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  • Introduction
  • Aggregation Task Summary
  • Before You Get Started
  • Tutorial
  • Add a match stage for people who are engineers
  • Add a sort stage to sort from youngest to oldest
  • Add a limit stage to see only three results
  • Add an unset stage to remove unneeded fields
  • Run the aggregation pipeline
  • Interpret results

Introduction

In this tutorial, you can learn how to use the Node.js driver to construct an aggregation pipeline, perform the aggregation on a collection, and print the results by completing and running a sample app. This aggregation performs the following operations:

  • Matches a subset of documents by a field value

  • Formats result documents

Tip

You can also query for a subset of documents in a collection by using the Query API. To learn how to specify a query, see the Read Operations guides.

Aggregation Task Summary

This tutorial demonstrates how to query a collection for a specific subset of documents in a collection. The results contain documents that describe the three youngest people who are engineers.

This example uses one collection, persons, which contains documents describing people. Each document includes a person's name, date of birth, vocation, and other details.

Before You Get Started

Before you start this tutorial, complete the Aggregation Template App instructions to set up a working Node.js application.

After you set up the app, access the persons collection by adding the following code to the application:

const personColl = await aggDB.collection("persons");

Delete any existing data in the collections and insert sample data into the persons collection as shown in the following code:

await personColl.deleteMany({});
const personData = [
  {
    person_id: "6392529400",
    firstname: "Elise",
    lastname: "Smith",
    dateofbirth: new Date("1972-01-13T09:32:07Z"),
    vocation: "ENGINEER",
    address: {
      number: 5625,
      street: "Tipa Circle",
      city: "Wojzinmoj",
    },
  },
  {
    person_id: "1723338115",
    firstname: "Olive",
    lastname: "Ranieri",
    dateofbirth: new Date("1985-05-12T23:14:30Z"),
    gender: "FEMALE",
    vocation: "ENGINEER",
    address: {
      number: 9303,
      street: "Mele Circle",
      city: "Tobihbo",
    },
  },
  {
    person_id: "8732762874",
    firstname: "Toni",
    lastname: "Jones",
    dateofbirth: new Date("1991-11-23T16:53:56Z"),
    vocation: "POLITICIAN",
    address: {
      number: 1,
      street: "High Street",
      city: "Upper Abbeywoodington",
    },
  },
  {
    person_id: "7363629563",
    firstname: "Bert",
    lastname: "Gooding",
    dateofbirth: new Date("1941-04-07T22:11:52Z"),
    vocation: "FLORIST",
    address: {
      number: 13,
      street: "Upper Bold Road",
      city: "Redringtonville",
    },
  },
  {
    person_id: "1029648329",
    firstname: "Sophie",
    lastname: "Celements",
    dateofbirth: new Date("1959-07-06T17:35:45Z"),
    vocation: "ENGINEER",
    address: {
      number: 5,
      street: "Innings Close",
      city: "Basilbridge",
    },
  },
  {
    person_id: "7363626383",
    firstname: "Carl",
    lastname: "Simmons",
    dateofbirth: new Date("1998-12-26T13:13:55Z"),
    vocation: "ENGINEER",
    address: {
      number: 187,
      street: "Hillside Road",
      city: "Kenningford",
    },
  },
];
await personColl.insertMany(personData);

Tutorial

1

Add a match stage for people who are engineers

First, add a $match stage that finds documents in which the value of the vocation field is "ENGINEER":

pipeline.push({
  $match: {
    "vocation": "ENGINEER"
  },
});
2

Add a sort stage to sort from youngest to oldest

Next, add a $sort stage that sorts the documents in descending order by the dateofbirth field to list the youngest people first:

pipeline.push({
  $sort: {
    "dateofbirth": -1,
  }
});
3

Add a limit stage to see only three results

Next, add a $limit stage to the pipeline to output only the first three documents in the results.

pipeline.push({
  $limit: 3
});
4

Add an unset stage to remove unneeded fields

Finally, add an $unset stage. The $unset stage removes unnecessary fields from the result documents:

pipeline.push({
  $unset: [
    "_id",
    "address",
  ]
});

Tip

Use the $unset operator instead of $project to avoid modifying the aggregation pipeline if documents with different fields are added to the collection.

5

Run the aggregation pipeline

Add the following code to the end of your application to perform the aggregation on the persons collection:

const aggregationResult = await personColl.aggregate(pipeline);

Finally, run the following command in your shell to start your application:

node agg_tutorial.js
6

Interpret results

The aggregated result contains three documents. The documents represent the three youngest people with the vocation of "ENGINEER", ordered from youngest to oldest. The results omit the _id and address fields.

{
  person_id: '7363626383',
  firstname: 'Carl',
  lastname: 'Simmons',
  dateofbirth: 1998-12-26T13:13:55.000Z,
  vocation: 'ENGINEER'
}
{
  person_id: '1723338115',
  firstname: 'Olive',
  lastname: 'Ranieri',
  dateofbirth: 1985-05-12T23:14:30.000Z,
  gender: 'FEMALE',
  vocation: 'ENGINEER'
}
{
  person_id: '6392529400',
  firstname: 'Elise',
  lastname: 'Smith',
  dateofbirth: 1972-01-13T09:32:07.000Z,
  vocation: 'ENGINEER'
}

To view the complete code for this tutorial, see the Completed Filtered Subset App on GitHub.

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