Had onsite for Software Engineer II on a team within Marketplace organization. Technical questions were very fair (id say medium difficulty) and used common DSA (not any esoteric stuff).

Question 1: Ad Event ingestion

You are given a class called AdEvent, which contains attributes of uuid (id for ad), timestamp (represented in YYYY-MM-DD format), but you can make it some integer value for easier testing, and event_type (either impression or click).

Write the following functions:

• consume_ad_event(ad_event): Take in an ad event and consume it
• get_historical_metrics(id): Given an ad id, return an output that looks like the following (note that the 1, 2, 3 in the test example are timestamp)

1: impressions - 5, clicks - 5
2: impressions - 10, clicks - 2
3: impressions - 15, clicks - 20, 
....

• has_low_performance(id, timestamp): Given an ad id along with a timestamp, identify if there were at least X impressions without any click in the last Y days. This signifies that an ad is receiving views, but no conversion! X and Y are hardcoded constants.

Follow Ups

• Suppose we store ad log events for 10 million days for each ad. What would the size of the data be? How would you handle the data volume/cost concern?
• Suppose we have a big company that makes advertisement in US, CA, JP, etc. How would you structure the backend database to support querying the performance metric by each country.

Question 2: Evaluator

You are given the following input:

• equations: an array with entry of format [ai, bi]. ai, bi are variables
• values: an array where values[i] = ai / bi
• queries: a list of lists represented in similar way to equations

For each query, compute the result. If unable to, return -1. return a list of the results of the queries

Note that this question is apparently this problem on leetcode: https://leetcode.com/problems/evaluate-division/description/

Follow Ups

• What if you had 10 million queries to this service. What design choices would you make to speed up the search