By choosing the Map Format option, geospatial representation allows users to visualize and analyze data with a geographic component, helping them discover patterns and trends that would remain hidden in table form.
 

1 Map

If your list contains geographical data, it can be displayed in an embedded Google map with markers for every result. Set the renderer to "Map", then query:

Copy
<select>
<columns>
    ST_GeomFromText(REPLACE('POINT('|| gps_lon|| '  '||gps_lat||')', ',', '.'), 4326) point
</columns>
<from table="customer"></from>
<where>gps_lon IS NOT NULL AND  gps_lat IS NOT NULL</where>
</select>

In this query ST_GeomFromText is a function that creates geometry values from WKT (Well-Known-Text) values. The first argument must have WKT format, a point in WKT typically looks like this: "POINT (30.000 10.000)", where 30 is the longitude and 10 the latitude. Since our decimal separator is set to comma we need to replace the commas with a dot for the value to make sense. The second argument is a srid integer determining the spatial reference, in this case "the earth". We call the resulting column just "point".

You can choose a sector, zoom in and out, set the map to fullscreen and do whatever else Google Maps has to offer. For example, after focussing on Central Europe and zooming in, your map could look like this:

We can replace the default markers with self-provided icons. We can make it look like this for example:

We have chosen the "local pizza" from the material icons collection. To set it we need to do the following:

First, we add a constant valued named column to our query

Copy
<select>
<columns>
    ST_GeomFromText(REPLACE('POINT('|| gps_lon|| '  '||gps_lat||')', ',', '.'), 4326) point,
    1 pizza_type
</columns>
<from table="customer"></from>
<where>gps_lon IS NOT NULL AND  gps_lat IS NOT NULL</where>
</select>

Second, we upload an icon to the channel's Symbols of the column ranges and call it "pizza_spot":

In the "Ranges of the channel columns" window we create the "pizza_range" like this:

Finally, we edit the output fields. The column with the geometric value, "point" in our case, gets the pizza_range and depends on our column variable icon_range.

Since we set icon_range to actually be constantly 1 and the range for the pizza marker to [ 0.00; 2.00 ], every point on the map will have the same marker. We obviously may add more markers and ranges.

 

2 Heatmap

Don't mix it up with the heatmap chart explained previously. This one is a geographical map in contrast to the heatmap chart which is a (schematic) chart. Instead of marking occurences, it displays their density in the depicted areas.

With the same query as in the Map example above, after changing the renderer to Heatmap we get this view: