Configure Online Archive

In Atlas, go to the Clusters page for your project.

1. If it is not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.

2. If it is not already displayed, select your desired project from the Projects menu in the navigation bar.

3. If the Clusters page is not already displayed, click Database in the sidebar.

Go to the Online Archive page for your cluster.

1. Click your cluster's name.

2. Click the Online Archive tab.

Start configuring online archive for your collection.

To configure an online archive for your collection, click:

• Configure Online Archive button the first time.

• Add Archive button subsequently.

Review the Online Archive Overview and click Next to proceed.

Create an Archiving Rule by providing the following information.

1. Specify the collection namespace, which includes the database name, the dot (.) separator, and the collection name (that is, <database>.<collection>), in the Namespace field.

   You can't modify the namespace once the online archive is created.

2. Select the cloud provider region where you want to store your archived data.

   Tip

   We recommend that you select the same region as your cluster if possible because you might incur higher data transfer cost if you choose a different region.

   Atlas displays the cloud provider regions based on the cloud provider where your cluster is deployed. For multi-cloud clusters, Atlas displays the cloud provider regions of the highest priority provider. Atlas displays a next to the region that closely or exactly matches the region where your cluster is deployed.

   AWS

   Azure

   GCP

   For Atlas clusters deployed on AWS, you can select one of the following regions:

   Data Federation Regions	AWS Regions
   Virginia, USA	us-east-1
   Oregon, USA	us-west-2
   Sao Paulo, Brazil	sa-east-1
   Ireland	eu-west-1
   London, England	eu-west-2
   Frankfurt, Germany	eu-central-1
   Tokyo, Japan	ap-northeast-1
   Mumbai, India	ap-south-1
   Singapore	ap-southeast-1
   Sydney, Australia	ap-southeast-2
   Montreal, Canada	ca-central-1

   For Atlas clusters deployed on Azure, you can select an Azure region only if there are no other Online Archives on the cluster that are using AWS. If an existing Online Archive on the cluster uses AWS for storing archived data, you can only select AWS regions for any new Online Archives on that cluster.

   Note

   For a cluster deployed on Azure, if you have existing Online Archives that use AWS and you delete them, you must wait five days before you can create a new Online Archive that uses Azure. Within this five-day period, any attempts to create a new Online Archive still default to AWS.

   For Atlas clusters deployed on Azure, you can select one of the following regions:

   Data Federation Regions	Azure Regions
   Virginia, USA	US_EAST_2
   Netherlands	EUROPE_WEST

   For Atlas clusters deployed on Google Cloud, you can select any supported AWS region.

   Data Federation Regions	AWS Regions
   Virginia, USA	us-east-1
   Oregon, USA	us-west-2
   Sao Paulo, Brazil	sa-east-1
   Ireland	eu-west-1
   London, England	eu-west-2
   Frankfurt, Germany	eu-central-1
   Tokyo, Japan	ap-northeast-1
   Mumbai, India	ap-south-1
   Singapore	ap-southeast-1
   Sydney, Australia	ap-southeast-2
   Montreal, Canada	ca-central-1

   Note

   Once Atlas creates the online archive, you can't modify the storage region.

3. Specify the criteria for selecting documents to archive for the type of collection you want to archive.

   Standard Collection

   Time-Series Collection

   For a standard collection, specify the criteria for selecting documents to archive under the Date Match or Custom Criteria tab in the Atlas User Interface.

   Date Match

   Custom Criteria

   To select documents from the collection using a combination of a date field and number of days:

   • Specify an already indexed date field from the documents in the collection. To specify a nested field, use the dot notation.

   • Specify the number of days to keep the data in the Atlas cluster.

   • Choose the date format of the specified date field.

     If you choose any of the following formats, the value of specified date field must be the BSON type long:

     • EPOCH_SECONDS

     • EPOCH_MILLIS

     • EPOCH_NANOSECONDS

     Important

     You can't modify the date field once the online archive is created.

   To select documents from the collection using a custom filter, specify a valid JSON filter to run. Atlas uses the specified custom filter with the db.collection.find(filter) command. You can't use the empty document argument ({}) to return all documents. You can use MongoDB Atlas operators such as $expr to take advantage of all of the aggregation operators as shown in the following examples.

   Note

   The following examples assume that all documents include bucket_end_date fields with datetime values. In the following examples, Atlas archives all documents that don't include a bucket_end_date field and all documents where the bucket_end_date is not a datetime value.

   Example

   In this custom filter example, when the current date exceeds the date in the bucket_end_date field in the documents, Atlas subtracts thirty days (specified in milliseconds) from the current date and then archives data after that many days, hours, and minutes.

