Parse and Aggregate Log Errors | Dataford Interview Questions

Adecco One emits application logs in a pipe-delimited format. Given an array of log lines, parse each line, keep only ERROR events from selected services within a half-open time interval, and aggregate the number of occurrences for each error code.

Each valid log line has this format:

timestamp|service|level|error_code|message

The timestamp is an integer, and the message may contain additional pipe characters. Return a dictionary mapping each matching error code to its count. If no lines match, return an empty dictionary.

Formal Specification

Implement aggregate_error_counts(logs, allowed_services, start_time, end_time).

logs is a list of strings.
allowed_services is a list of service names.
start_time is inclusive and end_time is exclusive.
A line matches only when its timestamp is in the interval, its service is allowed, and its level is exactly ERROR.
All input log lines are valid and contain at least five fields.

Constraints

1 <= len(logs) <= 10^5
Each log line contains at least five pipe-delimited fields
0 <= timestamp <= 10^9
1 <= len(error_code) <= 32
The total number of characters across all log lines is at most 10^7

Function Signature

def aggregate_error_counts(logs, allowed_services, start_time, end_time):

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