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DEA-C01 — questions

Page 3 of 16 · 313 total questions.

DEA-C01 Question 41

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Topic 1 · Question 41

A data engineer must ingest a source of structured data that is in .csv format into an Amazon S3 data lake. The .csv files contain 15 columns. Data analysts need to run Amazon Athena queries on one or two columns of the dataset. The data analysts rarely query the entire file. Which solution will meet these requirements MOST cost-effectively?

  • AUse an AWS Glue PySpark job to ingest the source data into the data lake in .csv format.
  • BCreate an AWS Glue extract, transform, and load (ETL) job to read from the .csv structured data source. Configure the job to ingest the data into the data lake in JSON format.
  • CUse an AWS Glue PySpark job to ingest the source data into the data lake in Apache Avro format.
  • DCreate an AWS Glue extract, transform, and load (ETL) job to read from the .csv structured data source. Configure the job to write the data into the data lake in Apache Parquet format. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Create an AWS Glue extract, transform, and load (ETL) job to read from the.csv structured data source. Configure the job to write the data into the data lake in Apache Parquet format.

Explanation

AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data. AWS Config tracks resource configuration changes and evaluates compliance. This option delivers the requirement at the lowest cost.

DEA-C01 Question 42

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Topic 1 · Question 42 · Select all that apply

A company has five offices in different AWS Regions. Each office has its own human resources (HR) department that uses a unique IAM role. The company stores employee records in a data lake that is based on Amazon S3 storage. A data engineering team needs to limit access to the records. Each HR department should be able to access records for only employees who are within the HR department's Region. Which combination of steps should the data engineering team take to meet this requirement with the LEAST operational overhead? (Choose two.)

  • AUse data filters for each Region to register the S3 paths as data locations.
  • BRegister the S3 path as an AWS Lake Formation location. (correct answer)
  • CModify the IAM roles of the HR departments to add a data filter for each department's Region.
  • DEnable fine-grained access control in AWS Lake Formation. Add a data filter for each Region. (correct answer)
  • ECreate a separate S3 bucket for each Region. Configure an IAM policy to allow S3 access. Restrict access based on Region.
Reveal answer & explanation
Correct answer: B, D

The correct answer is B, D. Option B: Register the S3 path as an AWS Lake Formation location. Option D: Enable fine-grained access control in AWS Lake Formation. Add a data filter for each Region.

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed. AWS Lake Formation builds and secures data lakes quickly.

DEA-C01 Question 43

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Topic 1 · Question 43 · Select all that apply

A company uses AWS Step Functions to orchestrate a data pipeline. The pipeline consists of Amazon EMR jobs that ingest data from data sources and store the data in an Amazon S3 bucket. The pipeline also includes EMR jobs that load the data to Amazon Redshift. The company's cloud infrastructure team manually built a Step Functions state machine. The cloud infrastructure team launched an EMR cluster into a VPC to support the EMR jobs. However, the deployed Step Functions state machine is not able to run the EMR jobs. Which combination of steps should the company take to identify the reason the Step Functions state machine is not able to run the EMR jobs? (Choose two.)

  • AUse AWS CloudFormation to automate the Step Functions state machine deployment. Create a step to pause the state machine during the EMR jobs that fail. Configure the step to wait for a human user to send approval through an email message. Include details of the EMR task in the email message for further analysis.
  • BVerify that the Step Functions state machine code has all IAM permissions that are necessary to create and run the EMR jobs. Verify that the Step Functions state machine code also includes IAM permissions to access the Amazon S3 buckets that the EMR jobs use. Use Access Analyzer for S3 to check the S3 access properties. (correct answer)
  • CCheck for entries in Amazon CloudWatch for the newly created EMR cluster. Change the AWS Step Functions state machine code to use Amazon EMR on EKS. Change the IAM access policies and the security group configuration for the Step Functions state machine code to reflect inclusion of Amazon Elastic Kubernetes Service (Amazon EKS).
  • DQuery the flow logs for the VPC. Determine whether the traffic that originates from the EMR cluster can successfully reach the data providers. Determine whether any security group that might be attached to the Amazon EMR cluster allows connections to the data source servers on the informed ports. (correct answer)
  • ECheck the retry scenarios that the company configured for the EMR jobs. Increase the number of seconds in the interval between each EMR task. Validate that each fallback state has the appropriate catch for each decision state. Configure an Amazon Simple Notification Service (Amazon SNS) topic to store the error messages.
Reveal answer & explanation
Correct answer: B, D

The correct answer is B, D. Option B: Verify that the Step Functions state machine code has all IAM permissions that are necessary to create and run the EMR jobs. Verify that the Step Functions state machine code also includes IAM permissions to access th... Option D: Query the flow logs for the VPC. Determine whether the traffic that originates from the EMR cluster can successfully reach the data providers. Determine whether any security group that might be attached to the Amazon...

