Downsample data with InfluxDB

This article walks through creating a continuous-query-like task that downsamples data by aggregating data within windows of time, then storing the aggregate value in a new bucket.

To perform a downsampling task, you need to the following:

A “source” bucket

A “destination” bucket

A separate bucket where aggregated, downsampled data is stored.

Some type of aggregation

To downsample data, it must be aggregated in some way. What specific method of aggregation you use depends on your specific use case, but examples include mean, median, top, bottom, etc. View Flux’s aggregate functions for more information and ideas.

1. Defines a variable that represents all data from the last 2 weeks in the mem measurement of the bucket.
2. Uses the to window the data into 1 hour intervals and calculate the average of each interval.
3. Stores the aggregated data in the system-data-downsampled bucket under the organization.

Again, this is a very basic example, but it should provide you with a foundation to build more complex downsampling tasks.

Once your task is ready, see Create a task for information about adding it to InfluxDB.

• If running a task against a bucket with a finite retention period, schedule tasks to run prior to the end of the retention period to let downsampling tasks complete before data outside of the retention period is dropped.