   {
     "$expr": { "$lte": [
       "$bucket_end_date",
       { "$subtract": [ "$$NOW", 2592000000 ] }
     ] }
   }

   In this custom filter example, when the current date exceeds the date inside an objectId, Atlas subtracts thirty days (specified in milliseconds) from the current date and then archives data after that many days, hours, and minutes.

   {
     "$expr": {
       "$lte": [
         {"$toDate": "$_id"},
         { "$subtract": [ "$$NOW", 2592000000 ] }
       ]
     }
   }

   If you use $expr in the custom filter, sometimes the Atlas cluster might be unable to use an index for archiving data.

   Note

   $NOW is only supported on Atlas clusters running MongoDB 4.2 or later.

   Important

   Online Archive for timeseries collection is available as a Preview. The feature and corresponding documentation might change at any time in the Preview stage.

   Online Archive for timeseries collection isn't available for Atlas clusters deployed on Azure and Google Cloud.

   To archive documents in a time series collection, select the This is a Time-Series Collection checkbox and specify the following:

   • Name of the field which contains the date in each time series document. This must correspond to the timeField in the time series collection. To specify a nested field, use the dot notation. You can't modify the time field once the online archive is created.

   • Number of days to keep the data in the Atlas cluster.

   • Date format of the specified date field. The date field value must be in ISODate format.

   Note

   Atlas runs an index sufficiency query to determine the efficiency of the archival process. If the number of documents scanned to the number of documents returned is 10 or more, the query result triggers an Index Sufficiency Warning. This warning indicates that you have insufficient indexes for an efficient archival process. For date-based archives, you must index the date field. For custom criteria that use an expression, Atlas might first convert a value before it evaluates it against the query.

Specify how many days you want to store data in the online archive and a time window when you want Atlas to run the archiving job.

1. (Optional) Specify a Deletion Age Limit.

   By default, Atlas doesn't delete archived data. However, if you specify the Deletion Age Limit, you can specify between 7 to 9125 days (25 years) to keep archived data. Atlas deletes archived data after the number of days you specify here. This data expiration rule takes effect 24 hours after you set the Deletion Age Limit.

   Warning

   Once Atlas deletes the data, you can't recover the data.

2. (Optional) Specify a Schedule Archiving Window.

   By default, Atlas periodically runs a query to archive data. However, you can toggle the Schedule Archiving Window to explicitly schedule the time window during which you want Atlas to archive data. You can specify the following:

   • Frequency. You can choose to run the job every day, on a specific day of the week, or on a specific date every month. If you wish to schedule the data archiving job on the 29th, 30th, or 31st of every month, Atlas doesn't run the archiving job for months without these dates (for example, February).

   • Time window, in hours. Select the period of time during which you want Atlas to run the data archiving job. You must specify a minimum of two hours. If a running job doesn't complete during the specified time window, Atlas continues to run the job until it completes.

Click Next to specify the most commonly queried fields.

Specify the two most frequently queried fields in your collection to create partitions in your online archive.

/title/plot/released

/genres/title

/title/plot/released

• Choose fields that contain only characters supported on AWS. To learn more about the characters to avoid, see Creating object key names. Atlas skips and doesn't archive documents that contain unsupported characters.

• Choose fields that do not contain polymorphic data. Atlas determines the data type of a partition field by sampling 10 documents from the collection. Atlas will not archive a document if the specified field value in a document does not match values in other documents in the same collection.

• Choose fields that you query frequently and order them from the most frequently queried in the first position to the least queried field in the last position. For example, if you frequently query on the date field, then leave the date field in the first position. But if you frequently query on another field, then that field should be in the first position.

Atlas supports the following partition attribute types:

• date

• double

• int

• long

• objectId

• string

• boolean

To learn more about the supported partition attribute types, see Partition Attribute Types.

While partitions improve query performance, queries that don't contain these fields require a full collection scan of all archived documents, which will take longer and increase your costs. To learn more about how partitions improve your query performance in Atlas Data Federation, see Data Structure in S3.

Click Next to review and confirm the online archive settings. You can review the following archiving rule settings:

• The name of the database and collection

• The name of the cloud provider and the cloud provider region

• The name of the date field (for Date Match only)

• The number of days to keep data on the Atlas cluster (for Date Match only)

• The number of days after which to delete archived data

• The frequency and time window for archiving data

• The custom query to use to identify data to archive (for Custom Criteria only)

• The partition fields

Click Back to edit these settings if needed.

Copy and run the displayed query in your mongosh shell to see the documents that match the criteria in the rule you defined in step 5. You can run explain on the query to check whether it uses an index. Proceed to the next step to create the index if the fields are not indexed. If the fields are already indexed, skip to step 11.

(Optional) Copy and run the displayed query in your mongosh to create the required index. This ensures that your data is indexed for optimal performance.

Verify and confirm your archiving rule.

1. Click Begin Archiving in the Confirm an online archive tab.

2. Click Confirm in the Begin Archiving window.