Efficiently Insert Rows into PostgreSQL Only if They Do Not Already Exist

Introduction

In database management, ensuring data integrity while inserting new records is crucial. A common scenario is attempting to insert a row that might already exist in the table, which can lead to errors due to unique constraints. This tutorial will guide you through efficient methods for conditionally inserting rows into a PostgreSQL database using Python and SQL.

Understanding the Problem

When working with databases, especially those enforcing uniqueness on certain columns (like primary keys or unique indexes), you may encounter an IntegrityError if you try to insert a duplicate entry. PostgreSQL provides several ways to handle such situations gracefully without causing errors.

Methods for Conditional Insertion

1. Using the UPSERT Command (INSERT ... ON CONFLICT)

PostgreSQL version 9.5 introduced the "upsert" feature, allowing conditional updates or inserts using the ON CONFLICT clause. This method is efficient and safe in concurrent environments.

Example:

INSERT INTO hundred (name, name_slug, status)
VALUES ('example_name', 'example_slug', 'active')
ON CONFLICT (hundred_pkey) DO NOTHING;

In this example, if a row with the same primary key (hundred_pkey) already exists, PostgreSQL will do nothing. You can replace DO NOTHING with DO UPDATE SET ... to update specific columns.

Advantages:

• Avoids race conditions.
• Simplifies SQL logic by combining insert and conflict handling in one statement.

2. Using a Conditional INSERT Statement

For PostgreSQL versions older than 9.5, you can use a conditional approach based on the existence of the row:

INSERT INTO hundred (name, name_slug, status)
SELECT 'example_name', 'example_slug', 'active'
WHERE NOT EXISTS (
    SELECT 1 FROM hundred WHERE name = 'example_name' AND name_slug = 'example_slug' AND status = 'active'
);

Caveat:

This method has a race condition risk in concurrent scenarios, where the NOT EXISTS check and the subsequent INSERT might be executed simultaneously by different transactions.

3. Using Temporary Tables

Another approach involves using temporary tables to batch process data:

1. Create a Temporary Table:

   CREATE TEMPORARY TABLE temp_data(name TEXT, name_slug TEXT, status TEXT);
   

2. Insert Data into the Temporary Table:

   sql_string = "INSERT INTO temp_data (name, name_slug, status) VALUES (%s, %s, %s)"
   cursor.execute(sql_string, (hundred, hundred_slug, status))
   

3. Perform the Insert with a Distinct Check:

   INSERT INTO hundred(name, name_slug, status)
   SELECT DISTINCT name, name_slug, status
   FROM temp_data
   WHERE NOT EXISTS (
       SELECT 1 FROM hundred 
       WHERE hundred.name = temp_data.name 
         AND hundred.name_slug = temp_data.name_slug 
         AND hundred.status = temp_data.status
   );
   

Advantages:

• Useful for bulk inserts where checking each row individually would be inefficient.

Best Practices

• Indexing: Ensure that the columns involved in uniqueness checks are indexed to optimize performance.
• Transaction Management: Use transactions when performing complex operations to maintain data integrity.
• Concurrency Considerations: Prefer ON CONFLICT for concurrent environments to avoid race conditions.

Conclusion

Choosing the right method depends on your PostgreSQL version and specific use case requirements. The INSERT ... ON CONFLICT clause is generally recommended due to its simplicity and reliability in handling duplicates, especially in concurrent scenarios. However, understanding all methods allows you to select the best approach for your needs.