This limit is making it slow and expensive to query the subgraphs. For example, we want to display a chart data based on a specific time range, it would take the application multiple calls to retrieve that data and stitch them together in order to bypass that limit.
cc @Oliver the follow up of our last core dev call.
At the moment, Bubbletea’s python lib is bypassing this “limitation” by invoking multiple requests, aggregating and stitching the results, so the user doesn’t have to. We have ideas that will enable more of this Data Science type of use cases (among others, revamping GraphQL API), so community feedback is important.
I believe the current limitation in place is set purely to try to avoid bad performance, but maybe, in the future, we could allow users to bypass the default behavior.