Oracle Analytics automatically recognizes geometry columns from Oracle databases and CSV files, so you can easily import and connect to spatial data.

A geometry data type in Oracle Analytics can represent a wide range of spatial shapes, including points, polygons, and lines, enabling detailed and dynamic geographic visualizations. You can use Geometry data types for visualizing data on maps or as inputs for advanced spatial calculations, enabling detailed spatial analysis.

Geometry columns are special first-class objects in Oracle Analytics that you can use for the following operations:

• To create map visualizations
• In custom calculations for spatial measurements and correlations (either on a canvas or in a data flow)
• As part of custom SQL sourcing (meaning that you can create a dataset using Spatial SQL defined through the Manual SQL query mode)

When you use a geometry column many other operations are disabled or extremely limited. You can't use geometry columns as filters in a workbook or as components (visualization definition grammar) in any visualizations other than maps. You can’t set the geometry data type manually on a data column, it must be recognized as a geometry data type when importing as a dataset.

You can easily use Geometry columns from Oracle databases and CSV files, so that you can easily import and connect to spatial data.

Oracle Analytics supports the geometry data type which lets users visualize and work with geometry columns.

You can make changes to geometry data layers and layer properties.

You can make changes to background map layers and geometry layer properties.

You can toggle the geometry type data layers on and off when the map legend is enabled.

1. In the Properties pane, click General, and check the Legend Position field. The legend displays by default.

   This example shows the legend and layer names for the map visualization.

   
   

   
   Description of the illustration maps_geodatatype_legend_layer_names.png

   
   
2. In the map legend, click a data layer to toggle it on or off.

   This example shows the Storm Buffer data layer toggled off, and Storm Line with US County data layers toggled on. Statistics now shows 3,222 Polygons and one Line. One Polygon for the Storm Buffer is now excluded from the visualization.

   
   

   
   Description of the illustration maps_geodatatype_legend_layer_names_off.png

   
   

   This example shows the US County data layer toggled off, and Storm Line with Storm Buffer data layers toggled on. Statistics now shows one Polygon and one Line. 3,222 Polygons for the US County data layer are now excluded from the visualization.

   
   

   
   Description of the illustration maps_geodatatype_legend_usclayer_off_stormline_on.png

   
   

You can use the Selection tool to interact with geometry data type map layers.

1. Hover over the top right of the map visualization and locate the options for selection: Rectangle, Radial, and Polygon .
2. Click an option to select it, then drag and draw a custom selection area on top of the data layer.

   This example shows how a Polygon selection is used and enables users to draw and select specific attributes.

   
   

   
   Description of the illustration maps_geodatatype_layer_polyselect_draw.png

   
   

   This example shows how selected locations are highlighted once the polygon drawing is released.

   
   

   
   Description of the illustration maps_geodatatype_layer_polydraw_released.png

   
   

   This example shows how users can interact with the custom selection by either keeping the selection or removing the selection.

   
   

   
   Description of the illustration maps_geodatatype_layer_custom_keepremove_selection.png

   
   

   This example shows how the option Keep Selected keeps only the filtered members

   
   

   
   Description of the illustration maps_geodatatype_keep_selected_filters.png

   
   

   This example shows the Radial selection.

   
   

   
   Description of the illustration maps_geodatatype_radial_selection.png

   
   

   This example shows the Rectangle selection.

   
   

   
   Description of the illustration maps_geodatatype_rectangle_selection.png

   
   

You can use the Information option with a map visualization tool to get information about geometry shapes that may not be displayed on the map.

For example, shapes or polygons that are greater in size than 128 KB (per record) aren’t displayed in the map visualization. In this case, the Information icon () appears toward the bottom right of the map visualization. When you click the icon, its color changes from grey to green () and turns on the Information option near the map visualization title. When you hover over this option, you can see which shapes don't render as part of the layer. The information displayed is more detailed if the attribute ID column is part of the map visualization (as a tooltip, color, or shape).

This example shows how the Information option provides more information on shapes that have issues, or that didn’t render.

Description of the illustration maps_geodatatype_info_issues_norender.png

In this example the polygons are shown in a Trellis Column, and polygons poly_4 and poly_5 aren’t displayed due to shape size beyond 128 KB, whereas poly_6 and poly_7 are displayed since the shape size is within 128 KB.

Description of the illustration maps_geodatatype_info_polygons_trellis.png

You can create calculations that use only one geometry column.

