Introduction

SQL joins are essential for combining data from different tables in a relational database. However, they can sometimes be tricky, especially when dealing with complex joins that involve multiple columns or need to account for variations in data structure. In this post, we’ll walk through a real-world scenario where a SQL join on multiple columns wasn’t producing the expected results and explore how to debug and resolve the issue.

The Scenario

Let’s say we have a dataset containing information about artists and their works, stored in a PostgreSQL database. The data is split across two tables: moma_artists and moma. The constituent_id column in the moma table contains a list of artist IDs separated by commas, while the moma_artists table contains individual artist records with their corresponding constituent_id.

We want to join these tables to see all the works associated with each artist, regardless of whether the artist is listed as the primary, secondary, or tertiary contributor. To achieve this, we need to split the constituent_id in the moma table and perform a join based on these split values.

The Query

Here’s the initial SQL query we used:

WITH C_ID AS (
    SELECT constituent_id,
           split_part(constituent_id, ',', 1) AS C_ID_1,
           split_part(constituent_id, ',', 2) AS C_ID_2,
           ...
           split_part(constituent_id, ',', 30) AS C_ID_30,
           item_id
    FROM moma
)
SELECT *
FROM moma_artists
LEFT JOIN C_ID ON moma_artists.constituent_id = C_ID_2
WHERE 1=1
  AND C_ID_2 IS NOT NULL
ORDER BY moma_artists.constituent_id DESC
LIMIT 50;

The Problem

The query didn’t return any results, even though we expected matches between moma_artists.constituent_id and C_ID_2. Both fields were of the varchar data type, so a mismatched column type wasn’t the issue.

What was going wrong?

Debugging Steps

1. Check for Leading or Trailing SpacesSometimes, data might have extra spaces that prevent a match in a join condition. To address this, we used the TRIM function to remove any leading or trailing spaces from both columns:

SELECT DISTINCT
  TRIM(moma_artists.constituent_id) AS constituent_id_trimmed,
  TRIM(C_ID_2) AS C_ID_2_trimmed
FROM moma_artists
LEFT JOIN C_ID ON TRIM(moma_artists.constituent_id) = TRIM(C_ID_2)
WHERE C_ID_2 IS NOT NULL;

Outcome: This step helped confirm that there were no spaces causing the mismatch.

Verify for NULL Values

Another potential issue was the presence of NULL values in either column. NULL values in SQL don’t match anything, not even other NULL values. We checked for NULL values:

SELECT COUNT(*) AS null_count_moma_artists
FROM moma_artists
WHERE constituent_id IS NULL;

SELECT COUNT(*) AS null_count_C_ID
FROM C_ID
WHERE C_ID_2 IS NULL;

Outcome: No NULL values were found in either column, so this wasn’t the issue.

Ensure Correct Splitting

We also checked that the constituent_id in the moma table contained enough commas to be split into 30 parts. If there weren’t enough commas, some split values could be NULL, causing the join to fail:

SELECT MAX(LENGTH(constituent_id) - LENGTH(REPLACE(constituent_id, ',', ''))) + 1 AS num_commas FROM moma;

Outcome: This revealed that some rows didn’t have enough parts, leading to NULL in C_ID_2.

Examine Case Sensitivity

SQL joins are case-sensitive by default. We ensured that both columns had matching case formats:

SELECT *
FROM moma_artists
LEFT JOIN C_ID ON LOWER(moma_artists.constituent_id) = LOWER(C_ID_2)
WHERE C_ID_2 IS NOT NULL;

1. Outcome: This helped identify that some values didn’t match due to case differences.

The Solution

After going through these steps, the problem was clear: a combination of missing parts in some rows and case sensitivity was causing the join to fail. By addressing these issues—ensuring that we split the constituent_id correctly and accounted for case sensitivity—we were able to perform the join successfully.

Conclusion

SQL joins can be challenging, especially when dealing with complex data structures. However, by systematically debugging the query—checking for spaces, NULL values, split correctness, and case sensitivity—we were able to resolve the issue and achieve the desired results. Remember, when a join isn’t working as expected, break down the problem, test each component, and you’ll often find a solution.