You work on a music app and want to recommend “friend” connections based on listening similarity. Assume the following tables (all timestamps are in UTC): **listens** - `user_id` (INT) - `song_id` (INT) - `listened_at` (TIMESTAMP) **friendships** (undirected; each friendship appears once) - `user_id_1` (INT) - `user_id_2` (INT) A pair of users `(a, b)` is a **recommended friend pair** on a given calendar date `d` if: 1) They are **not already friends** in `friendships` (treat friendships as undirected), and 2) On date `d`, they listened to **more than 3** of the **same songs** (i.e., at least 4 distinct overlapping `song_id`s that both users listened to that day). Write a SQL query to output all recommended pairs and the date(s) on which they qualify. **Output columns**: - `user_id_1` (INT) — the smaller user id in the pair - `user_id_2` (INT) — the larger user id in the pair - `listen_date` (DATE) - `overlap_songs` (INT) — number of distinct overlapping songs on that date Notes/assumptions: - If a user listens to the same song multiple times in a day, it should count as **1** toward overlap for that day. - A pair can appear on multiple dates if they qualify on multiple dates.