In this blog post I will share how to create an SAP Analytics Cloud (SAC), Geo Map based on Calculation Views created within the WebIDE. These are Calc Views that reside within an HDI Container as Column Views.
- HANA Cloud / HANA On-Prem with XSA
- Live Connection from SAC to HANA
- Dataset with Latitude and Longitude
- WebIDE Calculation Views
- hdinamespace subfolder Setting
- Create SAP_BOC_SPATIAL folder
- Spatial Reference 3857
- Location Data
- Create Geo Dimensional Calculation View with ST_POINT
- Associate Calc Views in SAP Analytics Cloud Model
For the official documentation please see the SAP Analytics Cloud Help
1. hdinamespace subfolder Setting
For the SAC Location Dimension to be picked up in your model, you need the WebIDE hdinamespace setting as below
Warning, if you change an existing project using “ignore” then some re-work will be required.
2. Create SAP_BOC_SPATIAL folder
SAP Analytics Cloud looks for location data inside the sub folder SAP_BOC_SPATIAL.
This should be created inside the WebIDE project src folder.
3. Spatial Reference 3857
For SAC to visualise the location data, HANA must have the Spatial Reference 3857 available.
We can check this with the public synonym ST_SPATIAL_REFERENCE_SYSTEMS.
If you do NOT see the SRS_ID 3857 then you can execute the SQL below to add that
CREATE SPATIAL REFERENCE SYSTEM "WGS 84 / Pseudo-Mercator" IDENTIFIED BY 3857 TYPE PLANAR SNAP TO GRID 1e-4 TOLERANCE 1e-4 COORDINATE X BETWEEN -20037508.3427892447 AND 20037508.3427892447 COORDINATE Y BETWEEN -19929191.7668547928 AND 19929191.766854766 ORGANIZATION "EPSG" IDENTIFIED BY 3857 LINEAR UNIT OF MEASURE "metre" ANGULAR UNIT OF MEASURE NULL POLYGON FORMAT 'EvenOdd' STORAGE FORMAT 'Internal' DEFINITION 'PROJCS["Popular Visualisation CRS / Mercator",GEOGCS["Popular Visualisation CRS",DATUM["Popular_Visualisation_Datum",SPHEROID["Popular Visualisation Sphere",6378137,0,AUTHORITY["EPSG","7059"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[ "EPSG","6055"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree", 0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4055"]],UNIT[ "metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Mercator_1SP"],PARAMETER["cen tral_meridian",0],PARAMETER["scale_factor",1],PARAMETER["false_easting",0],PA RAMETER["false_northing",0],AUTHORITY["EPSG","3785"],AXIS["X",EAST],AXIS["Y", NORTH]]' TRANSFORM DEFINITION '+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +wktext +no_defs'
4. Location Data
The location dataset must not contain duplicate values. To perform the correct join SAC requires a unique list of locations to ensure referential integrity of your model. This dataset will need latitude, longitude data and a field that joins to other Calc Views.
Here I have the table of UK Local Authorities, LAD2019_WKT, sorted on the field lad19cd, which I can see is unique.
5. Create Geo Dimensional Calculation View with ST_POINT
We can now create a new dimensional Calculation View inside the SAP_BOC_SPATIAL folder. Notice how the Namespace field is populated with the required folder name.
The output column names need to be unique across the two calculation views that you are using with SAC. I therefore appended _geo to the end of the lad19cd and lad19nm.
Create Calculated Column of data type ST_POINT.
Using the fields “long” and “lat” we generate the ST_POINT column that SAP Analytics Cloud requires using the SRS 3857.
ST_Transform(ST_GeomFromText('POINT(' || "long" || ' ' || "lat" || ')', 4326),3857)
We can Save and Build the Calculation View.
We can find our Calculation View as a Column View. Note how the name is prefixed with SAP_BOC_SPATIAL (the subfolder we created in step 2.)
We should data preview it to verify it works as expected. Note how the name is again prefixed with SAP_BOC_SPATIAL.
6. Associate Calc Views in SAP Analytics Cloud Model
Open an existing SAC Model that will join to the fields exposed in the above model, in my case I can join on either lad19cd_geo or lad19nm_geo. Click the “Location Dimension” button.
We need to associate our Geo Dimensional Calc View with an existing calculation view.
The Location Identifier comes from an existing calculation view, this is the Attribute Column that joins to the Identifier for Mapping column coming from the step 5 “Geo Dimensional Calculation View”. In my case Area_code joins to lad19cd_geo. This would be a 1:1 or many:1 with the many coming from the existing calculation view.
The final test is to create a Geo Map using this model to verify both the data and locations are displayed correctly on the map.
Spatial data has become more prevalent within the Enterprise, using SAP Analytics Cloud with HANA is a convenient way to visual this. Using this blog post you can understand how WebIDE based Calculation Views from HANA or HANA Cloud can be consumed live.