Grafana includes a WorldMap visualization that help you see geospatial data overlaid atop a map of the world. This can be helpful to understand how data changes based on its location.
To complete this tutorial, you need a cursory knowledge of the Structured Query Language (SQL). The tutorial walks you through each SQL command, but it is helpful if you've seen SQL before.
- To start, install TimescaleDB.
- Next setup Grafana.
Once your installation of TimescaleDB and Grafana are complete, ingest the data found in the NYC Taxi Cab tutorial and configure Grafana to connect to that database. Be sure to follow the full tutorial if you're interested in background on how to use TimescaleDB.
Be sure to pay close attention to the geospatial query portion of the tutorial and complete those steps.
The NYC Taxi Cab data also contains the location of each ride pickup. In the NYC Taxi Cab tutorial, we examined rides that originated near Times Square. Let's build on that query and visualize rides whose distance traveled was greater than five miles in Manhattan.
We can do this in Grafana using the 'Worldmap Panel'. Start by creating a new panel, selecting 'New Visualization', and selecting the 'Worldmap Panel'.
Once again, you can edit the query directly. In the Query screen, be sure to select your NYC Taxicab Data as the data source. In the 'Format as' dropdown, select 'Table'. Click on 'Edit SQL' and enter the following query in the text window:
SELECT time_bucket('5m', rides.pickup_datetime) AS time,rides.trip_distance AS value,rides.pickup_latitude AS latitude,rides.pickup_longitude AS longitudeFROM ridesWHERE $__timeFilter(rides.pickup_datetime) ANDST_Distance(pickup_geom,ST_Transform(ST_SetSRID(ST_MakePoint(-73.9851,40.7589),4326),2163)) < 2000GROUP BY time,rides.trip_distance,rides.pickup_latitude,rides.pickup_longitudeORDER BY timeLIMIT 500;
Let's dissect this query. First, we're looking to plot rides with visual markers that
denote the trip distance. Trips with longer distances get different visual treatments
on our map. Use the
trip_distance as the value for our plot, and store
this result in the
In the second and third lines of the
SELECT statement, we are using the
pickup_latitude fields in the database and mapping them to variables
WHERE clause, we are applying a geospatial boundary to look for trips within
2000m of Times Square.
Finally, in the
GROUP BY clause, we supply the
trip_distance and location variables
so that Grafana can plot data properly.
This query may take a while, depending on the speed of your Internet connection. This is why we're using the
LIMIT statement for demonstration purposes.
Now let's configure our Worldmap visualization. Select the 'Visualization' tab in the far left of the Grafana user interface. You'll see options for 'Map Visual Options', 'Map Data Options', and more.
First, make sure the 'Map Data Options' are set to 'table' and 'current'. Then in
the 'Field Mappings' section. Set the 'Table Query Format' to be 'Table'.
We can map the 'Latitude Field' to our
latitude variable, the 'Longitude Field' to
longitude variable, and the 'Metric' field to our
In the 'Map Visual Options', set the 'Min Circle Size' to 1 and the 'Max Circle Size' to 5.
In the 'Threshold Options' set the 'Thresholds' to '2,5,10'. This auto configures a set
of colors. Any plot whose
value is below 2 is a color, any
value between 2 and 5 is another color, any
value between 5 and 10 is a third color, and any
value over 10
is a fourth color.
Your configuration should look like this:
At this point, data should be flowing into our Worldmap visualization, like so:
You should be able to edit the time filter at the top of your visualization to see trip pickup data for different timeframes.
Complete your Grafana knowledge by following all the TimescaleDB + Grafana tutorials.
Found an issue on this page?Report an issue!