Document References May Require $lookups ¶

This approach works especially well if your application loads the book and publisher information separately. If your application requires the book and information together, it needs to perform a $lookup operation to join the data from the publishers and books collections. $lookup operations are not very performant, but in this scenario may be worth the trade off to avoid unbounded arrays.

MongoDB.live 2020 Presentations¶

To learn how to incorporate the flexible data model into your schema, see the following presentations from MongoDB.live 2020 :

• Learn about entity relationships in MongoDB and examples of their implementations with Data Modeling with MongoDB.
• Learn advanced data modeling design patterns you can incorporate into your schema with Advanced Schema Design Patterns.

Activate Backup¶

1. From your Context menu, click the project that has the hosts you want to configure.

2. Click Deployments .

3. Click Servers .

4. On the host where you want to activate Backup, click ellipsis icon .

5. Click Activate Backup .

6. From the banner, click Review & Deploy .

7. If you want to activate Backup, click Confirm & Deploy . Otherwise click Cancel , then Discard Changes to cancel activating Backup.

   Note

   Only one host can backup a deployment at a time. On the Server tab, the host that is backing up the deployment displays Backup - active . Any other host with Backup activated displays Backup - standby .

Deactivate Backup¶

1. From your Context menu, click the project that has the hosts you want to configure.
2. Click Deployments .
3. Click Servers .
4. On the host where you want to deactivate Backup, click ellipsis icon .
5. Click Deactivate Backup .
6. From the banner, click Review & Deploy .
7. If you want to activate Backup, click Confirm & Deploy . Otherwise click Cancel , then Discard Changes to cancel deactivating Backup.

Activate Monitoring¶

1. From your Context menu, click the project that has the hosts you want to configure.

2. Click Deployments .

3. Click Servers .

4. On the host where you want to activate Monitoring, click ellipsis icon .

5. Click Activate Monitoring .

6. From the banner, click Review & Deploy .

7. If you want to activate Monitoring, click Confirm & Deploy . Otherwise click Cancel , then Discard Changes to cancel activating Monitoring.

   Note

   Only one host can monitor a deployment at a time. On the Server tab, the host that is monitoring the deployment displays Monitoring - active . Any other host with Monitoring activated displays Monitoring - standby .

Deactivate Monitoring¶

1. From your Context menu, click the project that has the hosts you want to configure.
2. Click Deployments .
3. Click Servers .
4. On the host where you want to deactivate Monitoring, click ellipsis icon .
5. Click Deactivate Monitoring .
6. From the banner, click Review & Deploy .
7. If you want to deactivate Monitoring, click Confirm & Deploy . Otherwise click Cancel , then Discard Changes to cancel activating Monitoring.

Activate Automation¶

Automation is activated when you:

• Deploy a standalone MongoDB instance
• Deploy a replica set
• Deploy a sharded cluster
• Import an existing MongoDB deployment into Cloud Manager.

Collation¶

Use collation to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.

To specify a collation document, click Collation at the top of the pipeline builder.

A collation document has the following fields:

{
   locale: <string>,
   caseLevel: <boolean>,
   caseFirst: <string>,
   strength: <int>,
   numericOrdering: <boolean>,
   alternate: <string>,
   maxVariable: <string>,
   backwards: <boolean>
}

The locale field is mandatory; all other collation fields are optional. For descriptions of the fields, see Collation Document.

Import an Aggregation Pipeline from Text¶

You can import aggregation pipelines from plain text into the pipeline builder to easily modify and verify your pipelines.

To import a pipeline from plain text:

Reset Your Pipeline¶

To return your pipeline to the initial blank state, click the plus icon at the top of the pipeline builder.

Request Path Parameters¶

Request Query Parameters¶

The following query parameters are optional:

Request Body Parameters¶

This endpoint doesn’t use HTTP request body parameters.

Response Document¶

The response JSON document includes an array of result objects, an array of link objects and a count of the total number of result objects retrieved.

results Embedded Document¶

Each result is one project.

Response Header¶

HTTP/1.1 401 Unauthorized
Content-Type: application/json;charset=ISO-8859-1
Date: {dateInUnixFormat}
WWW-Authenticate: Digest realm="MMS Public API", domain="", nonce="{nonce}", algorithm=MD5, op="auth", stale=false
Content-Length: {requestLengthInBytes}
Connection: keep-alive

HTTP/1.1 200 OK
Vary: Accept-Encoding
Content-Type: application/json
Strict-Transport-Security: max-age=300
Date: {dateInUnixFormat}
Connection: keep-alive
Content-Length: {requestLengthInBytes}
X-MongoDB-Service-Version: gitHash={gitHash}; versionString={ApplicationVersion}

Response Body¶

{
  "links": [{

  }],
  "results": [{
      "activeAgentCount": 0,
      "hostCounts": {
        "arbiter": 0,
        "config": 0,
        "master": 0,
        "mongos": 0,
        "primary": 1,
        "secondary": 2,
        "slave": 0
      },
      "id": "{PROJECT-ID}",
      "links": [{

      }],
      "name": "Production Cluster",
      "orgId": "{ORG-ID}",
      "publicApiEnabled": true,
      "replicaSetCount": 1,
      "shardCount": 0
    },
    {
      "activeAgentCount": 0,
      "hostCounts": {
        "arbiter": 0,
        "config": 0,
        "master": 0,
        "mongos": 0,
        "primary": 1,
        "secondary": 2,
        "slave": 0
      },
      "id": "{PROJECT-ID}",
      "lastActiveAgent": "2017-10-26T02:39:59Z",
      "links": [{

      }],
      "name": "Staging Cluster",
      "orgId": "{ORG-ID}",
      "publicApiEnabled": true,
      "replicaSetCount": 1,
      "shardCount": 0
    }
  ],
  "totalCount": 2
}

Index Metrics¶

Each index that the Performance Advisor suggests contains the following metrics. These metrics apply specifically to queries which would be improved by the index:

Sample Queries¶

For each suggested index, the Performance Advisor shows the most commonly executed query shapes that the index would improve. For each query shape, the Performance Advisor displays the following metrics:

The Performance Advisor also shows each executed sample query that matches the query shape, with specific metrics for that query.

Query Targeting¶

Each index suggestion includes an Average Query Targeting score indicating how many documents were read for every document returned for the index’s corresponding query shapes. A score of 1 represents very efficient query shapes because every document read matched the query and was returned with the query results. All suggested indexes represent an opportunity to improve query performance.

Filter Index Suggestions¶

By default, the Performance Advisor suggests indexes for all clusters in the deployment. To only show suggested indexes from a specific collection, use the Collection dropdown at the top of the Performance Advisor.

You can also adjust the time range the Performance Advisor takes into account when suggesting indexes by using the Time Range dropdown at the top of the Performance Advisor.

Limitations of Index Suggestions¶

Behavior¶

• You can only create one index at a time through the Performance Advisor. If you want to create more simultaneously, you can do so using Data Explorer or the shell
• Cloud Manager always creates indexes at the top level of the deployment. If you create an index while viewing the Performance Advisor for a single shard in a sharded cluster, Cloud Manager creates that index for the entire sharded cluster.

Procedure¶

To create a suggested index:

{ <option1>: <value1>, ... }

{ unique: true, name: "myUniqueIndex" }

{ "locale": "fr" }