Automating Amazon Redshift Materialized View Refresh

Automate data processing by using AWS services.

Answer Correct answer: C — Use the query editor v2 in Amazon Redshift to refresh the materialized views.

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?

Use Apache Airflow to refresh the materialized views.
Use an AWS Lambda user-defined function (UDF) within Amazon Redshift to refresh the materialized views.
Use the query editor v2 in Amazon Redshift to refresh the materialized views. Correct Answer
Use an AWS Glue workflow to refresh the materialized views.

Community Votes

100%

100% of anonymous learners picked answer C. Votes are pick records left by other test-takers — they are not the verified answer.

Community Insight

The question tests knowledge of automated maintenance for Redshift objects, specifically highlighting that native auto-refresh or simple scheduling is less complex than external orchestration tools.

Learn how to automate Amazon Redshift materialized view refresh schedules with the least effort using built-in features or Query Editor v2.

Many candidates choose AWS Lambda (B) or Apache Airflow (A), over-engineering the solution by adding custom code and infrastructure management when native capabilities exist.

Community Discussion (11 comments)

magnorm 👍 2 Selected: C

https://docs.aws.amazon.com/redshift/latest/mgmt/query-editor-v2-schedule-query.html

pypelyncar 👍 2 Selected: C

the company can automate the refresh schedules for materialized views with minimal effort. This approach leverages the built-in capabilities of Amazon Redshift, reducing the need for additional services, configurations, or custom code. It aligns with the principle of using the simplest and most straightforward solution that meets the requirements, minimizing operational overhead and complexity

d8945a1 👍 3 Selected: C

We can schedule the refresh using query scheduler from Query Editor V2.

Christina666 👍 2 Selected: C

Amazon Redshift can automatically refresh materialized views with up-to-date data from its base tables when materialized views are created with or altered to have the autorefresh option. For more details, refer to the documentation here, https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html.

[Removed] 👍 2 Selected: C

https://docs.aws.amazon.com/redshift/latest/mgmt/query-editor-v2-schedule-query.html

FuriouZ 👍 2 Selected: C

You can set autorefresh for materialized views using CREATE MATERIALIZED VIEW. You can also use the AUTO REFRESH clause to refresh materialized views automatically.

GiorgioGss 👍 1 Selected: C

https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html

kj07 👍 1

You can set AUTO REFRESH option on creation. So I will vote with C.

confusedyeti69 👍 1 Selected: C

Lambda requires code and configuring permissions. A and D are additional overheads as well. Vote C

damaldon 👍 1

B. https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-UDFs.html

rralucard_ 👍 2 Selected: B

AWS Lambda allows running code in response to triggers without needing to provision or manage servers. However, creating a UDF within Amazon Redshift to call a Lambda function for this purpose involves writing custom code and managing permissions between Lambda and Redshift.

Comments & Corrections

No comments yet — spotted an error or have a note? Share it below.

Expert Analysis

Why the Answer Is Correct

Option C is correct because Amazon Redshift provides two primary mechanisms to handle this requirement with minimal effort: Native Auto-Refresh and Query Scheduler in Query Editor v2. The most efficient method is configuring AUTO REFRESH during the creation of the materialized view, which requires zero operational overhead after setup. Alternatively, if a specific schedule is needed rather than event-driven refreshes, Query Editor v2 allows users to schedule SQL queries directly without managing external services. Both approaches leverage built-in Redshift functionality, satisfying the 'LEAST effort' constraint.

Why the Other Options Are Wrong

Options A (Apache Airflow) and D (AWS Glue) introduce significant complexity by requiring the setup, configuration, and maintenance of external orchestration workflows. Option B (AWS Lambda UDF) is technically incorrect and overly complex; Lambda functions are not designed to trigger internal database metadata operations like refreshing views, and implementing such a pattern would require extensive custom coding and permission management, violating the least-effort principle.

Community Comment Notes

Community consensus strongly supports Option C, citing the availability of native auto-refresh features as well as the query scheduler in Query Editor v2. As user magnorm noted, "https://docs.aws.amazon.com/redshift/latest/mgmt/query-editor-v2-schedule-query.html" confirms the scheduling capability. Users like Christina666 pointed out that auto-refresh can be set during creation, while others like confusedyeti69 correctly identified that Lambda and orchestration tools add unnecessary overhead compared to native solutions.

Official Reference

Exam Strategy

When asked for the 'least effort' or 'simplest' solution, always prioritize managed, native service features over building custom integrations with Lambda, Glue, or third-party tools unless those features do not exist.

Frequently Asked Questions

Is Native Auto-Refresh better than Query Editor v2?

Native Auto-Refresh is generally preferred as it is event-driven and requires no ongoing management, but Query Editor v2 is also a valid low-effort option for scheduled refreshes.

Can I use Lambda to refresh Redshift views?

While possible via API calls, it is not the least effort solution and introduces unnecessary complexity compared to native Redshift capabilities.

More DEA-C01 FAQ →

Related Analysis

Practice All DEA-C01 Questions

Access 100 questions with complete answers and detailed explanations.

View Full DEA-C01 Practice Test →

← Back to DEA-C01 Study Guide