The Concept of Pipelines

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From the course by MongoDB Inc.

MongoDB Aggregation Framework

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MongoDB Inc.

MongoDB Aggregation Framework

11 ratings

This course will teach you how to perform data analysis using MongoDB's powerful Aggregation Framework. You'll begin this course by building a foundation of essential aggregation knowledge. By understanding these features of the Aggregation Framework you will learn how to ask complex questions of your data. This will lay the groundwork for the remainder of the course where you'll dive deep and learn about schema design, relational data migrations, and machine learning with MongoDB. By the end of this course you'll understand how to best use MongoDB and its Aggregation Framework in your own data science workflow.

From the lesson

The Fundamentals of MongoDB Aggregation

In this module you'll learn the fundamentals of MongoDB's Aggregation Framework. This will cover basics like filtering and sorting, as well as how to transform array data, how to group documents together, how to join data, and how to traverse graph data.

Course Logistics and Prerequisites2:07

Aggregation Introduction4:20

The Concept of Pipelines2:04

Aggregation Structure and Syntax3:48

$match: Filtering Documents3:21

Using $project5:58

Using Expressions3:14

Cursor Like Methods Stages: Part 15:03

Cursor Like Methods Stages: Part 25:15

The $group Stage5:56

Using Accumulator Expressions5:14

The $lookup Stage4:25

$graphLookup Stage6:21

Meet the Instructors

Nathan Leniz
Curriculum Engineer
Education
Kirby Kohlmorgen
Senior Curriculum Engineer
Education

Pipelines. You heard us mention pipelines quite a bit throughout the course,

so let's take a few minutes to discuss what they are.

Pipelines can be thought of as a conveyor belt in a factory.

Along the line, there are different assembly stations.

These assembly stations are stages.

Depending on what we want to accomplish,

we may have only one stage,

or we may have many stages.

Pipelines work like this.

Documents represented by these squares

enter our pipeline and begin to flow into our first stage.

This stage is called match which we'll be introduced to you very soon.

We set this stage up so that only red and blue squares make it through.

Next, they flow through our pipeline and enter the second stage.

In this example, we'll call this stage project.

We set the stage up to transform our squares into circles.

This is a small representation of the power of the aggregation framework offers.

We can transform our data in almost any way we desire.

We'll be covering project stage in great detail in later lessons.

This stage represents one of the many powerful analysis stages available,

and it is called group.

Here, we have configured the stage to gather all of the documents that are flowing into

it and produce a single document that gives us the ratio of red to blue circles.

We'll cover group in many other powerful data analysis stages later in the course.

There you have it, a high-level overview of what pipelines are.

At the most basic level,

there are a composition of stages from one to

many that we can arrange and configure in almost any way we like.

The aggregation framework drives

many stages to allow us to filter and transform our data.

All we have to do is compose the pipeline.

Some key takeaways to remember.

Pipelines are a composition of stages.

Stages are configurable to produce desired transformations.

Documents flow through stages like parts in an assembly line or water through a pipe.

Finally, with only a few exceptions which we'll cover later,

stages can be arranged in any way we like and as many as we require.

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