The answer is that the row count mismatch between PostgreSQL and Redshift in a Glue Python shell job is most likely caused by the SELECT * query including columns with data types that are not supported by psycopg2. When psycopg2 encounters an unsupported data type—such as PostgreSQL’s interval, array, or composite types—it silently fails to fetch or convert those rows, causing them to be dropped during the transfer without raising an error. This scenario tests your understanding of how AWS Glue Python shell jobs interact with source databases, a common trap on the AWS Certified Data Engineer Associate DEA-C01 exam where candidates might overlook data type compatibility issues. Unlike Spark jobs, a Python shell runs on a single executor, so distribution or parallelism is not the culprit. Remember the memory tip: “If the row count shrinks, check the data type links.”
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 data engineer is troubleshooting an AWS Glue ETL job that uses a Python shell script to extract data from an Amazon RDS for PostgreSQL database and load it into an Amazon Redshift table. The job runs successfully, but the data engineer notices that the row count in Redshift is consistently lower than the row count in PostgreSQL. The job uses a SELECT * query without any filtering. The data engineer suspects that some rows are being dropped during the transfer. The job uses the psycopg2 library to connect to PostgreSQL and the psycopg2 connection is configured with autocommit=True. The Redshift table has no constraints that would reject rows. What is the most likely cause of the missing rows?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The SELECT * query includes columns with data types that are not supported by psycopg2.
Option C is correct. If the Redshift table is set to distribute data, and if the distribution key is not unique, some rows may be lost if there are duplicates? Actually, the most common cause is that the Glue job is using multiple executors, and the data is being split across them, but Python shell uses a single executor. However, the most plausible answer is that the SELECT * query may include columns with special characters that are not handled correctly. Option A is wrong because autocommit=True should not cause data loss. Option B is wrong because SSL/TLS is about encryption, not row count. Option D is wrong because the Redshift table has no constraints.
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.
✓
The SELECT * query includes columns with data types that are not supported by psycopg2.
Why this is correct
Unsupported data types may cause rows to be skipped or nullified.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The SSL/TLS connection to PostgreSQL is dropping packets.
Why it's wrong here
SSL/TLS ensures data integrity; it does not drop packets.
✗
The autocommit=True setting is causing incomplete transactions.
Why it's wrong here
Autocommit ensures each statement is committed immediately, not losing data.
✗
The Redshift table has a distribution key that causes some rows to be silently discarded.
Why it's wrong here
Distribution keys do not discard rows; they just distribute them.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The SELECT * query includes columns with data types that are not supported by psycopg2. — Option C is correct. If the Redshift table is set to distribute data, and if the distribution key is not unique, some rows may be lost if there are duplicates? Actually, the most common cause is that the Glue job is using multiple executors, and the data is being split across them, but Python shell uses a single executor. However, the most plausible answer is that the SELECT * query may include columns with special characters that are not handled correctly. Option A is wrong because autocommit=True should not cause data loss. Option B is wrong because SSL/TLS is about encryption, not row count. Option D is wrong because the Redshift table has no constraints.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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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