How to join only one row in joined table with Postgres?

sql

prompt-engineering

performance

best-practices

byAlex Kataev·Sep 8, 2024

To fetch only the first matching row from a related table in Postgres, employ a LATERAL join with LIMIT 1. This approach selects a single row based on your desired order.

Concise example:

SELECT mt.*, lr.*
FROM main_table mt
CROSS JOIN LATERAL (
    SELECT * FROM joined_table jt
    WHERE jt.foreign_key = mt.id
    ORDER BY jt.order_column
    LIMIT 1
) lr;

Replace mt, jt, foreign_key, order_column, and the column selections to fit your schema. The key is to have LIMIT 1 inside the lateral subquery which isolates the top ordered row per main record.

Leverage the "DISTINCT ON" Clause

If you prefer a different approach or LATERAL JOIN is not an option, using DISTINCT ON with the right ORDER BY clause can be very effective.

In Postgres:

SELECT DISTINCT ON (mt.id) mt.*, jt.*
FROM main_table mt
JOIN joined_table jt ON mt.id = jt.foreign_key
ORDER BY mt.id, jt.order_column DESC;

Here, mt.id should be the unique identifier of rows in the main table. The jt.order_column should be the column you want to use for determining the "latest" or "first" row from the joined table, like a timestamp or incremental ID.

Remember, without ORDER BY, the DISTINCT ON results are unpredictable. Always include the columns used in DISTINCT ON in the ORDER BY clause to ensure the proper row is selected.

The Power of Window Functions

Sometimes you may want to retrieve more complex sets of data, like the latest or highest-scoring entries. In these cases, familiarize yourself with window functions like ROW_NUMBER(). They allow you to partition your data set and apply a function like ROW_NUMBER() to each partition.

Example snippet:

SELECT mt.*, jt.*
FROM (
    SELECT *,
           ROW_NUMBER() OVER (PARTITION BY foreign_key ORDER BY order_column DESC) as rn  -- "First come, first serve!"
    FROM joined_table
) jt
JOIN main_table mt ON mt.id = jt.foreign_key
WHERE jt.rn = 1;

Unique Entries with "NOT EXISTS"

In scenarios where you need to guarantee the uniqueness of rows, the NOT EXISTS clause can be your ally. This is particularly useful when your JOIN criteria might match multiple rows in the joined table, and you only want the first one.

Subquery example using NOT EXISTS:

SELECT mt.*, jt.*
FROM main_table mt
JOIN joined_table jt ON jt.foreign_key = mt.id
WHERE NOT EXISTS (
    SELECT 1
    FROM joined_table jt2
    WHERE jt2.foreign_key = mt.id
      AND jt2.order_column < jt.order_column  -- "There can be only one!" (Highlander, 1986)
);

Query Performance Maximization

When working with large datasets, prioritize query performance. Ensure that your JOIN fields, like author_id and book_id, are indexed appropriately. Proper indexing can drastically reduce query times.

Performance Tips:

Indexes: Create indexes on the columns involved in the join and ordering.
Ordering: Use DESC or ASC in your ORDER BY clause purposefully when using DISTINCT ON.
Testing: Validate query performance on different subsets of your data to avoid unexpected slowdowns.
Avoiding Bottlenecks: When using window functions or DISTINCT ON, be mindful that large partitions can cause performance issues.