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json_delta's Issues

Parallel parking

Hello,

Somewhere down the line, this service is deployed/delivered via several machines and has a considerable load. It will also need to have its persistence somewhere else. Because of some reasons that you cannot control, you start receiving duplicate requests for the same data. For example:

// request 1
{
  "_id": 1,
  "transactionId": "tx1",
  "name": "Bruce Willis",
  "address": {
    "street": "Nakatomi Plaza"
  }
}

// request 2
{
  "_id": 1,
  "transactionId": "tx1",
  "name": "Bruce Willis",
  "address": {
    "street": "Nakatomi Plaza"
  }

The systems that send these requests, also started sending a transactionId that allows you to detect they are duplicate. For some more reasons, it's very problematic business wise to store duplicate data. You can only store one, even if you receive may. And all those many requests can be delivered at exactly the same time.

Can you elaborate on an approach to this?

Different databases per environment

Imagine that for some reason you team decide to have different databases per environment. For example, memory db for tests mode and postgres for dev, staging and production. How would you improve your solution to be better prepared for this change? What would be your approach?

Filter by date

Hello,

Thanks for making our challenge! It's always interesting to see new approaches to the problem and to learn from it. :)

Now the team will leave some questions and provide some feedback. Here is my first one. To filter by the dates, you do:

return _.filter(elements, function(item) {
    return item._timestamp >= startDate && item._timestamp < endDate
})

Imagine that elements is a very huge collection. How could you replace this loop for something faster?

What are the implications of having a CPU heavy operation like that on a request? What would happen to the server?

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