Configure Online Archive¶

Navigate to the Database Deployments 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 Database Deployments page is not already displayed, click Databases in the sidebar.

Navigate to the Online Archive tab for your cluster.¶

1. Click the name of the cluster.
2. Click the Online Archive tab to view the list of online archives, if any, for the cluster.

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

   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.

Click Next to specify the most commonly queried fields.¶

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

Enter up to two most commonly queried fields from the collection in the Second most commonly queried field and Third most commonly queried field fields respectively. To specify nested fields, use the dot notation. Do not include quotes ("") around nested fields that you specify using dot notation.

The specified fields are used to partition your archived data. Partitions are similar to folders. The date field is in the first position of the partition by default. You can move another field to the first position of the partition if you frequently query by that field.

The order of fields listed in the path is important in the same way as it is in Compound Indexes. Data in the specified path is partitioned first by the value of the first field, and then by the value of the next field, and so on. Atlas supports queries on the specified fields using the partitions.

For example, suppose you are configuring the online archive for the movies collection in the sample_mflix database. If your archived field is the released date field, which you moved to the third position, your first queried field is title, and your second queried field is plot, your partition will look similar to the following:

/title/plot/released

Atlas creates partitions first for the title field, followed by the plot field, and then the released field. Atlas uses the partitions for queries on the following fields:

• the title field,
• the title field and the plot field,
• the title field and the plot field and the released field.

Atlas can also use the partitions to support a query on the title and released fields. However, in this case, Atlas would not be as efficient in supporting the query as it would be if the query were on the title and plot fields only. Partitions are parsed in order; if a query omits a particular partition, Atlas is less efficient in making use of any partitions that follow that. Since a query on title and released omits plot, Atlas uses the title partition more efficiently than the released partition to support this query.

Atlas can't use the partitions to support queries on fields not specified here. Also, Atlas can't use the partitions to support queries that include the following fields without the title field:

• the plot field,
• the released field, or
• the plot and released fields.

The value of a partition field can be up to a maximum of 700 characters. Documents with values exceeding 700 characters are not archived.

• 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 query fields that do not have a large number of possible values unless you always use those fields in your queries. Query fields, such as _id, with possibly large number of values can cause operations such as count to open all partitions resulting in high latency.
• 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
• int
• long
• objectId
• string

• uuid

  Note

  Partition fields of type UUID must be of binary subtype 4. Atlas skips partition fields of type UUID with subtype 3.

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 Data Lake, see Data Structure in S3.

Click Next to verify and confirm the online archive settings.¶

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.