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Time Series Collection Limitations

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  • Unsupported Features
  • Aggregation $merge
  • distinct Command
  • Geospatial Queries
  • Document Size
  • Extended Date Range
  • Updates
  • Time Series Secondary Indexes
  • Capped Collections
  • Modification of Collection Type
  • Modification of timeField and metaField
  • Granularity
  • Bucket Size
  • Modifying Bucket Parameters
  • Sharding
  • Sharding Administration Commands
  • Shard Key Fields
  • Resharding
  • Transactions
  • Views
  • Snapshot Isolation

Time series collections generally behave like regular collections with several limitations.

MongoDB does not support the following features with time series collections:

You cannot use the $merge aggregation stage to add data from another collection to a time series collection. Use the $out aggregation stage to write documents to a time series collection.

You can use $merge to move data from a time series collection to another collection.

Due to the unique data structure of time series collections, MongoDB can't efficiently index them for distinct values. Avoid using the distinct command or db.collection.distinct() helper method on time series collections. Instead, use a $group aggregation to group documents by distinct values.

For example, to query for distinct meta.type values on documents where meta.project = 10, instead of:

db.foo.distinct("meta.type", {"meta.project": 10})

Use:

db.foo.createIndex({"meta.project":1, "meta.type":1})
db.foo.aggregate([{$match: {"meta.project": 10}},
{$group: {_id: "$meta.type"}}])

This works as follows:

  1. Creating a compound index on meta.project and meta.type and supports the aggregation.

  2. The $match stage filters for documents where meta.project = 10.

  3. The $group stage uses meta.type as the group key to output one document per unique value.

Time series collections only support the $geoNear aggregation stage for sorting geospatial data from queries against 2dsphere indexes. You can't use $near and $nearSphere operators on time series collections

The maximum size for documents within a time series collection is 4 MB.

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.

For details on TTL deletes, see Expire Data from Collections by Setting TTL.

If your time series collection contains documents with timeField timestamps before 1970-01-01T00:00:00.000Z or after 2038-01-19T03:14:07.000Z, create an index on the timeField to optimize queries.

Update commands must meet the following requirements:

  • You can only match on the metaField field value.

  • You can only modify the metaField field value.

  • Your update document can only contain update operator expressions.

  • Your update command must not limit the number of documents to be updated. Set multi: true or use the updateMany() method.

  • Your update command must not set upsert: true.

To automatically delete old data, set up automatic removal (TTL).

MongoDB partially supports the following indexes on time series collections:

MongoDB doesn't support the following index types on time series collections:

If there are secondary indexes on time series collections and you need to downgrade the feature compatibility version (FCV), you must first drop any secondary indexes that are incompatible with the downgraded FCV. For more information, see setFeatureCompatibilityVersion.

You cannot create a time series collection as a capped collection.

You can only set the collection type when you create a collection:

  • You cannot convert an existing collection into a time series collection.

  • You cannot convert a time series collection into a different collection type.

To move data from an existing collection to a time series collection, migrate data into a time series collection.

You can only set a collection's timeField and metaField parameters when you create the collection. You cannot modify these parameters later.

For any configuration of granularity parameters, the maximum size of a bucket is 1000 measurements or 125KB of data, whichever is lower. MongoDB may also enforce a lower maximum size for high cardinality data with many unique values, so that the working set of buckets fits within the WiredTiger cache.

Once you set a collection's granularity or the custom bucketing parameters bucketMaxSpanSeconds and bucketRoundingSeconds, you can increase the time span covered by a bucket, but not decrease it. Use the collMod command to modify the parameters. For example:

db.runCommand({
collMod: "timeseries",
timeseries: { bucketMaxSpanSeconds: 3600, bucketRoundingSeconds: 3600 }
})

Note

bucketMaxSpanSeconds and bucketRoundingSeconds must be equal. If you modify one parameter, you must also set the other to the same value.

Time series collections are subject to several sharding limitations.

You cannot run sharding administration commands on sharded time series collections.

When sharding time series collections, you can only specify the following fields in the shard key:

  • The metaField

  • Sub-fields of metaField

  • The timeField

You may specify combinations of these fields in the shard key. No other fields, including _id, are allowed in the shard key pattern.

When you specify the shard key:

Tip

Avoid specifying only the timeField as the shard key. Since the timeField increases monotonically, it may result in all writes appearing on a single chunk within the cluster. Ideally, data is evenly distributed across chunks.

To learn how to best choose a shard key, see:

Starting in MongoDB 8.0, use of the timeField as a shard key in a time series collection is deprecated.

You cannot reshard a sharded time series collection. However, you can refine its shard key.

You cannot write to time series collections in transactions.

Note

MongoDB supports reads from time series collections in transactions.

  • Time series collections are writable non-materialized views. Limitations for views apply to time series collections.

  • You cannot create a view from a time series bucket collection namespace (namely, a collection prefixed with system.buckets).

Read operations on time series collections with read concern "snapshot" guarantee snapshot isolation only in the absence of concurrent drop or rename operations on collections in the read operation. Re-creating a time series collection on the same namespace with different granularity setting does not yield full snapshot isolation.

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