a visualization in Amazon QuickSight that provides the ability to easilyidentify revenue trends across cities and stores.The visualization also helps identify outliersthat need to be examined with further analysis.Which visual type in QuickSight meets the sales team's requirements?
A company uses Amazon EC2 instances to receive files from external vendors throughouteach day. At the end of each day, the EC2 instances combine the files into a single file,perform gzip compression, and upload the single file to an Amazon S3 bucket. The totalsize of all the files is approximately 100 GB each day.When the files are uploaded to Amazon S3, an AWS Batch job runs a COPY command toload the files into an Amazon Redshift cluster.Which solution will MOST accelerate the COPY process?
A. Upload the individual files to Amazon S3. Run the COPY command as soon as the filesbecome available.
B. Split the files so that the number of files is equal to a multiple of the number of slices inthe Redshift cluster. Compress and upload the files to Amazon S3. Run the COPYcommand on the files.
C. Split the files so that each file uses 50% of the free storage on each compute node inthe Redshift cluster. Compress and upload the files to Amazon S3. Run the COPYcommand on the files.
D. pply sharding by breaking up the files so that the DISTKEY columns with the samevalues go to the same file. Compress and upload the sharded files to Amazon S3. Run theCOPY command on the files.
Answer: B
Question #4
A bank is building an Amazon S3 data lake. The bank wants a single data repository forcustomer data needs, such as personalized recommendations. The bank needs to useAmazon Kinesis Data Firehose to ingest customers' personal information, bank accounts,and transactions in near real time from a transactional relational database. All personally identifiable information (Pll) that is stored in the S3 bucket must be masked.The bank has enabled versioning for the S3 bucket.Which solution will meet these requirements?
A. Invoke an AWS Lambda function from Kinesis Data Firehose to mask the PII beforeKinesis Data Firehose delivers the data to the S3 bucket.
B. Use Amazon Macie to scan the S3 bucket. Configure Macie to discover Pll. Invoke anAWS Lambda function from S3 events to mask the Pll.
C. Configure server-side encryption (SSE) for the S3 bucket. Invoke an AWS Lambdafunction from S3 events to mask the PII.
D. Create an AWS Lambda function to read the objects, mask the Pll, and store the objectsback with same key. Invoke the Lambda function from S3 events.
Answer: A
Question #5
A company developed a new voting results reporting website that uses Amazon KinesisData Firehose to deliver full logs from AWS WAF to an Amazon S3 bucket. The company isnow seeking a solution to perform this infrequent data analysis with data visualizationcapabilities in a way that requires minimal development effort.Which solution MOST cost-effectively meets these requirements?
A. Use an AWS Glue crawler to create and update a table in the AWS Glue data catalogfrom the logs. Use Amazon Athena to perform ad-hoc analyses. Develop datavisualizations by using Amazon QuickSight.
B. Configure Kinesis Data Firehose to deliver the logs to an Amazon OpenSearch Servicecluster. Use OpenSearch Service REST APIs to analyze the data. Visualize the data bybuilding an OpenSearch Service dashboard.
C. Create an AWS Lambda function to convert the logs to CSV format. Add the Lambdafunction to the Kinesis Data Firehose transformation configuration. Use Amazon Redshift toperform a one-time analysis of the logs by using SQL queries. Develop data visualizationsby using Amazon QuickSight.
D. Create an Amazon EMR cluster and use Amazon S3 as the data source. Create anApache Spark job to perform a one-time analysis of the logs. Develop data visualizationsby using Amazon QuickSight.
Answer: A
Explanation: This solution meets the requirements because:
AWS Glue is a fully managed extract, transform, and load (ETL) service that can
be used to prepare and load data for analytics1. You can use AWS Glue to create
a crawler that automatically scans your logs in S3 and infers their schema and
format1. The crawler can also update the AWS Glue Data Catalog, which is a
central metadata repository that Athena uses to access your data in S31.
Amazon Athena is an interactive query service that allows you to analyze data in
S3 using standard SQL2. You can use Athena to perform ad-hoc analyses on your
logs without having to load them into a database or data warehouse2. Athena is
serverless, so you only pay for the queries you run and the amount of data
scanned by each query2.
Amazon QuickSight is a scalable, serverless, embeddable, machine learningpowered
business intelligence service that can create interactive
dashboards3. You can use QuickSight to develop data visualizations from your
Athena queries and share them with others3. QuickSight also supports live
analytics, which means you can see the latest data without having to refresh your
dashboards3.
Question #6
A large ecommerce company uses Amazon DynamoDB with provisioned read capacity andauto scaled write capacity to store its product catalog. The company uses Apache HiveQLstatements on an Amazon EMR cluster to query the DynamoDB table. After the companyannounced a sale on all of its products, wait times for each query have increased. The dataanalyst has determined that the longer wait times are being caused by throttling whenquerying the table.Which solution will solve this issue?