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed. AWS Step Functions coordinates multi-step workflows as a managed state machine. Amazon EMR runs big-data frameworks like Spark and Hadoop on managed clusters.

DEA-C01 Question 44

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Topic 1 · Question 44

A company is developing an application that runs on Amazon EC2 instances. Currently, the data that the application generates is temporary. However, the company needs to persist the data, even if the EC2 instances are terminated. A data engineer must launch new EC2 instances from an Amazon Machine Image (AMI) and configure the instances to preserve the data. Which solution will meet this requirement?

  • ALaunch new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data. Apply the default settings to the EC2 instances.
  • BLaunch new EC2 instances by using an AMI that is backed by a root Amazon Elastic Block Store (Amazon EBS) volume that contains the application data. Apply the default settings to the EC2 instances.
  • CLaunch new EC2 instances by using an AMI that is backed by an EC2 instance store volume. Attach an Amazon Elastic Block Store (Amazon EBS) volume to contain the application data. Apply the default settings to the EC2 instances. (correct answer)
  • DLaunch new EC2 instances by using an AMI that is backed by an Amazon Elastic Block Store (Amazon EBS) volume. Attach an additional EC2 instance store volume to contain the application data. Apply the default settings to the EC2 instances.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume. Attach an Amazon Elastic Block Store (Amazon EBS) volume to contain the application data. Apply the default settings to the EC2...

Explanation

Amazon EC2 provides resizable virtual servers when you need full control of the operating system. Amazon EBS provides block storage attached to a single EC2 instance.

DEA-C01 Question 45

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Topic 1 · Question 45

A company uses Amazon Athena to run SQL queries for extract, transform, and load (ETL) tasks by using Create Table As Select (CTAS). The company must use Apache Spark instead of SQL to generate analytics. Which solution will give the company the ability to use Spark to access Athena?

  • AAthena query settings
  • BAthena workgroup (correct answer)
  • CAthena data source
  • DAthena query editor
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Athena workgroup

Explanation

Amazon Athena runs serverless SQL queries directly on data in Amazon S3 with no infrastructure to manage.

DEA-C01 Question 46

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Topic 1 · Question 46

A company needs to partition the Amazon S3 storage that the company uses for a data lake. The partitioning will use a path of the S3 object keys in the following format: s3://bucket/prefix/year=2023/month=01/day=01. A data engineer must ensure that the AWS Glue Data Catalog synchronizes with the S3 storage when the company adds new partitions to the bucket. Which solution will meet these requirements with the LEAST latency?

  • ASchedule an AWS Glue crawler to run every morning.
  • BManually run the AWS Glue CreatePartition API twice each day.
  • CUse code that writes data to Amazon S3 to invoke the Boto3 AWS Glue create_partition API call. (correct answer)
  • DRun the MSCK REPAIR TABLE command from the AWS Glue console.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use code that writes data to Amazon S3 to invoke the Boto3 AWS Glue create_partition API call.

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed. AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data.

DEA-C01 Question 47

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Topic 1 · Question 47

A media company uses software as a service (SaaS) applications to gather data by using third-party tools. The company needs to store the data in an Amazon S3 bucket. The company will use Amazon Redshift to perform analytics based on the data. Which AWS service or feature will meet these requirements with the LEAST operational overhead?

  • AAmazon Managed Streaming for Apache Kafka (Amazon MSK)
  • BAmazon AppFlow (correct answer)
  • CAWS Glue Data Catalog
  • DAmazon Kinesis
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Amazon AppFlow

Explanation

Amazon AppFlow securely transfers data between SaaS apps and AWS without code.

DEA-C01 Question 48

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Topic 1 · Question 48

A data engineer is using Amazon Athena to analyze sales data that is in Amazon S3. The data engineer writes a query to retrieve sales amounts for 2023 for several products from a table named sales_data. However, the query does not return results for all of the products that are in the sales_data table. The data engineer needs to troubleshoot the query to resolve the issue. The data engineer's original query is as follows: SELECT product_name, sum(sales_amount) FROM sales_data - WHERE year = 2023 - GROUP BY product_name - How should the data engineer modify the Athena query to meet these requirements?

