Did you know that MongoDB Atlas provides a complete set of example datato help you learn faster? The Load Sample Datafeature enables you to load eight datasets into your database toexplore. You can use this with the MongoDB Atlas M0 'free tier' to tryout MongoDB Atlas and MongoDB's features. The sample data helps you tryout features such as indexing, querying including geospatial, and aggregations, aswell as using MongoDB Tooling such as MongoDB Charts and MongoDB Compass.
Then why not download the test or demo file completely free. Download demo.csv files starting from 10 rows up to almost half a million rows. Select the one that goes well with your requirements. You can even find options dealing with.csv files that can store records, data or values with 100, 1000, 5000, 10000, 50000, and 100000 rows. Download Sample Csv File For Testing.Csv Flies. Rentals Details: Sample employee CSV file download. The employee CSV can be downloaded in CSV format. The employee statistics file contains a little over 100 to 20,000 rows of data that is helpful in performance testing your web app. Here you public datasets csv › Verified 6 days ago.
In the rest of this post, we'll explore why it was created, how to first loadthe sample data, and then we'll outline what the datasets contain. We'll also coverhow you can download these datasets to use them on your own local machine.
#Table of Contents
#Why Did We Create This Sample Data Set ?
Before diving into how we load the sample data, it's worth highlightingwhy we built the feature in the first place. We built this featurebecause often people would create a new empty Atlas cluster and they'dthen have to wait until they wrote their application or imported datainto it before they were able to learn and explore the platform. Atlas'sSample Data was the solution. It removes this roadblock and quicklyallows you to get a feel for how MongoDB works with different types ofdata.
#Loading The Sample Data Set Into Your Atlas Cluster
Loading the Sample Data requires an existing Atlas cluster andthree steps.
- In your left navigation pane in Atlas, click Clusters, thenchoose which cluster you want to load the data into.
- For that cluster, click the Ellipsis (...) button.
- Click the correspondingly named button, 'Load Sample Dataset.'
This process will take a few minutes to complete, so let's look at exactlywhat kind of data we're going to load. Once the process is completed, youshould see a banner on your Atlas Cluster similar to this image below.
#A deeper dive into the Atlas Sample Data
The Atlas Sample Datasets are comprised of eight databases and their associated collections.Each individual dataset is documented to illustrate the schema, the collections, theindexes, and a sample document from each collection.
#Sample AirBnB Listings Dataset
This dataset consists of a single collection of AirBnB reviews and listings.There are indexes on the
name, and on the
location fields as well as on the
_id of thedocuments.
The data is a randomized subset of the original publicly availableAirBnB dataset. It covers several different cities around the world. Thisdataset is used extensively in MongoDB University courses.
You can find more details on the Sample AirBnB Documentation page.
#Sample Analytics Dataset
This dataset consists of three collections of randomly generated financialservices data. There are no additional indexes beyond the
_id index oneach collection. The collections represent accounts, transactions, andcustomers.
The transactions collection uses the Bucket Patternto hold a set of transactions for a period. It was built for MongoDB's private training,specifically for the MongoDB for Data Analysis course.
The advantages in using this pattern are a reduction in index size whencompared to storing each transaction in a single document. It canpotentially simplify queries and it provides the ability to usepre-aggregated data in our documents.
You can find more details on the Sample Analytics Documentation page.
#Sample Geospatial Dataset
This dataset consists of a single collection with information on shipwrecks.It has an additional index on the
coordinates field (GeoJSON). Thisindex is a Geospatial 2dsphere index. This dataset was created to helpexplore the possibility of geospatial queries within MongoDB.
The image below was created in MongoDB Chartsand shows all of the shipwrecks on the eastern seaboard of North America.
You can find more details on the Sample Geospatial Documentation page.
#Sample Mflix Dataset
This dataset consists of five collections with information on movies,movie theatres, movie metadata, and user movie reviews and their ratingsfor specific movies. The data is a subset of the IMDB dataset. There arethree additional indexes beyond
_id: on the sessions collection on the
user_id field, on the theatres collection on the
location.geo field,and on the users collection on the
The Atlas Search Movies site usesthis data and MongoDB's Atlas Searchto provide a searchable movie catalog.
