The answer is to use the COPY command with a manifest file and gzip compression, as this is the most efficient approach for loading 50 TB of clickstream data into Amazon Redshift within two hours. The COPY command leverages Redshift’s massively parallel processing (MPP) architecture to read data directly from S3 in parallel across all nodes, and a manifest file allows you to specify multiple gzipped CSV files, which reduces network I/O and storage overhead. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of Redshift’s data ingestion best practices, often appearing as a question about optimizing bulk loads with sort keys and distribution keys—a common trap is choosing staging tables or INSERT commands, which lack the parallel throughput of COPY. For memory, remember that COPY with manifest and gzip is the “triple threat” for speed: parallelism, file control, and compression.
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses Amazon Redshift as a data warehouse. They need to load 50 TB of clickstream data from S3 into Redshift daily. The data arrives in 5-minute intervals as gzipped CSV files. The target table has a sort key and a distribution key. The load must complete within 2 hours. Which approach is MOST efficient?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the COPY command with a manifest file and gzip compression.
The COPY command is the most efficient way to load large volumes of data into Amazon Redshift because it uses the cluster's massively parallel processing (MPP) architecture to read data directly from S3 in parallel across all nodes. With a manifest file, you can specify multiple gzipped CSV files, and the gzip compression reduces network I/O and storage overhead. This approach can easily load 50 TB within 2 hours, especially when the target table has a sort key and distribution key, as COPY automatically leverages these for optimal data distribution and sorting during the load.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Use AWS Glue to transform the data and write to Redshift using JDBC.
Why it's wrong here
Glue is slower than native COPY for large volumes.
✗
Use a staging table and then merge using a stored procedure.
Why it's wrong here
Staging adds extra steps and time.
✗
Use a series of INSERT statements from a Lambda function.
Why it's wrong here
INSERT is not efficient for 50 TB.
✓
Use the COPY command with a manifest file and gzip compression.
Why this is correct
COPY is optimized for bulk loading from S3.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may overcomplicate the solution by choosing AWS Glue or staging tables, not realizing that Redshift's COPY command is purpose-built for high-speed parallel ingestion from S3 and is the most efficient method for bulk data loads.
Detailed technical explanation
How to think about this question
The COPY command in Redshift automatically decompresses gzip files in parallel across all slices, and the manifest file allows you to specify multiple files for concurrent loading, which maximizes throughput. When the target table has a distribution key, COPY distributes rows across nodes according to that key, and the sort key is applied during the load to maintain sorted order without a separate vacuum operation. In practice, for 50 TB of gzipped CSV data, the COPY command can achieve throughput of several TB per hour on a large cluster, easily meeting the 2-hour SLA.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the COPY command with a manifest file and gzip compression. — The COPY command is the most efficient way to load large volumes of data into Amazon Redshift because it uses the cluster's massively parallel processing (MPP) architecture to read data directly from S3 in parallel across all nodes. With a manifest file, you can specify multiple gzipped CSV files, and the gzip compression reduces network I/O and storage overhead. This approach can easily load 50 TB within 2 hours, especially when the target table has a sort key and distribution key, as COPY automatically leverages these for optimal data distribution and sorting during the load.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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