  • AReplace sum(sales_amount) with count(*) for the aggregation.
  • BChange WHERE year = 2023 to WHERE extract(year FROM sales_data) = 2023. (correct answer)
  • CAdd HAVING sum(sales_amount) > 0 after the GROUP BY clause.
  • DRemove the GROUP BY clause.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Change WHERE year = 2023 to WHERE extract(year FROM sales_data) = 2023.

DEA-C01 Question 49

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Topic 1 · Question 49

A data engineer has a one-time task to read data from objects that are in Apache Parquet format in an Amazon S3 bucket. The data engineer needs to query only one column of the data. Which solution will meet these requirements with the LEAST operational overhead?

  • AConfigure an AWS Lambda function to load data from the S3 bucket into a pandas dataframe. Write a SQL SELECT statement on the dataframe to query the required column.
  • BUse S3 Select to write a SQL SELECT statement to retrieve the required column from the S3 objects. (correct answer)
  • CPrepare an AWS Glue DataBrew project to consume the S3 objects and to query the required column.
  • DRun an AWS Glue crawler on the S3 objects. Use a SQL SELECT statement in Amazon Athena to query the required column.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Use S3 Select to write a SQL SELECT statement to retrieve the required column from the S3 objects.

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed.

DEA-C01 Question 50

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Topic 1 · Question 50

A company uses Amazon Redshift for its data warehouse. The company must automate refresh schedules for Amazon Redshift materialized views. Which solution will meet this requirement with the LEAST effort?

  • AUse Apache Airflow to refresh the materialized views.
  • BUse an AWS Lambda user-defined function (UDF) within Amazon Redshift to refresh the materialized views.
  • CUse the query editor v2 in Amazon Redshift to refresh the materialized views. (correct answer)
  • DUse an AWS Glue workflow to refresh the materialized views.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use the query editor v2 in Amazon Redshift to refresh the materialized views.

Explanation

Amazon Redshift is a managed petabyte-scale data warehouse for complex analytical queries.

DEA-C01 Question 51

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Topic 1 · Question 51

A data engineer must orchestrate a data pipeline that consists of one AWS Lambda function and one AWS Glue job. The solution must integrate with AWS services. Which solution will meet these requirements with the LEAST management overhead?

  • AUse an AWS Step Functions workflow that includes a state machine. Configure the state machine to run the Lambda function and then the AWS Glue job. (correct answer)
  • BUse an Apache Airflow workflow that is deployed on an Amazon EC2 instance. Define a directed acyclic graph (DAG) in which the first task is to call the Lambda function and the second task is to call the AWS Glue job.
  • CUse an AWS Glue workflow to run the Lambda function and then the AWS Glue job.
  • DUse an Apache Airflow workflow that is deployed on Amazon Elastic Kubernetes Service (Amazon EKS). Define a directed acyclic graph (DAG) in which the first task is to call the Lambda function and the second task is to call the AWS Glue job.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use an AWS Step Functions workflow that includes a state machine. Configure the state machine to run the Lambda function and then the AWS Glue job.

Explanation

AWS Lambda runs code without provisioning servers and scales automatically, which minimizes operational overhead. AWS Step Functions coordinates multi-step workflows as a managed state machine. AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data.

DEA-C01 Question 52

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Topic 1 · Question 52

A company needs to set up a data catalog and metadata management for data sources that run in the AWS Cloud. The company will use the data catalog to maintain the metadata of all the objects that are in a set of data stores. The data stores include structured sources such as Amazon RDS and Amazon Redshift. The data stores also include semistructured sources such as JSON files and .xml files that are stored in Amazon S3. The company needs a solution that will update the data catalog on a regular basis. The solution also must detect changes to the source metadata. Which solution will meet these requirements with the LEAST operational overhead?

  • AUse Amazon Aurora as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the Aurora data catalog. Schedule the Lambda functions to run periodically.
  • BUse the AWS Glue Data Catalog as the central metadata repository. Use AWS Glue crawlers to connect to multiple data stores and to update the Data Catalog with metadata changes. Schedule the crawlers to run periodically to update the metadata catalog. (correct answer)
  • CUse Amazon DynamoDB as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the DynamoDB data catalog. Schedule the Lambda functions to run periodically.
  • DUse the AWS Glue Data Catalog as the central metadata repository. Extract the schema for Amazon RDS and Amazon Redshift sources, and build the Data Catalog. Use AWS Glue crawlers for data that is in Amazon S3 to infer the schema and to automatically update the Data Catalog.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Use the AWS Glue Data Catalog as the central metadata repository. Use AWS Glue crawlers to connect to multiple data stores and to update the Data Catalog with metadata changes. Schedule the crawlers to run periodicall...

Explanation

AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data.

