Spotify SQL Interview Question | Joins | windows function | Udit Soni
🔥 Welcome to the 7th Video of the SQL Interview Series! 🔥
Script:
Table: artists
CREATE TABLE artists (
artist_id INT PRIMARY KEY,
artist_name VARCHAR(100),
label_owner VARCHAR(100)
);
INSERT INTO artists (artist_id, artist_name, label_owner) VALUES
(101, 'Ed Sheeran', 'Warner Music Group'),
(120, 'Drake', 'Warner Music Group'),
(125, 'Bad Bunny', 'Rimas Entertainment'),
(130, 'Lady Gaga', 'Interscope Records'),
(140, 'Katy Perry', 'Capitol Records');
Table : songs
CREATE TABLE songs (
song_id INT PRIMARY KEY,
artist_id INT,
name VARCHAR(100)
);
INSERT INTO songs (song_id, artist_id, name) VALUES
(55511, 101, 'Perfect'),
(45202, 101, 'Shape of You'),
(22222, 120, 'One Dance'),
(19960, 120, 'Hotline Bling'),
(33333, 125, 'Dákiti'),
(44444, 125, 'Yonaguni'),
(55555, 130, 'Bad Romance'),
(66666, 130, 'Poker Face'),
(99999, 140, 'Roar'),
(101010, 140, 'Firework');
Table: global_song_rank
CREATE TABLE global_song_rank (
day INT,
song_id INT,
rank INT
);
INSERT INTO global_song_rank (day, song_id, rank) VALUES
(1, 45202, 5),
(3, 45202, 2),
(1, 19960, 3),
(9, 19960, 6),
(1, 55511, 8),
(5, 22222, 7),
(2, 33333, 4),
(4, 44444, 8),
(6, 55555, 1),
(7, 66666, 10),
(5, 99999, 5);
SQL interview questions Spotify / rank artists top 10 songs global rankings / COUNT GROUP BY / RANK DENSE_RANK / window functions / music data analysis / tie handling / continuous ranking / Spotify data analyst interview / music tech SQL problems
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Crack SQL interviews for music-tech giants! In this 7th video of SQL for Interviews, we solve Spotify’s REAL question:
✅ What You’ll Learn:
Master RANK() vs DENSE_RANK() for handling ties
Use COUNT() with GROUP BY to tally Top 10 appearances
Why window functions beat subqueries here
Optimize queries for ranking-heavy datasets
💡 Perfect For:
Data analysts targeting music/streaming roles (Spotify, Apple Music)
SQL beginners struggling with ranking logic
Anyone prepping for tie-handling interview questions
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