> ## Documentation Index
> Fetch the complete documentation index at: https://paradedb-ankitml-legacy-docs-remove.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# BM25 Scoring

> BM25 scores sort the result set by relevance

BM25 scores measure how relevant a score is for a given query. Higher scores indicate higher relevance.

## Basic Usage

The `pdb.score(<key_field>)` function produces a BM25 score and can be added to any query where any of the ParadeDB operators are present.

```sql theme={null}
SELECT id, pdb.score(id)
FROM mock_items
WHERE description ||| 'shoes'
ORDER BY pdb.score(id)
LIMIT 5;
```

In order for a field to be factored into the BM25 score, it must be present in the BM25 index. For instance,
consider this query:

```sql theme={null}
SELECT id, pdb.score(id)
FROM mock_items
WHERE description ||| 'keyboard' OR rating < 2
ORDER BY pdb.score(id)
LIMIT 5;
```

While BM25 scores will be returned as long as `description` is indexed, including `rating` in the BM25 index definition will allow results matching
`rating < 2` to rank higher than those that do not match.

## Joined Scores

First, let's create a second table called `orders` that can be joined with `mock_items`:

```sql theme={null}
CALL paradedb.create_bm25_test_table(
  schema_name => 'public',
  table_name => 'orders',
  table_type => 'Orders'
);

ALTER TABLE orders
ADD CONSTRAINT foreign_key_product_id
FOREIGN KEY (product_id)
REFERENCES mock_items(id);

CREATE INDEX orders_idx ON orders
USING bm25 (order_id, product_id, order_quantity, order_total, customer_name)
WITH (key_field = 'order_id');
```

Next, let's compute a "combined BM25 score" over a join across both tables.

```sql theme={null}
SELECT o.order_id, o.customer_name, m.description, pdb.score(o.order_id) + pdb.score(m.id) as score
FROM orders o
JOIN mock_items m ON o.product_id = m.id
WHERE o.customer_name ||| 'Johnson' AND m.description ||| 'running shoes'
ORDER BY score DESC, o.order_id
LIMIT 5;
```

## Score Refresh

The scores generated by the BM25 index may be influenced by dead rows that have not been cleaned up by the `VACUUM` process.

Running `VACUUM` on the underlying table will remove all dead rows from the index and ensures that only rows visible to the current
transaction are factored into the BM25 score.

```sql theme={null}
VACUUM mock_items;
```

This can be automated with [autovacuum](/documentation/performance-tuning/overview).