Time Series Data in Mongodb did not do document optimization

Question

Suppose we insert 10 objects to mongodb time series collection. some of those objects contains common metaField of time series collection. I had expectations that number of documents created will be less than the number of objects inserted. But this is not the case. Example:

db.createCollection(
    "weather",
    {
       timeseries: {
          timeField: "timestamp",
          metaField: "metadata",
          granularity: "hours"
       }
    }
)

db.weather.insertMany( [
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-18T00:00:00.000Z"),
      "temp": 12
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-18T04:00:00.000Z"),
      "temp": 11
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-18T08:00:00.000Z"),
      "temp": 11
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-18T12:00:00.000Z"),
      "temp": 12
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-18T16:00:00.000Z"),
      "temp": 16
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-18T20:00:00.000Z"),
      "temp": 15
   }, {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-19T00:00:00.000Z"),
      "temp": 13
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-19T04:00:00.000Z"),
      "temp": 12
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-19T08:00:00.000Z"),
      "temp": 11
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-19T12:00:00.000Z"),
      "temp": 12
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-19T16:00:00.000Z"),
      "temp": 17
   },
   {
      "metadata": { "sensorId": 5578, "type": "temperature" },
      "timestamp": ISODate("2021-05-19T20:00:00.000Z"),
      "temp": 12
   }
] )

> db.weather.countDocuments({})
12

Number of documents seen in the collection are 12 (which is same as number of objects inserted). Why it did not merge the objects together in single document.

score 1 · Answer 1 · answered Apr 18 '23 at 20:10

1

MongoDB timeseries batches documents by sensor. In your sample insert, since all of the documents are for the same sensor, they can all be inserted with the same cost as a inserting a single document. This optimization here is internal to the database server, and does not result in fewer documents being inserted.

See Optimize Inserts in the documentation.

answered Apr 18 '23 at 20:10

Joe

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Thank you for reply. Basically, I wanted to check how many documents created on mongodb for the number of objects inserted. With time series data in mongodb, I was expecting number of documents less than the number of objects inserted, because of meteField. – Yogesh Sonawane Apr 19 '23 at 08:50

Time Series Data in Mongodb did not do document optimization

1 Answers1