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TTL Indexes

On this page

  • Create a TTL Index
  • Convert a non-TTL single-field Index into a TTL Index
  • Change the expireAfterSeconds value for a TTL Index
  • Behavior
  • Restrictions

Note

If you are removing documents to save on storage costs, consider Online Archive in MongoDB Atlas. Online Archive automatically archives infrequently accessed data to fully-managed S3 buckets for cost-effective data tiering.

TTL indexes are special single-field indexes that MongoDB can use to automatically remove documents from a collection after a certain amount of time or at a specific clock time. Data expiration is useful for certain types of information like machine generated event data, logs, and session information that only need to persist in a database for a finite amount of time.

You can create and manage TTL indexes in the UI for deployments hosted in MongoDB Atlas.

Create a TTL Index

Warning

After you create a TTL index, it might have a very large number of qualifying documents to delete at once. This large workload might cause performance issues on the server. To avoid these issues, plan to create the index during off hours, or delete qualifying documents in batches before you create the index for future documents.

To create a TTL index, use createIndex(). Specify an index field that is either a date type or an array that contains date type values. Use the expireAfterSeconds option to specify a TTL value in seconds.

The TTL index expireAfterSeconds value must be within 0 and 2147483647 inclusive.

For example, to create a TTL index on the lastModifiedDate field of the eventlog collection with a TTL value of 3600 seconds, use the following operation in mongosh:

db.eventlog.createIndex(
   { "lastModifiedDate": 1 },
   { expireAfterSeconds: 3600 }
)

Starting in MongoDB 6.3, you can create partial TTL indexes on time series collections. These indexes use the collection timeField as the key field, and require a partial filter expression on the metaField.

Time series collections include an optional expireAfterSeconds field. If you don't set expireAfterSeconds, a TTL index with a partialFilterExpression lets you set an expiration period for documents that match the filter. If you do set expireAfterSeconds, a partial TTL index lets you set a different, shorter expiration period for matching documents. You can only create a partialFilterExpression on the metaField.

Important

If the expireAfterSeconds value of the collection is lower than the expireAfterSeconds of the partial TTL index, the collection deletes documents after the shorter time, so the TTL index has no effect.

If a time series collection contains documents with timeField timestamps before 1970-01-01T00:00:00.000Z or after 2038-01-19T03:14:07.000Z, no documents are deleted from the collection by the TTL "time to live" feature.

This weather data time series collection deletes documents after 24 hours:

db.createCollection(
   "weather24h",
   {
      timeseries: {
         timeField: "timestamp",
         metaField: "sensor",
         granularity: "hours"
      },
      expireAfterSeconds: 86400
   }
)

This TTL index deletes documents from the MongoDB NYC headquarters weather sensor after 1 hour, instead of 24 hours:

db.eventlog.createIndex(
  { "timestamp": 1 },
  { partialFilterExpression: { "sensor": { $eq: "40.761873, -73.984287" } } },
  { expireAfterSeconds: 3600 } )

Convert a non-TTL single-field Index into a TTL Index

Starting in MongoDB 5.1, you can add the expireAfterSeconds option to an existing single-field index. To change a non-TTL single-field index to a TTL index, use the collMod database command:

db.runCommand({
  "collMod": <collName>,
  "index": {
    "keyPattern": <keyPattern>,
    "expireAfterSeconds": <number>
  }
})

The following example converts a non-TTL single-field index with the pattern { "lastModifiedDate": 1 } into a TTL index:

db.runCommand({
  "collMod": "tickets",
  "index": {
    "keyPattern": { "lastModifiedDate": 1 },
    "expireAfterSeconds": 100
  }
})

Change the expireAfterSeconds value for a TTL Index

To change the expireAfterSeconds value for a TTL Index, use the collMod database command:

db.runCommand({
  "collMod": <collName>,
  "index": {
    "keyPattern": <keyPattern>,
    "expireAfterSeconds": <number>
  }
})

The following example changes the expireAfterSeconds value for an index with the pattern { "lastModifiedDate": 1 } on the tickets collection:

db.runCommand({
  "collMod": "tickets",
  "index": {
    "keyPattern": { "lastModifiedDate": 1 },
    "expireAfterSeconds": 100
  }
})

Important

Consider the following before updating the expireAfterSeconds parameter of a TTL index:

  • Changing the expireAfterSeconds parameter does not trigger a complete index rebuild. However, reducing the expireAfterSeconds value can make many documents eligible for immediate deletion, potentially causing performance issues due to the increased delete operations.

