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Time Series Collections

On this page

  • Overview
  • Create a Time Series Collection
  • Query a Time Series Collection

In this guide, you can learn about time series collections in MongoDB, and how to interact with them in the MongoDB Java driver.

Time series collections efficiently store sequences of measurements over a period of time. Time series data consists of any data collected over time, metadata that describes the measurement, and the time of the measurement.

Example
Measurement
Metadata
Sales Data
Revenue
Company
Infection Rates
Amount of People Infected
Location

To create a time series collection, pass the following parameters to the createCollection() method:

MongoDatabase database = mongoClient.getDatabase("fall_weather");
TimeSeriesOptions tsOptions = new TimeSeriesOptions("temperature");
CreateCollectionOptions collOptions = new CreateCollectionOptions().timeSeriesOptions(tsOptions);
// Creates a time series collection that stores "temperature" values over time
database.createCollection("september2021", collOptions);

Important

Versions prior to MongoDB 5.0 cannot create a time series collection.

To check if you successfully created the collection, send the "listCollections" command to the runCommand() method.

Document commandResult = database.runCommand(new Document("listCollections", new BsonInt64(1)));
List<String> keys = Arrays.asList("cursor");
// Prints information about the database's collections and views
System.out.println("listCollections: " + commandResult.getEmbedded(keys, Document.class).toJson());

Your output should look similar to the following:

{
"id": <some number>,
"ns": "<db name>.$cmd.listCollections",
"firstBatch": [
{
"name": "<time series collection name>",
"type": "timeseries",
"options": {
"expireAfterSeconds": <some number>,
"timeseries": { ... }
},
...
},
...
]
}

To query in a time series collection, use the same conventions as you would for retrieving and aggregating data.

Note

Window Functions

MongoDB version 5.0 introduces window functions into the aggregation pipeline. You can use window functions to perform operations on a contiguous span of time series data. For more information, see our Aggregates Builders guide.

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