Structure your Data for MongoDB

What You’ll Need¶

An idea of what data you’d like to store

Check Your Environment¶

There are no technical requirements for this guide.

Procedure¶

1

Define Your Data Set¶

When setting up a data store, your first task is to answer the question: “What data would I like to store and how do the fields relate to each other?”.

This guide uses a hypothetical inventory database to track items and their quantities, sizes, tags, and ratings.

Here is an example of the types of fields you might wish to capture:

name	quantity	size	status	tags	rating
journal	25	14x21,cm	A	brown, lined	9
notebook	50	8.5x11,in	A	college-ruled,perforated	8
paper	100	8.5x11,in	D	watercolor	10
planner	75	22.85x30,cm	D	2019	10
postcard	45	10x,cm	D	double-sided,white	2

2

Start Thinking in JSON¶

While a table might seem like a good place to store data, as you can see from the example above, there are fields in this data set that require multiple values and would not be easy to search or display if modeled in a single column (for example – size and tags).

In a SQL database you might solve this problem by creating a relational table.

In MongoDB, data is stored as documents. These documents are stored in MongoDB in JSON (JavaScript Object Notation) format. JSON documents support embedded fields, so related data and lists of data can be stored with the document instead of an external table.

JSON is formatted as name/value pairs. In JSON documents, fieldnames and values are separated by a colon, fieldname and value pairs are separated by commas, and sets of fields are encapsulated in “curly braces” ({}).

If you wanted to begin to model one of the rows above, for example this one:

name	quantity	size	status	tags	rating
notebook	50	8.5x11,in	A	college-ruled,perforated	8

You might start with the name and quantity fields. In JSON these fields would look like:

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{"name": "notebook", "qty": 50}

3

Identify Candidates for Embedded Data and Model Your Data¶

Next you will decide which fields require multiple values. These fields will be candidates for embedded documents or lists/arrays of embedded documents within the document.

For example, in the data above, size might consist of three fields:

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{ "h": 11, "w": 8.5, "uom": "in" }

And some items have multiple ratings, so ratings might be represented as a list of documents containing the field scores:

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[ { "score": 8 }, { "score": 9 } ]

And you might need to handle multiple tags per item. So you might store them in a list too.

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[ "college-ruled", "perforated" ]

Finally, a JSON document that stores an inventory item might look like this:

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{
 "name": "notebook",
 "qty": 50,
 "rating": [ { "score": 8 }, { "score": 9 } ],
 "size": { "height": 11, "width": 8.5, "unit": "in" },
 "status": "A",
 "tags": [ "college-ruled", "perforated"]
}

This looks very different from the tabular data structure you started with in Step 1.

Note

It’s a JSON standard to quote field names.

Summary¶

Congratulations. You now have an idea of how to structure your data using a JSON document.

What’s Next¶

Next you’ll set up a MongoDB instance. Choose one of the following options:

Structure your Data for MongoDB¶

What You’ll Need¶

Check Your Environment¶

Procedure¶

Define Your Data Set¶

Start Thinking in JSON¶

Identify Candidates for Embedded Data and Model Your Data¶

Summary¶

What’s Next¶

See Also¶