You can create calculations that use two geometry columns.

The geometry data type offers exciting possibilities for map-based visualizations and advanced spatial analysis. While there are some limitations to the geometry data type, understanding them helps you make the most of its capabilities.

Limitations with the geometry data type columns:

• Geometry columns can't be:
  • Used as joins between database tables
  • Used as objects to drill on
  • Dragged into any Filter grammar field
  • Used to pass context in a custom data action
  • Clicked to filter a selection of shapes
  • Rendered in maps on mobile devices
  • Used in advanced analytics functions like Forecasting, Clustering, Outlier/Non-Outlier, Reference Line, and Trend Line
• Geometry columns:
  • Can only be placed in the Category grammar field for a map visualization. The content of a geometry column is only valid when used in a map or as an argument for a spatial calculation
  • Are only valid when used in a map, or as an argument for a spatial calculation
• Geometry data have limitations for use in data flows.
• Spatial joins or joins between geometry data types from different database tables or datasets aren’t supported.
• Geometry data type records must each be under 128 kilobytes. If a record in a data source has a geometry expression where the size is above 128 kilobytes, the projection for this record doesn’t show on a map.
  • For example, suppose a table contains data about US states. The table has 50 rows, each containing a geometry data type column with the polygon representing the state shape. Assume one of the states has a very high resolution for its border definition, and the size of the geometry object string for this state amounts to more than 128 kilobytes. Now suppose Oracle Analytics creates the dataset, and queries made to the dataset honor every single column from the dataset. If geometries are projected on a map, then only 49 states are shown on the map. The state that's larger than 128 kilobytes isn't shown on the map, and a warning displays in the dialog for the Information icon on the map.

    If the size of a geometry shape is over 128 kilobytes, then you can try these alternative workarounds:

    • Simplify the definition of the polygon (reduce the number of points to delimit the polygon), and therefore reduce its technical storage.
    • Split the polygon into two or more distinct polygons to break down the size of each piece.
• Oracle Analytics supports 2-D map coordinate systems only. Any known coordinate system defined in the data source is projected to WGS 84 (EPSG 4326).
• File-based data sources containing geometry data must be Text/CSV files with the Geometry field expressed as Well-Known Text (WKT) formats. WKT is a text markup language for representing vector geometry objects. It can represent distinct geometry objects such as Points, MultiPoints, LineString, Polygons, and MultiPolygons. WKT format syntaxes such as GeometryCollection or FeatureCollection aren’t supported.
• Files with the GeoJSON format with geometry data aren’t supported for importing as datasets with geometries in Oracle Analytics. In order to create a dataset with a geometry column, you must first convert GeoJSON files into CSV with WKT geometry formats, or load them into an Oracle database with the SDO.Geometry format.

The geometry data type has some performance considerations that you should understand to help you make the most of its capabilities.

You should consider the following performance considerations for the Geometry data type:

• Physical size of the data retrieved by the map
  • For large datasets with many distinct geometry records, the performance when rendering a map visualization might be impacted by the size of the geometry data that transits over the network to the browser in which Oracle Analytics is running. The performance is a combination of how many distinct geometries are represented on the map, and the average size (in kilobytes) of each geometry. As the map visualization builds, it fetches the geometry definitions through the network for each distinct shape on the map, and for each distinct layer. Very large lists of geometries take longer to render when geometries have a very fine definition (large average size).
  • Mitigation Avoid using too many geometries in a map. Even if the system supports up to 125,000 geometries, using too many can cause the map to render slowly. If you do need to show many shapes at once, filter specific areas so that users can display one area at a time.
• Spatial Cartesian joins
  • Spatial calculation functions such as GeometryDistance, GeometryRelate, and GeometryWithinDistance, may require you to have two joined datasets. These functions might require a many to many join type in order to compute every pair of geometries in your data. You must design this modelling with care to minimise the impact on query performance.
  • Mitigation
    • Use a data model, and most importantly, data filtering on geometry records to avoid Cartesian joining effects.
    • When using a database, spatial calculations ship down the function to the database and let Oracle Analytics retrieve the results of the calculation. When you optimize performance, try to ensure this function-shipping is happening properly. There may be cases where other calculations are added (in data flows or workbooks) that prevent Oracle Analytics from pushing down the work to the database. In the context of troubleshooting performance, it’s important to check the context that allows function shipping.

You can use this list of spatial functions from the Oracle Analytics Calculation Library when you work with the geometry data type.