hubspot oa | HubSpot SDE OA | hubspot new gard oa | 一亩三分地

1,170Views

HubSpot’s online assessment (OA) for internship and new grad roles has recently been making the rounds, and many candidates are curious about whatto expect. The test is designed to evaluate both problem-solving skills and coding fundamentals, often mixing in algorithm challenges, debugging, andscenario-based questions that reflect real-world engineering work.

Problem description:

Responsibility — So, you have to implement a new view of the analytics: sessions. The workload is a data set of individual web page visits, andthis comes with an accompanying visitorId generated by their tracking cookie which identifies each unique user. The purpose is to create a list of sessions for each visitor from that data.

The raw event data is available at REDACTED via the dataset API

The data set looks like this:

  "events": [
    {
      "url": "/pages/a-big-river",
      "visitorId": "d1177368-2310-11e8-9e2a-9b860a0d9039",
      "timestamp": 1512754583000
    },
    {
      "url": "/pages/a-small-dog",
      "visitorId": "d1177368-2310-11e8-9e2a-9b860a0d9039",
      "timestamp": 1512754631000
    },
    {
      "url": "/pages/a-big-talk",
      "visitorId": "f877b96c-9969-4abc-bbe2-54b17d030f8b",
      "timestamp": 1512709065294
    },
    {
      "url": "/pages/a-sad-story",
      "visitorId": "f877b96c-9969-4abc-bbe2-54b17d030f8b",
      "timestamp": 1512711000000
    },
    {
      "url": "/pages/a-big-river",
      "visitorId": "d1177368-2310-11e8-9e2a-9b860a0d9039",
      "timestamp": 1512754436000
    },
    {
      "url": "/pages/a-sad-story",
      "visitorId": "f877b96c-9969-4abc-bbe2-54b17d030f8b",
      "timestamp": 1512709024000
    }
  ]
}

With the input data, we would like to generate sessions from this incoming data. You have the CSV of all your recorded user activity, defining a session as abunch of events from a single visitor with 10 minutes apart between each event. A visitor may have more than one session.

Therefore for the example input data above, we should get something like:

"sessionsByUser": {
  "f877b96c-9969-4abc-bbe2-54b17d030f8b": [
    {
      "duration": 41294,
      "pages": [
        "/pages/a-sad-story",
        "/pages/a-big-talk"
      ],
      "startTime": 1512709024000
    },
    {
      "duration": 0,
      "pages": [
        "/pages/a-sad-story"
      ],
      "startTime": 1512711000000
    }
  ],
  "d1177368-2310-11e8-9e2a-9b860a0d9039": [
    {
      "duration": 195000,
      "pages": [
        "/pages/a-big-river",
        "/pages/a-big-river",
        "/pages/a-small-dog"
      ],
      "startTime": 1512754436000
    }
  ]
}
}

After you get your event data, transform it into sessions and POST the result to REDACTED via HTTP

Approach

Our approach was firstly to:

Map visitorId → list of visits (url, timestamp) in a map.
Fill that map with data from the GET URL.
Sort each visitor’s list by timestamp ascending. Then iterate:
- If current session is empty, start a new one and record startTime.
- Else, check the time gap to the previous event:
  - ≤ 10 minutes: add to current session.
  - > 10 minutes: close current session, start a new one.
Calculate session fields:
- startTime: timestamp of first event.
- duration: lastEventTime − firstEventTime.
- pages: ordered list of URLs in session.
Compile sessions for all users into the final JSON and POST to the API.