DEA-C01 Question 53

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Topic 1 · Question 53

A company stores data from an application in an Amazon DynamoDB table that operates in provisioned capacity mode. The workloads of the application have predictable throughput load on a regular schedule. Every Monday, there is an immediate increase in activity early in the morning. The application has very low usage during weekends. The company must ensure that the application performs consistently during peak usage times. Which solution will meet these requirements in the MOST cost-effective way?

  • AIncrease the provisioned capacity to the maximum capacity that is currently present during peak load times.
  • BDivide the table into two tables. Provision each table with half of the provisioned capacity of the original table. Spread queries evenly across both tables.
  • CUse AWS Application Auto Scaling to schedule higher provisioned capacity for peak usage times. Schedule lower capacity during off-peak times. (correct answer)
  • DChange the capacity mode from provisioned to on-demand. Configure the table to scale up and scale down based on the load on the table.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use AWS Application Auto Scaling to schedule higher provisioned capacity for peak usage times. Schedule lower capacity during off-peak times.

Explanation

Auto Scaling adjusts capacity automatically to match demand, improving availability and cost efficiency. This option delivers the requirement at the lowest cost.

DEA-C01 Question 54

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Topic 1 · Question 54

A company is planning to migrate on-premises Apache Hadoop clusters to Amazon EMR. The company also needs to migrate a data catalog into a persistent storage solution. The company currently stores the data catalog in an on-premises Apache Hive metastore on the Hadoop clusters. The company requires a serverless solution to migrate the data catalog. Which solution will meet these requirements MOST cost-effectively?

  • AUse AWS Database Migration Service (AWS DMS) to migrate the Hive metastore into Amazon S3. Configure AWS Glue Data Catalog to scan Amazon S3 to produce the data catalog.
  • BConfigure a Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use AWS Glue Data Catalog to store the company's data catalog as an external data catalog. (correct answer)
  • CConfigure an external Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use Amazon Aurora MySQL to store the company's data catalog.
  • DConfigure a new Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use the new metastore as the company's data catalog.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Configure a Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use AWS Glue Data Catalog to store the company's data catalog as an external data catalog.

Explanation

AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data. Amazon EMR runs big-data frameworks like Spark and Hadoop on managed clusters. AWS Config tracks resource configuration changes and evaluates compliance. This option delivers the requirement at the lowest cost.

DEA-C01 Question 55

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Topic 1 · Question 55

A company uses an Amazon Redshift provisioned cluster as its database. The Redshift cluster has five reserved ra3.4xlarge nodes and uses key distribution. A data engineer notices that one of the nodes frequently has a CPU load over 90%. SQL Queries that run on the node are queued. The other four nodes usually have a CPU load under 15% during daily operations. The data engineer wants to maintain the current number of compute nodes. The data engineer also wants to balance the load more evenly across all five compute nodes. Which solution will meet these requirements?

  • AChange the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
  • BChange the distribution key to the table column that has the largest dimension. (correct answer)
  • CUpgrade the reserved node from ra3.4xlarge to ra3.16xlarge.
  • DChange the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Change the distribution key to the table column that has the largest dimension.

DEA-C01 Question 56

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Topic 1 · Question 56

A security company stores IoT data that is in JSON format in an Amazon S3 bucket. The data structure can change when the company upgrades the IoT devices. The company wants to create a data catalog that includes the IoT data. The company's analytics department will use the data catalog to index the data. Which solution will meet these requirements MOST cost-effectively?

  • ACreate an AWS Glue Data Catalog. Configure an AWS Glue Schema Registry. Create a new AWS Glue workload to orchestrate the ingestion of the data that the analytics department will use into Amazon Redshift Serverless. (correct answer)
  • BCreate an Amazon Redshift provisioned cluster. Create an Amazon Redshift Spectrum database for the analytics department to explore the data that is in Amazon S3. Create Redshift stored procedures to load the data into Amazon Redshift.
  • CCreate an Amazon Athena workgroup. Explore the data that is in Amazon S3 by using Apache Spark through Athena. Provide the Athena workgroup schema and tables to the analytics department.
  • DCreate an AWS Glue Data Catalog. Configure an AWS Glue Schema Registry. Create AWS Lambda user defined functions (UDFs) by using the Amazon Redshift Data API. Create an AWS Step Functions job to orchestrate the ingestion of the data that the analytics department will use into Amazon Redshift Serverless.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Create an AWS Glue Data Catalog. Configure an AWS Glue Schema Registry. Create a new AWS Glue workload to orchestrate the ingestion of the data that the analytics department will use into Amazon Redshift Serverless.

