richard-churchman
5f6bbe45f7
Major bug fixes relating to the Redis implementation in Reprocessing and Search Key Cache were identified and fixed as part of the rekeying development. Included functionality to stop the Exhaustive training. Fixed the Unsupervised learning functionality in Exhaustive Training. Embedded the Mock Data CSV data into a class to make it compatible with Docker without needing to modify the Dockerfile (i.e, build). Included a new table that stores training data to enhance support capabilities for Exhaustive. Reintroduced and validated the Multitenancy functionality. Postgres is now fully deprecated in place of Redis for cache, and all implementations of the Interfaces for Postgres have been removed. No migrations exist to support this deprecation, and Postgres as a cache is now wholly unsupported. Removed the Indexing background thread, as Redis does not require it, given that it is a key-value pair database. Created a RedisCommandFlag Environment Variable to support Fire and Forget write to Redis in Invocation. Implemented functionality to Export, Peek and Download configuration environments using a secure, encrypted scheme. Created a permission to access the functionality via the user interface. Extensive database-based logging is included to provide for a comprehensive audit. Created functionality to Import the encrypted Export file inside a database transaction to ensure consistency. As Docker is now the primary deployment model, log4net instantiation has been moved to an approach that primarily uses programmatic instantiation of the ConsoleLogger and RollingFileAppender given Environment Variables. Implemented functionality to support remote \ mounted Log4Net XML Serialisation files for more advanced log4net configurations. Reintroduced access to counters via the user interface and created a permission. Took the opportunity to implement ReSharper linter suggestions. Disabled the Lock button across the whole application, with that functionality being reserved for future use. It is intended that locking happens programmatically on the basis of dependencies in future commits. Fixed several significant end-use bugs which became apparent during testing of the refactored code relating to case management and visualisations. Fixed certain other minor bugs that came up during testing. Brought documentation up to date for this commit. Brought the Docker Compose file up to date for this commit. Removed Redundant Environment Variables for this commit. Made the README file less verbose and unnecessary.
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layout, title, nav_order, parent, grand_parent
| layout | title | nav_order | parent | grand_parent |
|---|---|---|---|---|
| default | Generate Map in Visualisation Datasource | 6 | Visualisations | Configuration |
🚀Speed up implementation with hands-on, face-to-face training from the developer.
Generate Map in Visualisation Datasource
Similar to charts Visualisations are achieved via embedding configuration Javascript for the Kendo Charting toolset. The Kendo Map toolset provides a rich set of mapping functions that can be used to alternatively present data that would otherwise be in grid form.
A demonstration of the Kendo mapping tools can be seen as follows:
https://demos.telerik.com/kendo-ui/map/index
A datasource can accept the initialisation parameters for a Kendo Chart:
Extracted as follows:
({
center: [30.268107, -97.744821],
zoom: 3,
layers: [{
type: "tile",
urlTemplate: "https://#= subdomain #.tile.openstreetmap.org/#= zoom #/#= x #/#= y #.png",
subdomains: ["a", "b", "c"],
attribution: "© <a href='https://osm.org/copyright'>OpenStreetMap contributors</a>"
}],
markers: [{
location: [30.268107, -97.744821],
shape: "pinTarget",
tooltip: {
content: "Austin, TX"
}
}]
})
For the purpose of chart initialisation, series are the columns returned by the SQL statement (which are parsed out on creation of the datasource and do not otherwise require manual definition beyond the SQL select block), however, the latitude and longitude values must be returned using the Array type, which has special construct in SQL:
select ARRAY["Latitude" ,"Longitude"] as "Location","Sum" from "ExampleGeoCoded"
Executing the above SQL directly presents the following dataset:
The array return value will be used to drop a bubble or pin. In the case of bubble, the Sum expresses magnitude.
Taking the following example of Kendo Map initialisation:
({
center: [51.5072,0.1276],
zoom: 3,
layers: [{
type: "tile",
urlTemplate: "https://#= subdomain #.tile.openstreetmap.org/#= zoom #/#= x #/#= y #.png",
subdomains: ["a", "b", "c"],
attribution: "© <a href='https://osm.org/copyright'>OpenStreetMap contributors</a>"
}, {
type: "bubble",
style: {
fill: {
color: "#00f",
opacity: 0.4
},
stroke: {
width: 0
}
},
locationField: "Location",
valueField: "Sum"
}]
})
Note the locationField and valueField has been updated for binding to the datasource:
locationField: "Location",
valueField: "Sum"
Any datasource object will be added during the recall process and should be removed from the initialisation.
Navigate Administration >> Visualisation >> Visualisation Datasources, then click on the Visualisation Registry Entry to create a new datasource:
Using the above SQL and map initialisation as above, create a new entry:
Click Add to create a version of the Visualisation Registry Datasource, which will parse the SQL and create the series definitions in the background:
Navigate to the Visualisation Registry through the Visualisation Directory to recall. Noting the default parameter value for Name, as Email, click on Run to execute the datasource, whereby SQL will be tokenized for with the parameter value provided. Scroll down to make visible the third tile:
It can be seen that the map has been plotted as initialisation with bubbles being dropped based on the location, and the bubbles magnitude being the Sum value. In the event that magnitude, thus bubble, is not required, then the pin target can simply be used in the chart initialization.