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uniqArrayIf

Description​

The Array and If combinators can be applied to the uniq function to count the number of unique values in arrays for rows where the condition is true, using the uniqArrayIf aggregate combinator function.

Note

-If and -Array can be combined. However, Array must come first, then If.

This is useful when you want to count unique elements in an array based on specific conditions without having to use arrayJoin.

Example usage​

Count unique products viewed by segment type and engagement level​

In this example, we'll use a table with user shopping session data to count the number of unique products viewed by users of a specific user segment and with an engagement metric of time spent in the session.

CREATE TABLE user_shopping_sessions
(
    session_date Date,
    user_segment String,
    viewed_products Array(String),
    session_duration_minutes Int32
) ENGINE = Memory;

INSERT INTO user_shopping_sessions VALUES
    ('2024-01-01', 'new_customer', ['smartphone_x', 'headphones_y', 'smartphone_x'], 12),
    ('2024-01-01', 'returning', ['laptop_z', 'smartphone_x', 'tablet_a'], 25),
    ('2024-01-01', 'new_customer', ['smartwatch_b', 'headphones_y', 'fitness_tracker'], 8),
    ('2024-01-02', 'returning', ['laptop_z', 'external_drive', 'laptop_z'], 30),
    ('2024-01-02', 'new_customer', ['tablet_a', 'keyboard_c', 'tablet_a'], 15),
    ('2024-01-02', 'premium', ['smartphone_x', 'smartwatch_b', 'headphones_y'], 22);

-- Count unique products viewed by segment type and engagement level
SELECT 
    session_date,
    -- Count unique products viewed in long sessions by new customers
    uniqArrayIf(viewed_products, user_segment = 'new_customer' AND session_duration_minutes > 10) AS new_customer_engaged_products,
    -- Count unique products viewed by returning customers
    uniqArrayIf(viewed_products, user_segment = 'returning') AS returning_customer_products,
    -- Count unique products viewed across all sessions
    uniqArray(viewed_products) AS total_unique_products
FROM user_shopping_sessions
GROUP BY session_date
ORDER BY session_date
FORMAT Vertical;

Row 1:
──────
session_date:                2024-01-01
new_customer⋯ed_products:    2
returning_customer_products: 3
total_unique_products:       6

Row 2:
──────
session_date:                2024-01-02
new_customer⋯ed_products:    2
returning_customer_products: 2
total_unique_products:       7

See also​