Log Parsing for Error Patterns | Dataford Interview Questions

Cruise autonomous vehicle services emit structured log lines during operation. Given a collection of log lines, identify recurring ERROR message patterns even when variable values such as IDs, timestamps, or numeric measurements differ.

Each log line has the format [timestamp] LEVEL message, where timestamp contains no spaces, LEVEL is INFO, WARN, or ERROR, and message is the remaining text. Consider two error messages equivalent when they become identical after replacing every UUID with <UUID>, hexadecimal value beginning with 0x with <HEX>, and decimal integer with <NUM>.

Implement identify_error_patterns(logs, min_occurrences). Return a list of dictionaries for normalized error patterns occurring at least min_occurrences times. Each dictionary must contain pattern and count. Sort results by decreasing count, then by pattern in lexicographic order.

Constraints

1 <= len(logs) <= 10^5
Each log line is valid and contains a non-empty message
Timestamps contain no spaces
1 <= min_occurrences <= len(logs)
UUIDs use the standard hexadecimal format
Numeric values are non-negative decimal integers

Function Signature

def identify_error_patterns(logs, min_occurrences):

Your question is Log Parsing for Error Patterns. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Constraints

1 <= len(logs) <= 10^5
Each log line is valid and contains a non-empty message
Timestamps contain no spaces
1 <= min_occurrences <= len(logs)
UUIDs use the standard hexadecimal format
Numeric values are non-negative decimal integers

Function Signature

def identify_error_patterns(logs, min_occurrences):

Your question is Log Parsing for Error Patterns. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.