Migrate Data into a Time Series Collection
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To migrate data from an existing collection into a time series collection:
Create a New 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.
Transform Data (Optional)
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" } }
Migrate Data into a Time Series Collection
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. If your collection includes timeField
values before
1970-01-01T00:00:00.000Z
or after 2038-01-19T03:14:07.000Z
,
MongoDB logs a warning and disables some query optimizations that make
use of the internal clustered index. Create a secondary index on the timeField
to regain query
performance and resolve the log warning.
Tip
See also:
Add Secondary Indexes to Time Series Collections
If you insert a document into a collection with a timeField
value before 1970-01-01T00:00:00.000Z
or after
2038-01-19T03:14:07.000Z
,
MongoDB logs a warning and prevents some query optimizations from
using the internal index. Create a secondary index
on the timeField
to regain query performance and resolve the log
warning.