MLS-C01 Exploratory Data Analysis Practice Question
Exhibit
Refer to the exhibit. ``` ERROR: Could not read CSV file 's3://bucket/data.csv': Error: (103) The CSV file contains a row with 5 fields, but the header has 4 fields. Row 1502: "2023-01-15","A","B","C","D" ```
A data scientist is using Amazon Athena to query a CSV file stored in S3. The query fails with the error: 'HIVE_CANNOT_OPEN_SPLIT: Number of fields in line 1502 does not match number of fields in the first line.' What is the most likely cause?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The CSV file has inconsistent number of columns in some rows.
The error indicates that a row has more fields than the header, which is exactly what happens when the CSV file has inconsistent number of columns in some rows. Option A is incorrect because the error does not mention delimiter; a different delimiter would cause all rows to have wrong number of fields, not just some. Option B is incorrect because missing header would cause Athena to treat the first row as data, not cause mismatched field counts later. Option C is incorrect because Athena can handle large files; the error is about schema mismatch, not file size.
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 CSV file uses a different delimiter than comma.
Why it's wrong here
The error does not mention delimiter; it mentions field count.
- ✗
The CSV file is missing a header row.
Why it's wrong here
The error states the header has 4 fields, so header exists.
- ✗
The CSV file is too large for Athena to process.
Why it's wrong here
Size is not indicated; error is about field count mismatch.
- ✓
The CSV file has inconsistent number of columns in some rows.
Why this is correct
The error indicates row 1502 has 5 fields while header has 4.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.