Explanation

Amazon Redshift is a managed petabyte-scale data warehouse for complex analytical queries. AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data. AWS Config tracks resource configuration changes and evaluates compliance. This option delivers the requirement at the lowest cost.

DEA-C01 Question 57

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Topic 1 · Question 57

A company stores details about transactions in an Amazon S3 bucket. The company wants to log all writes to the S3 bucket into another S3 bucket that is in the same AWS Region. Which solution will meet this requirement with the LEAST operational effort?

  • AConfigure an S3 Event Notifications rule for all activities on the transactions S3 bucket to invoke an AWS Lambda function. Program the Lambda function to write the event to Amazon Kinesis Data Firehose. Configure Kinesis Data Firehose to write the event to the logs S3 bucket.
  • BCreate a trail of management events in AWS CloudTraiL. Configure the trail to receive data from the transactions S3 bucket. Specify an empty prefix and write-only events. Specify the logs S3 bucket as the destination bucket.
  • CConfigure an S3 Event Notifications rule for all activities on the transactions S3 bucket to invoke an AWS Lambda function. Program the Lambda function to write the events to the logs S3 bucket.
  • DCreate a trail of data events in AWS CloudTraiL. Configure the trail to receive data from the transactions S3 bucket. Specify an empty prefix and write-only events. Specify the logs S3 bucket as the destination bucket. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Create a trail of data events in AWS CloudTraiL. Configure the trail to receive data from the transactions S3 bucket. Specify an empty prefix and write-only events. Specify the logs S3 bucket as the destination bucket.

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed. AWS CloudTrail records API activity for auditing and governance. AWS Config tracks resource configuration changes and evaluates compliance.

DEA-C01 Question 58

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Topic 1 · Question 58

A data engineer needs to maintain a central metadata repository that users access through Amazon EMR and Amazon Athena queries. The repository needs to provide the schema and properties of many tables. Some of the metadata is stored in Apache Hive. The data engineer needs to import the metadata from Hive into the central metadata repository. Which solution will meet these requirements with the LEAST development effort?

  • AUse Amazon EMR and Apache Ranger.
  • BUse a Hive metastore on an EMR cluster.
  • CUse the AWS Glue Data Catalog. (correct answer)
  • DUse a metastore on an Amazon RDS for MySQL DB instance.
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use the AWS Glue Data Catalog.

Explanation

AWS Glue is a serverless ETL and data-catalog service that prepares and integrates data. This option needs the least custom development effort.

DEA-C01 Question 59

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Topic 1 · Question 59

A company needs to build a data lake in AWS. The company must provide row-level data access and column-level data access to specific teams. The teams will access the data by using Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR. Which solution will meet these requirements with the LEAST operational overhead?

  • AUse Amazon S3 for data lake storage. Use S3 access policies to restrict data access by rows and columns. Provide data access through Amazon S3.
  • BUse Amazon S3 for data lake storage. Use Apache Ranger through Amazon EMR to restrict data access by rows and columns. Provide data access by using Apache Pig.
  • CUse Amazon Redshift for data lake storage. Use Redshift security policies to restrict data access by rows and columns. Provide data access by using Apache Spark and Amazon Athena federated queries.
  • DUse Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Use Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation.

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed. AWS Lake Formation builds and secures data lakes quickly.

DEA-C01 Question 60

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Topic 1 · Question 60 · Select all that apply

An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures. The POC test uses objects in Amazon S3 that contain the metrics in .csv format. The POC test uses Amazon Athena to query the data. The data is partitioned in the S3 bucket by date. As the amount of data increases, the company wants to optimize the storage solution to improve query performance. Which combination of solutions will meet these requirements? (Choose two.)

  • AAdd a randomized string to the beginning of the keys in Amazon S3 to get more throughput across partitions.
  • BUse an S3 bucket that is in the same account that uses Athena to query the data.
  • CUse an S3 bucket that is in the same AWS Region where the company runs Athena queries. (correct answer)
  • DPreprocess the .csv data to JSON format by fetching only the document keys that the query requires.
  • EPreprocess the .csv data to Apache Parquet format by fetching only the data blocks that are needed for predicates. (correct answer)
Reveal answer & explanation
Correct answer: C, E

The correct answer is C, E. Option C: Use an S3 bucket that is in the same AWS Region where the company runs Athena queries. Option E: Preprocess the.csv data to Apache Parquet format by fetching only the data blocks that are needed for predicates.

Explanation

Amazon S3 provides durable, scalable object storage that is fully managed. Amazon Athena runs serverless SQL queries directly on data in Amazon S3 with no infrastructure to manage.

Showing questions 41–60 of 313 · Page 3 of 16