  • The recommended approach is to manually delete documents in small batches before updating the TTL index. This helps control the impact on your cluster.

  • Deleting many documents can fragment storage files, additionally impacting performance. You may need to run the compact command on your collection or perform a Initial Sync to reclaim space and optimize storage.

Behavior

Expiration of Data

TTL indexes expire documents after the specified number of seconds has passed since the indexed field value. The expiration threshold is the indexed field value plus the specified number of seconds.

If the field is an array, and there are multiple date values in the index, MongoDB uses lowest (earliest) date value in the array to calculate the expiration threshold.

For time series collections, TTL indexes also remove a bucket of data when all documents inside it expire. This is equal to the upper timestamp limit of the bucket, plus the expireAfterSeconds value. For example, if a bucket covers data up until 2023-03-27T18:29:59Z and expireAfterSeconds is 300, the TTL index expires the bucket after 2023-03-27T18:34:59Z.

If the indexed field in a document doesn't contain one or more date values, the document will not expire.

If a document does not contain the indexed field, the document will not expire.

Delete Operations

A background thread in mongod reads the values in the index and removes expired documents from the collection.

In progress delete operations performed by the TTL thread appear in db.currentOp() output. As the TTL thread deletes documents, the metrics.ttl.deletedDocuments server status metric is incremented.

Starting in MongoDB 6.1:

  • To improve efficiency, MongoDB may batch multiple document deletions together.

  • The explain command results contain a new BATCHED_DELETE stage for batched document deletions.

If a time series collection contains documents with timeField timestamps before 1970-01-01T00:00:00.000Z or after 2038-01-19T03:14:07.000Z, no documents are deleted from the collection by the TTL "time to live" feature.

Deletion Process

The TTL background deletion process checks each TTL index for expired documents. For each TTL index, the background process deletes documents until one of the following conditions is met:

  • The process deletes 50000 documents from the current index.

  • The process spends one second deleting documents from the current index.

  • All expired documents are deleted from the current index.

Then, the process moves on to the next index. After the process goes through each TTL index once, the current sub-pass is complete and a new sub-pass begins to check for remaining expired documents. A pass is complete when the TTL monitor has deleted all possible candidate documents from all TTL indexes.

Additionally, the process stops the current deletion loop every 60 seconds to prevent spending too much time on a single large delete. When this happens, the current sub-pass ends and a new sub-pass begins.

Passes and sub-passes are tracked in the metrics.ttl.passes and metrics.ttl.subPasses server status metrics, respectively.

Timing of the Delete Operation

MongoDB begins removing expired documents or time series buckets as soon as the index finishes building on the primary. For more information on the index build process, see Index Builds on Populated Collections.

The TTL index does not guarantee that expired data is deleted immediately upon expiration. There may be a delay between the time that a document expires and the time that MongoDB removes the document from the database.

The background task that removes expired documents runs every 60 seconds. As a result, documents may remain in a collection during the period between the expiration of the document and the running of the background task. MongoDB starts deleting documents 0 to 60 seconds after the index completes.

Because the duration of the removal operation depends on the workload of your mongod instance, expired data may exist for some time beyond the 60 second period between runs of the background task.

The delete operations initiated by the TTL task run in the foreground, like other deletes.

Replica Sets

On replica set members, the TTL background thread only deletes documents when a member is in state primary. The TTL background thread is idle when a member is in state secondary. Secondary members replicate deletion operations from the primary.

Support for Queries

A TTL index supports queries in the same way non-TTL indexes do.

Restrictions

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