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So in the last lectures we learn about embedded or nested documents and arrays and this gives you a lot

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of flexibility to structure your data in the way you need it to be structured,

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also something I'll dive into deeper in my data schema and modeling and relations module in this course.

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One thing I want to do before I close or finish this module is I want to show you how you could access

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such structured data

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and let's start with the hobbies here.

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You can of course output that by let's say finding Albert with find and then I'll look for name, Albert

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Twostone, like this,

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now if I pretty print that, here's Albert.

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We can now access .hobbies here because find will give us that person and hobbies should give us

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access to the array here

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then, though one important thing, we should use findOne here

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so that mongodb knows we'll only have one element, so that we can directly access the fields of that

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element after fetching it, 

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so after the closing parentheses.

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With this we indeed get the hobbies output here, sports and cooking and we can even search for that. If we

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want to find all passengers with a hobby of sports, what we can do is we can access hobbies here which

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is an array

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and look for sports and I'd put that in a pretty way

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and here we find Albert too, the entire document not just the sports entry because we're looking for the

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entire passenger documents where hobbies is equal to sports and mongodb is clever enough to see

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that hobbies actually is an array so it will simply look if that array has one element named sports and

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then it gives us the entire document as a result,

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so this is how we can also query such arrays.

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Now how can we query objects?

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Remember we had nested objects, nested documents in our flight data

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so here if I find all, we had the status. Now if we want to find all results with a status description

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of on time, we can use our flight data and find and now in the filter,

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we want to look for the status but the status,

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well we're interested in one of the fields of that nested document. For this, we can use status dot

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and then the nested field,

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so you use dot notation to drill into your embedded document, so .description. Important when using

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that,

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so when having a dot in here, when using such a path to a nested field, you need to wrap the entire

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term with double quotation marks though otherwise it will fail

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and now we can check where is this equal to on time.

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If I now pretty print this, I get both my flights because both have status description of on time, you

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get no error

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instead this query works,

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so we can drill into embedded documents with that dot notation. And obviously we can go one level further

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as far as we need to,

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we can also drill into details.

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So we're looking for our details here and we want to find all flights where details responsible is Max

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Schwarzmuller,

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we can do that too.

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Now I'm drilling into details responsible and I'm looking for Max Schwarzmuller here and I again find

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both flights because both have Max Schwarzmuller as a responsible person.

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So this dot notation is also something you'll see a lot in this course as this is an important syntax

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that allows you to look into embedded documents in your filters.

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And this is it for now,

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we'll dive much deeper into all of that and how to write efficient queries and how to access your data

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and work with it,

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we'll dive into all that throughout the course.

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These are the core things you got to know about how mongodb works, how you could work with it, how

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you can store update, delete and read data and how you can also structure your data.

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Now as I mentioned, we'll have a whole module where I dive into how to optimally or cleverly structure

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your data and how to work with related data

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but this is now a good start.

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Let's practice this before we learn about a different way of looking into your data.