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Complete Data-Engineer-Associate Amazon Web Services Materials

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Question 28

A company has a data warehouse that contains a table that is named Sales. The company stores the table in Amazon Redshift The table includes a column that is named city_name. The company wants to query the table to find all rows that have a city_name that starts with "San" or "El."

Which SQL query will meet this requirement?

Options:

A.

Select * from Sales where city_name - '$(San|EI)";

B.

Select * from Sales where city_name -, ^(San|EI) *';

C.

Select * from Sales where city_name - '$(San&EI)";

D.

Select * from Sales where city_name -, ^(San&EI)";

Question 29

A data engineer runs Amazon Athena queries on data that is in an Amazon S3 bucket. The Athena queries use AWS Glue Data Catalog as a metadata table.

The data engineer notices that the Athena query plans are experiencing a performance bottleneck. The data engineer determines that the cause of the performance bottleneck is the large number of partitions that are in the S3 bucket. The data engineer must resolve the performance bottleneck and reduce Athena query planning time.

Which solutions will meet these requirements? (Choose two.)

Options:

A.

Create an AWS Glue partition index. Enable partition filtering.

B.

Bucket the data based on a column that the data have in common in a WHERE clause of the user query

C.

Use Athena partition projection based on the S3 bucket prefix.

D.

Transform the data that is in the S3 bucket to Apache Parquet format.

E.

Use the Amazon EMR S3DistCP utility to combine smaller objects in the S3 bucket into larger objects.

Question 30

A data engineer configured an AWS Glue Data Catalog for data that is stored in Amazon S3 buckets. The data engineer needs to configure the Data Catalog to receive incremental updates.

The data engineer sets up event notifications for the S3 bucket and creates an Amazon Simple Queue Service (Amazon SQS) queue to receive the S3 events.

Which combination of steps should the data engineer take to meet these requirements with LEAST operational overhead? (Select TWO.)

Options:

A.

Create an S3 event-based AWS Glue crawler to consume events from the SQS queue.

B.

Define a time-based schedule to run the AWS Glue crawler, and perform incremental updates to the Data Catalog.

C.

Use an AWS Lambda function to directly update the Data Catalog based on S3 events that the SQS queue receives.

D.

Manually initiate the AWS Glue crawler to perform updates to the Data Catalog when there is a change in the S3 bucket.

E.

Use AWS Step Functions to orchestrate the process of updating the Data Catalog based on 53 events that the SQS queue receives.

Question 31

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?

Options:

A.

Replace sum(sales amount) with count(*J for the aggregation.

B.

Change WHERE year = 2023 to WHERE extractlyear FROM sales data) = 2023.

C.

Add HAVING sumfsales amount) > 0 after the GROUP BY clause.

D.

Remove the GROUP BY clause

Page: 7 / 9
Exam Name: AWS Certified Data Engineer - Associate (DEA-C01)
Last Update: Nov 14, 2024
Questions: 130
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