Why does PostgreSQL perform sequential scan on indexed column?

📚 Why does PostgreSQL perform sequential scan on indexed column? 🤔

So you've set up your PostgreSQL database, created a table with an index on a column, and you're excited to see how your queries will benefit from this optimized structure. But wait, why is PostgreSQL performing a sequential scan instead of using the index? 🤷‍♀️

🔍 Understanding the Problem The issue here lies in the selectivity of the indexed column. Selectivity refers to the uniqueness of values in a column compared to the total number of rows. If PostgreSQL determines that the indexed column is not selective enough, it might decide that a sequential scan is faster than an index scan.

In the given example, the indexed column "year" is not highly selective, as there seems to be a large number of rows with a "year" greater than 2009. This lack of selectivity leads PostgreSQL to favor a sequential scan, as it believes it can read the entire table faster than using the index.

💡 Easy Solutions Fortunately, there are a few ways you can encourage PostgreSQL to use an index scan instead of a sequential scan:

1️⃣ Increase the selectivity: If possible, make the indexed column more selective. For example, if you have many rows with a "year" greater than 2009, consider narrowing down the range or using a different column for indexing.

2️⃣ Analyze the table: Run the ANALYZE command on the table to update the statistics used by the query optimizer. This can help PostgreSQL make better decisions regarding the use of indexes.

3️⃣ Use a partial index: If your queries frequently filter rows based on specific conditions, you can create a partial index that only includes those rows. This can improve selectivity and increase the chances of index usage.

📣 Call-to-Action: Explore and Engage Now that you understand why PostgreSQL might perform a sequential scan instead of an index scan, take a look at your own database and queries. Are there any instances where you could optimize index usage?

Share your thoughts, experiences, and any other tips you have for improving query performance in PostgreSQL. Comment below or join our thriving community of tech enthusiasts on our forum. Happy optimizing! 🚀🔥

P.S. If you found this post helpful, share it with your fellow PostgreSQL enthusiasts! Let's spread the knowledge and make our databases lightning-fast together! 💪📊

Disclaimer: The example and explanations in this blog post are based on the information provided by the user and may not cover all possible scenarios. It's always recommended to analyze your specific database and queries for optimal performance.