We have a number of log sources. Each log source contains N log entries. Each entry is a javascript object with a timestamp and message. We don't know the number of log entries each source contains - however - we do know that the entries within each source are sorted 🕒 chronologically 🕒.
- Drain all of the log sources. You should see what this means after digging in.
- Print all of the entries, across all of the sources, in chronological order.
- We don't need to store the log entries, just print them to stdout.
- Do this efficiently. There are time and space complexities afoot!
We expect candidates to spend 1-3 hours on this exercise.
We want to see you flex your CS muscles!!! Use the appropriate data structures to satisfy the time and space complexities inherent to the problem!!!
- We don't know how many logs each source contains. A source could contain millions of entries and be exabytes in size! In other words, reading the entirety of a log source into memory won't work well.
- Log sources could contain logs from last year, from yesterday, even from 100 years ago. We won't know the timeframe of a log source until we start looking.
- Consider what would happen when asked to merge 1 million log sources. Where might bottlenecks arise?
There are two parts of the challenge which you'll see when diving into things. You can get started by running npm start.
Create a GitHub repo and email your point of contact the link.
If - for whatever reason - you cannot create a GitHub repo for this challenge, it is also acceptable to 'zip' the directory and provide your submission as an email attachment.