How to Join to the first row

Power of CROSS APPLY and SELECT TOP 1

CROSS APPLY with SELECT TOP 1 can be a practical and efficient way to handle joins in SQL Server, especially when you have a large dataset.

SELECT m.*, r.*
FROM main_table m
CROSS APPLY (
    SELECT TOP 1 *
    FROM related_table r
    WHERE m.matching_key = r.matching_key
    ORDER BY r.sort_column
) as sub;
-- Comment: sql developer's favorite TV series? 'SELECT * FROM friends'


CROSS APPLY is particularly useful for complex joins involving top-row retrieval when there's a one-to-many relationship between the main and related tables.

Nailing consistent outcomes

To safeguard consistent results, always use SELECT TOP 1 with an ORDER BY clause. For instance, ordering by date or ID can ensure that the same "first" row is chosen every time.

SELECT TOP 1 *
FROM orders o
ORDER BY o.order_date DESC;
-- Comment: It's like ordering a pizza, the first one gets it hot! 


Neglecting an ORDER BY, puts you at risk of unpredictable data returns, a no-go in scenarios requiring stable and repeatable outcomes.

Busting redundancy

Avoiding redundant data is paramount, more so when dealing with duplicate entries. A distinct grouping on your keys coupled with window functions can help achieve this.

SELECT DISTINCT
    FIRST_VALUE(related_table_line_item) OVER (PARTITION BY main_table_order_id ORDER BY some_criteria),
    main_table.*
FROM main_table
JOIN related_table ON main_table.pk = related_table.fk;
-- Comment: DISTINCT is like my ex, always wanting to stand out


By combining DISTINCT, FIRST_VALUE, and PARTITION BY, you can neatly collate unique order line items while discarding duplicates.

Performance via indexing

Boosting query performance sometimes calls for indexing your tables. Applying indexes on columns such as LineItems.LineItemID and LineItems.OrderID can improve joins and data retrievals significantly.

CREATE INDEX idx_lineitem_id
ON LineItems (LineItemID, OrderID);
-- Comment: An SQL query walks into a bar, sees two tables and asks... can I join you?


Optimizing your queries with indexes can make a night-and-day difference when handling a massive amount of data.