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Migrate Data into a Time Series Collection

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  • Create a New Time Series Collection
  • Transform Data (Optional)
  • Migrate Data into a Time Series Collection

To migrate data from an existing collection into a time series collection:

  1. Create a New Time Series Collection
  2. Transform Data (Optional)
  3. Migrate Data into a Time Series Collection

To create a new time series collection, issue the following command in the mongosh:

db.createCollection(
"weathernew", {
timeseries: {
timeField: "ts",
metaField: "metaData",
granularity: "hours"
}
}
)

For more information on the preceeding command, see Create a Time Series Collection.

Time series collections support secondary indexes on the field specified as the metaField. If the data model of your time series data does not have a designated field for your metadata, you can transform your data to create one. To transform the data in your existing collection, use $merge or $out to create a temporary collection with your time series data.

Consider a collection with weather data of the following format:

{
"_id" : ObjectId("5553a998e4b02cf7151190b8"),
"st" : "x+47600-047900",
"ts" : ISODate("1984-03-05T13:00:00Z"),
"position" : {
"type" : "Point",
"coordinates" : [ -47.9, 47.6 ]
},
"elevation" : 9999,
"callLetters" : "VCSZ",
"qualityControlProcess" : "V020",
"dataSource" : "4",
"type" : "FM-13",
"airTemperature" : { "value" : -3.1, "quality" : "1" },
"dewPoint" : { "value" : 999.9, "quality" : "9" },
"pressure" : { "value" : 1015.3, "quality" : "1" },
"wind" : {
"direction" : { "angle" : 999, "quality" : "9" },
"type" : "9",
"speed" : { "rate" : 999.9, "quality" : "9" }
},
"visibility" : {
"distance" : { "value" : 999999, "quality" : "9" },
"variability" : { "value" : "N", "quality" : "9" }
},
"skyCondition" : {
"ceilingHeight" : { "value" : 99999, "quality" : "9", "determination" : "9" },
"cavok" : "N"
},
"sections" : [ "AG1" ],
"precipitationEstimatedObservation" : { "discrepancy" : "2", "estimatedWaterDepth" : 999 }
}

To transform this data, we issue the following command:

db.weather_data.aggregate([
{
$addFields: {
metaData: {
"st": "$st",
"position": "$position",
"elevation": "$elevation",
"callLetters": "$callLetters",
"qualityControlProcess": "$qualityControlProcess",
"type": "$type"
}
},
}, {
$project: {
_id: 1,
ts: 1,
metaData: 1,
dataSource: 1,
airTemperature: 1,
dewPoint: 1,
pressure: 1,
wind: 1,
visibility: 1,
skyCondition: 1,
sections: 1,
precipitationEstimatedObservation: 1
}
}, {
$out: "temporarytimeseries"
}
])

After you run this command, you have an intermediary temporarytimeseries collection:

db.temporarytimeseries.findOne()
{
"_id" : ObjectId("5553a998e4b02cf7151190b8"),
"ts" : ISODate("1984-03-05T13:00:00Z"),
"dataSource" : "4",
"airTemperature" : { "value" : -3.1, "quality" : "1" },
"dewPoint" : { "value" : 999.9, "quality" : "9" },
"pressure" : { "value" : 1015.3, "quality" : "1" },
"wind" : {
"direction" : { "angle" : 999, "quality" : "9" },
"type" : "9",
"speed" : { "rate" : 999.9, "quality" : "9" }
},
"visibility" : {
"distance" : { "value" : 999999, "quality" : "9" },
"variability" : { "value" : "N", "quality" : "9" }
},
"skyCondition" : {
"ceilingHeight" : { "value" : 99999, "quality" : "9", "determination" : "9" },
"cavok" : "N"
},
"sections" : [ "AG1" ],
"precipitationEstimatedObservation" : { "discrepancy" : "2", "estimatedWaterDepth" : 999 },
"metaData" : {
"st" : "x+47600-047900",
"position" : {
"type" : "Point",
"coordinates" : [ -47.9, 47.6 ]
},
"elevation" : 9999,
"callLetters" : "VCSZ",
"qualityControlProcess" : "V020",
"type" : "FM-13"
}
}

To migrate your data from an existing collection that is not of type timeseries into a time series collection, use mongodump and mongorestore.

Warning

When migrating or backfilling into a time series collection you should always insert the documents in order, from oldest to newest. In this case mongodump exports documents in natural order and the --maintainInsertionOrder option for mongorestore guarantees the same insertion order for documents.

For example, to export the temporarytimeseries collection, issue the following command:

mongodump
--uri="mongodb://mongodb0.example.com:27017,mongodb1.example.com:27017,mongodb2.example.com:27017/weather" \
--collection=temporarytimeseries --out=timeseries

The command returns the following output:

2021-06-01T16:48:39.980+0200 writing weather.temporarytimeseries to timeseries/weather/temporarytimeseries.bson
2021-06-01T16:48:40.056+0200 done dumping weather.temporarytimeseries (10000 documents)

To import timeseries/weather/temporarytimeseries.bson into the new collection weathernew, issue the following command:

mongorestore
--uri="mongodb://mongodb0.example.com:27017,mongodb1.example.com:27017,mongodb2.example.com:27017/weather" \
--collection=weathernew --noIndexRestore \
--maintainInsertionOrder \
timeseries/weather/temporarytimeseries.bson

The command returns the following output:

2021-06-01T16:50:56.639+0200 checking for collection data in timeseries/weather/temporarytimeseries.bson
2021-06-01T16:50:56.640+0200 restoring to existing collection weather.weathernew without dropping
2021-06-01T16:50:56.640+0200 reading metadata for weather.weathernew from timeseries/weather/temporarytimeseries.metadata.json
2021-06-01T16:50:56.640+0200 restoring weather.weathernew from timeseries/weather/temporarytimeseries.bson
2021-06-01T16:51:01.229+0200 no indexes to restore
2021-06-01T16:51:01.229+0200 finished restoring weather.weathernew (10000 documents, 0 failures)
2021-06-01T16:51:01.229+0200 10000 document(s) restored successfully. 0 document(s) failed to restore.
Note

Ensure that you run the preceeding command with the --noIndexRestore option. mongorestore cannot create indexes on time series collections.

If your original collection had secondary indexes, manually recreate them now.

Tip
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