Analyze Document Collaboration CSVs

You are given two CSV files. `document_activity.csv` - `page_id` STRING — document identifier - `user_id` STRING — user who viewed or worked on the document - `viewed_at` TIMESTAMP — event time in UTC - `is_creator` BOOLEAN — `true` if the user created the document - `collaborator_source` STRING NULL — for non-creators only, the channel by which the collaborator reached the document (for example: invite, shared link, search). This field is `NULL` for creators. `users.csv` - `user_id` STRING — user identifier - `country` STRING — user's country Assumptions: - `document_activity.user_id` joins to `users.user_id`. - Each row represents one user-page event. - A document is considered collaborative if at least two distinct users appear on the same `page_id`. - No date filtering is required; use the full dataset. - Treat all timestamps as UTC. Tasks: 1. **Distribution of collaborator acquisition channels** - Consider only rows where `is_creator = false`. - Compute the distribution of `collaborator_source`. - Return: `collaborator_source`, `collaborator_count`, `collaborator_share`. - Define `collaborator_share` as `collaborator_count / total_non_creator_rows`. 2. **Find who collaborated most with a given user** - Given an input `user_id`, find the other user or users who collaborated most often with that user. - Define collaboration as appearing on the same `page_id`. - Count distinct shared `page_id` values, not raw events. - Return: `input_user_id`, `other_user_id`, `shared_page_count`. - If multiple users tie for the maximum, return all tied users ordered by `other_user_id`. 3. **Identify which country has the highest collaboration rate** - Join to `users.csv` to get each user's country. - For each country, define: - `total_active_users` = number of distinct users from that country who appear in `document_activity` - `collaborating_users` = number of those users who appear on at least one collaborative document - `collaboration_rate` = `collaborating_users / total_active_users` - Return: `country`, `collaborating_users`, `total_active_users`, `collaboration_rate`. - Rank countries by `collaboration_rate` descending.