Aggregation Editor

Basics

There are three ways to open Aggregation Editor:

Aggregation Editor has two main sections: the Pipeline Editor and the Result Tab.

Pipeline Editor

The Pipeline Editor is where the aggregation query is edited (e.g. stages are added, operators are chosen).

It has three main tabs:

Result Tab

The Result tab displays the aggregation query results in either Table, Tree, or JSON view. It is part of the greater Collections Tab.

The other tabs Query Code and Explain will be covered later in the tutorial.

Build a MongoDB aggregation query

The dataset Customers will be used in this tutorial to illustrate the feature’s capabilities. Download it here.

Add a new stage

All aggregation queries start with a question that needs to be answered, which in this tutorial is:

Which city has the highest number of pet manatees?

A stage operator defines what the stage actually does. Looking at the Customers data set, a $match operator needs to be applied to find all customers who own a pet manatee.

The $match operator acts as a filter that takes the input set of documents and outputs only those that match the given criteria.

To add a new stage:

This will generate a stage in the Pipeline tab and a Stage tab right next to it.

Edit a stage

Now that Stage 1 has been created, it’s ready to be edited.

To edit a stage:

Choose the desired stage operator from the drop-down menu, which in this case is $match.

State the query, which in this example is:

{
"pet" : "manatee"
}

Check the input of a stage

To double-check the input of a stage, which in the example is the precise set of documents that were scanned for a value match “manatee” for the field “pet”:

A quick click on Count Documents shows that 1001 documents were scanned, which is exactly the starting amount of documents in the Customers collection.

Check the output of a stage

To show the output of a stage:

The ability to show the output makes it easier to double-check that results are accurate (e.g. no customers should appear who own a pet cat), before they’re carried over as the input of a later stage.

The Count Documents feature can again be used to check for a smaller result count.

Add a stage before or after a selected stage

It is also possible to place an additional stage before or after any selected stage:

The current output only contains customers with a pet manatee. As a next step, the results can be grouped by city in a second stage using the $group operator and the query:

{
_id:"$address.city", totalPets: { $sum: "$number_pets"}
}

Which gives us the following results, not sorted in any order:

As a third and final stage, a $sort operator can be applied to sort the results in descending order:

{
totalPets: -1
}

Move a stage

Choose the stage to be moved in the Pipeline tab or its corresponding Stage tab and:

Enable or disable a stage

To temporarily enable or disable stages from your pipeline, check or uncheck the Include in pipeline checkbox as needed:

Delete a stage

Choose the stage to be deleted in the Pipeline tab or its corresponding Stage tab and:

Execute full pipeline

Now that the aggregation query is complete and all stages ($match, $group, and $sort) are in the correct order, the full pipeline can be executed:

Check query results

The Result Tab displays the query results which can be edited in-place, and can be viewed in either Table, Tree, or JSON view. Find the full documentation here.

The aggregation query then helps us to answer our initial question:

It looks like Berlin has the highest number of pet manatees, with 99 living across the German capital.

View multiple result tabs

The Result Tab can show either one tab, meaning results from previous queries aren’t kept, or multiple tabs, which is similar to how a browser works.

Click on the Retain button in the toolbar to trigger multiple tabs. Unclick it to stick with one tab.

Clear all result tabs

To close all result tabs:

Generate JavaScript, Java, Python, and C# code from aggregation queries

Query Code is a feature available in Studio 3T that translates aggregation queries to JavaScript (Node.js), Java (2.x and 3.x driver API), Python, C#, and the mongo shell language.

To view a MongoDB aggregation query’s equivalent code:

1. Execute the aggregation query
2. Click on the Query Code tab
3. Choose the target language

Read about Query Code in full here.

View the full MongoDB aggregation query

To see the full MongoDB aggregation query instead of viewing them line-by-line as stages:

1. Click on the Query Code tab
2. Choose mongo shell

Explain the full pipeline

The Explain Tab is part of the greater Collection Tab (full documentation here), which shows information on query plans and execution statistics of said query plans.

Explain results can also be accessed by clicking on the Explain (lightbulb) button in the toolbar.

Open and save aggregation queries

To save your aggregation query as a JavaScript file:

Copy and paste aggregation queries

The copy and paste function is extremely helpful, especially when working in between Studio 3T features (for example, going from SQL Query to the View Editor).

To copy an aggregation query:

To paste an aggregation query:

Specify query options

The Options tab is where disk use and custom collation settings can be set.

Allow disk use

Allow Disk Use enables writing to temporary files, which will then allow aggregation operations to write data to the _tmp subdirectory in the dbPath directory.

Custom collation

Customize your queries’ collation, which is the way searching and sorting is performed.

Read more about collation here.

Older Studio 3T versions

In older versions of Studio 3T, query options can be set in the Options tab.

Note that these options only became available in MongoDB 2.6, so on MongoDB 2.4 or an earlier instance, the Options tab is not shown.