Using Functions in WHERE Clauses with Postgres

As a developer, you’re likely familiar with the concept of using functions to perform specific operations within your SQL queries. In this article, we’ll delve into how to use functions in the WHERE clause of your Postgres queries, specifically when working with similarity searches.

Introduction to Similarity Searches

Postgres provides an ilike operator that allows you to search for patterns within a string column. This is useful when you want to match strings that contain certain keywords or characters, such as a company name or city name. However, if you need more complex comparisons, such as searching for similar text across multiple columns, the similarity function comes into play.

The similarity function returns a percentage value (between 0 and 1) indicating the likelihood of two strings being similar. You can use this function to calculate a weighted total score by combining scores from multiple columns.

The Challenge

Let’s assume you’re working with a table that contains information about companies, including their name, common name, abbreviated name, city name, and child names. You want to search for records where the company name, common name, or city name matches a given input string ($1), and also calculate a weighted total score by combining these similarities.

The current query uses the similarity function in three places:

• As a column alias (e.g., parent_name_similarity)
• In the WHERE clause (e.g., similarity(parent.name, $1) > .3)
• In the ORDER BY clause (e.g., similarity(parent.name, $1) DESC)

While this query works as intended, it does feel repetitive and inefficient. We can improve performance by reusing a single function call for all operations.

Simplifying the Query

Let’s examine how to simplify the query using a technique called “function reuse.” Instead of calling similarity multiple times in different parts of the query, we’ll create a new column alias that combines the results from each column. We can then use this combined score in both the WHERE clause and ORDER BY clause.

Here’s an example:

SELECT parent.id, parent.name, child.id, child.name,
    similarity(parent.name, $1) AS parent_name_similarity,
    similarity(parent.abbreviated_name, $1) AS parent_abbr_similarity,
    similarity(parent.common_name, $1) AS parent_common_similarity,
    similarity(parent.state, $1) AS parent_state_similarity,
    similarity(parent.city, $1) AS parent_city_similarity,
    similarity(child.name, $1) AS child_name_similarity,
    (
        parent_name_similarity
        + parent_abbr_similarity
        + CASE WHEN child_name_similarity IS NULL THEN 0 ELSE child_name_similarity END
    ) AS weighted_total
FROM account_master parent
LEFT OUTER JOIN child_table child ON child.parent = parent.id::text
WHERE weighted_total > .3
ORDER BY weighted_total DESC;

However, this approach still requires calling similarity multiple times in the WHERE clause.

Function Reuse with a Single Call

To truly reuse the similarity function, we can create a new column alias that combines the results from each column using the weightage function (which is not shown in the original code). This would allow us to use the combined score once for both the WHERE clause and ORDER BY clause.

Unfortunately, Postgres does not provide an explicit weightage function. However, we can achieve similar results by multiplying each individual similarity value with a fixed weight value. Let’s assume that you want to assign a weight value of 1.0 for parent_name_similarity, 2.0 for parent_abbr_similarity, and 3.0 for parent_common_similarity.

Here’s an updated example:

SELECT parent.id, parent.name, child.id, child.name,
    similarity(parent.name, $1) AS parent_name_similarity,
    (similarity(parent.abbreviated_name, $1) * 2) AS parent_abbr_similarity_weighted,
    (similarity(parent.common_name, $1) * 3) AS parent_common_similarity_weighted,
    (
        parent_name_similarity
        + parent_abbr_similarity_weighted
        + CASE WHEN child_name_similarity IS NULL THEN 0 ELSE child_name_similarity END
    ) AS weighted_total
FROM account_master parent
LEFT OUTER JOIN child_table child ON child.parent = parent.id::text
WHERE weighted_total > .3
ORDER BY weighted_total DESC;

In this updated query, we’re using the weightage function to multiply each individual similarity value with a fixed weight value. This allows us to reuse the combined score once for both the WHERE clause and ORDER BY clause.

Conclusion

Using functions in the WHERE clause of your Postgres queries can be an efficient way to perform complex comparisons, such as searching for similar text across multiple columns. By reusing a single function call and combining individual similarity values using weighted scoring, we can simplify our queries while maintaining performance.

In this article, we explored how to use the similarity function in Postgres queries to calculate weighted totals scores by combining individual column similarities. We also examined techniques for function reuse to reduce repetition and improve query efficiency.

Last modified on 2024-12-07