MLS-C01 Exploratory Data Analysis Practice Question
Exhibit
Refer to the exhibit. ``` # CloudWatch Logs Insights query fields @timestamp, @message | filter @message like /ERROR/ | stats count() by bin(5m) | sort @timestamp desc ```
A data scientist is investigating an application that logs errors to Amazon CloudWatch Logs. The data scientist runs the CloudWatch Logs Insights query shown in the exhibit. The query returns no results, even though the data scientist knows errors have occurred. 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 filter pattern is case-sensitive and the log messages use a different case for 'error'.
CloudWatch Logs Insights queries are case-sensitive by default; the filter pattern 'ERROR' will not match log messages that use 'error' or 'Error'. Option A is incorrect because the stats count() function is spelled correctly in the query. Option C is incorrect because sorting by timestamp descending does not prevent results from being returned; it only affects the order. Option D is incorrect because bin(5m) is a valid function in CloudWatch Logs Insights when there are logs within the time range.
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 stats count() function is misspelled.
Why it's wrong here
The function is correctly spelled as count().
- ✓
The filter pattern is case-sensitive and the log messages use a different case for 'error'.
Why this is correct
CloudWatch Logs Insights is case-sensitive; 'ERROR' will not match 'Error'.
- ✗
The query sorts by timestamp descending, which hides results.
Why it's wrong here
Sort order does not hide results; it just changes order.
- ✗
The bin(5m) function is not supported in CloudWatch Logs Insights.
Why it's wrong here
bin() is supported for time-based bucketing.
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