This dataset is the basis of our Atlas Search tutorial.
You can find more details on the Sample Mflix Documentation page.
#Sample Restaurants Dataset
This dataset consists of two collections with information on restaurants andneighbourhoods in New York. There are no additional indexes. This dataset isthe basis of our Geospatial tutorial.The restaurant document only contains the location and the name for a givenrestaurant.
In order to use the collections for geographical searching, we need to add anindex, specifically a 2dsphere index.We can add this index and then search for all restaurants in a one-kilometerradius of a given location, with the results being sorted by those closest tothose furthest away. The code below creates the index, then adds ahelper variable to represent 1km, which our query then uses with the$nearSpherecriteria to return the list of restaurants within 1km of that location.
You can find more details on the Sample Restaurants Documentation page.
#Sample Supply Store Dataset
This dataset consists of a single collection with information on mock salesdata for a hypothetical office supplies company. There are no additionalindexes. This is the second dataset used in the MongoDB Chart tutorials.
The sales collection uses the Extended Reference patternto hold both the items sold and their details as well as information on thecustomer who purchased these items. This pattern includes frequently accessedfields in the main document to improve performance at the cost of additionaldata duplication.
You can find more details on the Sample Supply Store Documentation page.
#Sample Training Dataset
This dataset consists of nine collections with no additional indexes. Itrepresents a selection of realistic data and is used in the MongoDB private training courses.
It includes a number of public, well-known data sources such as theOpenFlights,NYC's OpenData,and NYC's Citibike Data.
Csv Sample Data Sets
The routes collection uses the Extended Reference patternto hold OpenFlights data on airlineroutes between airports. It references airline information in the
airlinesub document, which has details about the specific plane on the route. Thisis another example of improving performance at the cost of minor dataduplication for fields that are likely to be frequently accessed.
You can find more details on the Sample Training Documentation page.
#Sample Weather Dataset
This dataset consists of a single collection with no additional indexes. Itrepresents detailed weather reports from locations across the world. Itholds geospatial data on the locations in the form of legacy coordinate pairs.
You can find more details on the Sample Weather Documentation page.
Datasets Csv Files Download
If you have ideas or suggestions for new datasets, we are always interested.Let us know on the developer community website.
#Downloading the Dataset for Use on Your Local Machine
It is also possible to download and explore these datasets on your own localmachine. You can download the complete sample dataset via the wget command:
Note: You can also use the curl command:
You should check you are running a local
mongod instance or you shouldstart a new
mongod instance at this point. This
mongod will be usedin conjunction with
mongorestore to unpack and host a local copy of thesample dataset. You can find more details on starting mongod instances onthis documentation page.
This section assumes that you're connecting to a relativelystraightforward setup, with a default authentication database and someauthentication set up.(You should alwayscreate some usersfor authentication!)
If you don't provide any connection details to
mongorestore, it willattempt to connect to MongoDB on your local machine, on port 27017(which is MongoDB's default). This is the same as providing
You can use a variety of tools to view your documents. You can use MongoDBCompass,the CLI,or the MongoDB Visual Studio Code (VSCode) pluginto interact with the documents in your collections. You can find out howto use MongoDB Playground for VSCodeand integrate MongoDB into a Visual Studio Code environment.
If you find the sample data useful for building or helpful, let us know onthe community forums!
See Full List On Sample-videos.com
These datasets offer a wide selection of data that you can use to bothexplore MongoDB's features and prototype your next project without havingto worry about where you'll find the data.
Check out the documentation on Load Sample Datato learn more on these datasets and load it into your Atlas Clustertoday to start exploring it!
Nerdpdt.peachycollection.co › Sample-csv-file-freeSample Csv File Free Download - Nerdpdt.peachycollection.co
To learn more about schema patterns and MongoDB, please check out ourblog series Building with Patternsand the free MongoDB University Course M320: Data Modelingto level up your schema design skills.
If you have questions, please head to our developer community website where the MongoDB engineers and the MongoDB community will help you build your next big idea with MongoDB.