Examine the recommendations by Mongo Atlas
The prod database is managed at https://cloud.mongodb.com/v2/6239e2417155de3d798e9187#clusters/detail/datasets-server-prod

It provides recommendations, that might be useful to take into account. They are all listed in the Performance advisor: https://cloud.mongodb.com/v2/6239e2417155de3d798e9187#metrics/replicaSet/6239e8ba6c32bf5c2d888fb5/advisor

Currently:

<img width="1567" alt="Capture d’écran 2022-06-17 à 10 39 13" src="https://user-images.githubusercontent.com/1676121/174261254-7419c2ed-f31d-4f95-8d6a-3037408f9a4b.png">

It proposes to create one index and drop two (see #392).

It also remarks that the [datasets_server_cache.splits](https://cloud.mongodb.com/v2/6239e2417155de3d798e9187#metrics/replicaSet/6239e8ba6c32bf5c2d888fb5/explorer/datasets_server_cache/splits) collection contains documents larger than 2MB, which "can result in excess cache pressure, especially if a small portion of them are being updated or queried.". For the latter, note that we had implemented more granular collections, but then stepped back: see https://github.com/huggingface/datasets-server/pull/202
Examine the recommendations by Mongo Atlas: The prod database is managed at https://cloud.mongodb.com/v2/6239e2417155de3d798e9187#clusters/detail/datasets-server-prod

It provides recommendations, that might be useful to take into account. They are all listed in the Performance advisor: https://cloud.mongodb.com/v2/6239e2417155de3d798e9187#metrics/replicaSet/6239e8ba6c32bf5c2d888fb5/advisor

Currently:

<img width="1567" alt="Capture d’écran 2022-06-17 à 10 39 13" src="https://user-images.githubusercontent.com/1676121/174261254-7419c2ed-f31d-4f95-8d6a-3037408f9a4b.png">

It proposes to create one index and drop two (see #392).

It also remarks that the [datasets_server_cache.splits](https://cloud.mongodb.com/v2/6239e2417155de3d798e9187#metrics/replicaSet/6239e8ba6c32bf5c2d888fb5/explorer/datasets_server_cache/splits) collection contains documents larger than 2MB, which "can result in excess cache pressure, especially if a small portion of them are being updated or queried.". For the latter, note that we had implemented more granular collections, but then stepped back: see https://github.com/huggingface/datasets-server/pull/202