Problem: Sorting logs 🕒 chronologically 🕒 from multiple sources, both in Synchronous and Asynchronous manner. Addressing the problem of storing logs in memory if a source contains millions of entries and can be exabytes in size.

Solution: Use of a min-heap for sorting, reading logs once-at-a-time, and the asynchronous solution, since there’s a “flight time” a buffer is used.

Instructions

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 🕒.

The Objectives:

1. Drain all of the log sources for both the synchronous and asynchronous solutions.
   • Synchronous
   • Asynchronous
2. 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.
3. 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!!!

Pointers & Callouts

• 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.