Deploy a Data Lake for an HTTP Data Store¶
This page describes how to deploy a Data Lake for accessing data in an HTTP data store.
The support for HTTP data stores is available as a Beta feature. The feature and the corresponding documentation may change at any time during the Beta stage.
Before you begin, you will need to:
- Create a MongoDB Atlas account, if you do not have one already.
Format your data store using one of the supported data formats.Note
If your file format is
TSV, you must include a header row in your data. See Comma-Separated and Tab-Separated Value Data Files for more information.
- Make your data store accessible over the public internet.
- If your HTTP data store is not accessible over HTTPS, you must
use the JSON Editor to configure your data store.
In your JSON configuration, you must set the
- Atlas Data Lake does not support HTTP data store URLs that require authentication.
Select the Data Lake option on the left-hand navigation.¶
Create a Data Lake.¶
- For your first Data Lake, click Create a Data Lake.
- For your subsequent Data Lakes, click Configure a New Data Lake.
Select the configuration method.¶
- For a guided experience, click Visual Editor.
- To edit the raw JSON, click JSON Editor.
Specify your data store.¶
Create the virtual databases, collections, and views and map the databases, collections, and views to your data store.¶
(Optional) Click the for the:
- Data Lake to specify a name for your Data Lake.
Database to edit the database name. Defaults to
databases.[n].nameJSON configuration setting.
Collection to edit the collection name. Defaults to
databases.[n].collections.nameJSON configuration setting.
- View to edit the view name.
You can click:
- Create Database to add databases and collections.
- associated with the database to add collections to the database.
associated with the collection to add views on the collection. To create a view, you must specify:
- The name of the view.
The pipeline to apply to the view.Note
The view definition pipeline cannot include the
$mergestage. If the view definition includes nested pipeline stages such as
$facet, this restriction applies to those nested pipelines as well.
To learn more about views, see:
- associated with the database, collection, or view to remove it.
- Data Lake to specify a name for your Data Lake. Defaults to
Drag and drop the data store to map with the collection.
databases.[n].collections.[n].dataSourcesJSON configuration setting.