Implement pagination capabilities within the Map controller for loading & displaying large datasets efficiently

Currently in Spatial when the map performs an operation that requires loading a large amount of data that needs to be placed on the map, it attempts to fetch & process all this data at once instead of batching it into smaller sizes. Based on our experience, this approach results in the following pain-points for users:

1. Long loading times if the map actually ends up being able to process the data

2. Timeout errors if the map isn't able to load the data within the allotted time by the server - this is what happens most of the time when attempting to load more than 50 Asset pins on the map for instance

3. Users are forced to severely limit the amount of records that can be shown on the map at the same time, which is driving a lot of users away from fully utilizing Spatial in Manage

Some examples of these map operations that time out include but are not limited to:

• Using the "Related Items" function with a Work Order that has a significant number of Tasks or Assets within the "Multiple Assets, Location and CIs" table

• Pointing the map control's data source to a source that can contain multiple records e.g.: to the list view, or another controller with a significant number of records like the "Multiple Assets, Location and CIs" table

This idea is to propose the implementation of some kind of pagination capabilities when loading the map control's data source with a configurable batch size as a system property, as well some kind of optimization strategy where the critical set of data that needs to be placed on the map is loaded fast and the rest of results are either loaded in the background or as the user scrolls through the map (i.e. lazy loading).

On average, we have experienced a waste of approximately 3 minutes everytime a large dataset is queried via the map (longer if the request fails as the user needs to log out and log back in) and the typical user will perform this operation around 10 times a day, which would result in a total waste of 30 minutes per day per user. If the typical user earns about $30/hour, this means the amount of money being wasted daily per user is $15 which would entail a total of $15 x 260 working days = $3900 dollars/year per user that could be saved by simply optimizing the loading process in the maps.