A. Increase the size of the EMR nodes that are provisioned.
B. Increase the number of EMR nodes that are in the cluster.
C. Increase the DynamoDB table's provisioned write throughput.
D. Increase the DynamoDB table's provisioned read throughput.
Answer: D
Question #7
A social media company is using business intelligence tools to analyze data for forecasting.The company is using Apache Kafka to ingest data. The company wants to build dynamicdashboards that include machine learning (ML) insights to forecast key business trends.The dashboards must show recent batched data that is not more than 75 minutes old.Various teams at the company want to view the dashboards by using Amazon QuickSightwith ML insights.Which solution will meet these requirements?
A. Replace Kafka with Amazon Managed Streaming for Apache Kafka (Amazon MSK). UseAWS Data Exchange to store the data in Amazon S3. Use SPICE in QuickSight Enterpriseedition to refresh the data from Amazon S3 each hour. Use QuickSight to create a dynamicdashboard that includes forecasting and ML insights.
B. Replace Kafka with an Amazon Kinesis data stream. Use AWS Data Exchange to storethe data in Amazon S3. Use SPICE in QuickSight Standard edition to refresh the data fromAmazon S3 each hour. Use QuickSight to create a dynamic dashboard that includesforecasting and ML insights.
C. Configure the Kafka-Kinesis-Connector to publish the data to an Amazon Kinesis DataFirehose delivery stream. Configure the delivery stream to store the data in Amazon S3with a max buffer size of 60 seconds. Use SPICE in QuickSight Enterprise edition torefresh the data from Amazon S3 each hour. Use QuickSight to create a dynamicdashboard that includes forecasting and ML insights.
D. Configure the Kafka-Kinesis-Connector to publish the data to an Amazon Kinesis DataFirehose delivery stream. Configure the delivery stream to store the data in Amazon S3with a max buffer size of 60 seconds. Refresh the data in QuickSight Standard edition SPICE from Amazon S3 by using a scheduled AWS Lambda function. Configure theLambda function to run every 75 minutes and to invoke the QuickSight API to create adynamic dashboard that includes forecasting and ML insights.
Answer: C
Question #8
A company recently created a test AWS account to use for a development environmentThe company also created a production AWS account in another AWS Region As part ofits security testing the company wants to send log data from Amazon CloudWatch Logs inits production account to an Amazon Kinesis data stream in its test accountWhich solution will allow the company to accomplish this goal?
A. Create a subscription filter in the production accounts CloudWatch Logs to target theKinesis data stream in the test account as its destination In the test account create an 1AMrole that grants access to the Kinesis data stream and the CloudWatch Logs resources inthe production account
B. In the test account create an 1AM role that grants access to the Kinesis data stream andthe CloudWatch Logs resources in the production account Create a destination datastream in Kinesis Data Streams in the test account with an 1AM role and a trust policy thatallow CloudWatch Logs in the production account to write to the test account
C. In the test account, create an 1AM role that grants access to the Kinesis data streamand the CloudWatch Logs resources in the production account Create a destination datastream in Kinesis Data Streams in the test account with an 1AM role and a trust policy thatallow CloudWatch Logs in the production account to write to the test account
D. Create a destination data stream in Kinesis Data Streams in the test account with an1AM role and a trust policy that allow CloudWatch Logs in the production account to writeto the test account Create a subscription filter in the production accounts CloudWatch Logsto target the Kinesis data stream in the test account as its destination
Answer: D
Question #9
A banking company wants to collect large volumes of transactional data using AmazonKinesis Data Streams for real-time analytics. The company usesPutRecord to send data toAmazon Kinesis, and has observed network outages during certain times of the day. Thecompany wants to obtain exactly once semantics for the entire processing pipeline.What should the company do to obtain these characteristics?
A. Design the application so it can remove duplicates during processing be embedding aunique ID in each record.
B. Rely on the processing semantics of Amazon Kinesis Data Analytics to avoid duplicateprocessing of events.
C. Design the data producer so events are not ingested into Kinesis Data Streams multipletimes.
D. Rely on the exactly one processing semantics of Apache Flink and Apache SparkStreaming included in Amazon EMR.
A company uses Amazon kinesis Data Streams to ingest and process customer behaviorinformation from application users each day. A data analytics specialist notices that its datastream is throttling. The specialist has turned on enhanced monitoring for the Kinesis datastream and has verified that the data stream did not exceed the data limits. The specialistdiscovers that there are hot shardsWhich solution will resolve this issue?
A. Use a random partition key to ingest the records.
B. Increase the number of shards Split the size of the log records.
C. Limit the number of records that are sent each second by the producer to match thecapacity of the stream.
D. Decrease the size of the records that are sent from the producer to match the capacityof the stream.
Answer: A
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