Using Compass to View Data in an Atlas Cluster

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来自 MongoDB Inc. 的课程

Introduction to MongoDB

75 个评分

MongoDB Inc.

Introduction to MongoDB

75 个评分

This course will get you up and running with MongoDB quickly, and teach you how to leverage its power for data analytics. We'll start by mastering the fundamentals of MongoDB, including MongoDB’s Document data model, importing data into a cluster, working with our CRUD API and Aggregation Framework. These topics will be taught through a demo application which will give you a great first encounter of how simple and practical it can be to build applications with MongoDB. In addition to these essential topics, you will also learn and work with useful MongoDB tools and services. You will work with Atlas, MongoDB's database as a service, MongoDB Compass, a schema visualization tool, as well as many other useful command-line utilities.

从本节课中

Week 1

MongoDB Document Model5:15

Creating an Atlas Free-Tier Cluster4:44

Installing MongoDB on Windows12:10

Installing MongoDB on OSX12:19

Getting Data Into MongoDB4:12

Using Compass to View Data in an Atlas Cluster3:37

Working with Data in MongoDB4:12

How to Connect to Your Atlas Cluster from Python3:21

Intro to the Aggregation Framework3:23

Your First Aggregation (Using $group)7:01

Incremental Improvements with $sort and $sortByCount1:24

Wowza! You can do that? ($facet)8:42

Filtering on Scalar Fields ($match, find(), and Compass)4:52

与讲师见面

Norberto Leite
Lead Engineer
Engineering
Kirby Kohlmorgen
Senior Curriculum Engineer
Education
Shannon Bradshaw
Vice President
Education

Now let's view the data we just loaded.

For this and a number of other tasks in this course,

MongoDB Compass is the best option.

Compass is a GUI client for MongoDB that enables you to view databases,

filter data using queries, modify data as needed and much more.

To download Compass, let's visit the MongoDB Download Center.

I will just Google for it here.

Click the Compass tab, and make sure you select the right distribution for

your operating system.

I'm running on a Mac, so I will download the latest version for OSX.

Once downloaded, go ahead and install compass.

It should launch upon install, but

in case it doesn't, just use Spotlight to launch it.

Compass should launch once installed on Windows, but

in case it doesn't, just click search and type compass.

Once launched, you'll see a connect screen similar to this.

Now, Compass is actively developed, so exactly what you see in the Compass UI

might differ from what it is as I record this video.

To connect to your free tier cluster, visit the cluster page for

your Atlas account.

Click Connect, and click Connect Your Application.

Go ahead and copy the URL connection string, and then go back to Compass.

You should see a model that asks you whether you want to

use the connection string you just copied to connect Compass to MongoDB cluster.

Go there and do this.

Compass will populate nearly all the fields in the connection form.

You just need to type the password for our analytics user.

Remember, that is analytics-password.

Now, all of the details you need to fill in this form

are included in the lecture notes for this lesson.

So don't worry if Compass didn't pop up

the model asking you if you simply wanted to copy in what was in the clipboard.

At the very bottom of the connect form, enter Analytics Free-Tier,

and click Create Favorite, so

that you can easily reconnect to your free-tier atlas cluster at any time.

Now, I'll click Connect, and you'll see that I'm presented with three databases.

The admin and local databases are created by default and

are used by MongoDB for internal bookkeeping.

The database we created when we loaded data set using Mongo import

is called mflix.

Click mflix.

You then see that the mflix database contains one collection

called movies_initial with 46,014 documents in it.

In MongoDB, documents are like Rose in a relational database.

And documents are organized together in collections.

Much in the same way that Rose make up tables in a relational database.

Each document in a collection is a distinct record.

In the movies_initial collection, each document stores data for one movie.

Now click movies_initial.

In the documents view that loads,

you can scroll through the documents in this collection.

Note the fields and basic shape of the documents.

In the coming lessons, we'll be doing some data cleaning and reshaping of the schema

in order to better enable an application and analytics.

For example, note that the genre field is a simple string

containing a comma separated list of genres.

This makes it difficult to partition documents based on the genre.

We'll do something about that in a number of other fields.

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