Скачать или смотреть Can PostgreSQL Efficiently Use an Index for Row-Wise Comparison?

Discover whether PostgreSQL can utilize a B-Tree index for row-wise comparisons in queries and learn how it applies to your implementation.
---
This video is based on the question https://stackoverflow.com/q/63420878/ asked by the user 'Milan Jovanovic' ( https://stackoverflow.com/u/9198020/ ) and on the answer https://stackoverflow.com/a/63421066/ provided by the user 'Gordon Linoff' ( https://stackoverflow.com/u/1144035/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Can PostgreSQL use an index for row-wise comparison?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding Index Usage in PostgreSQL for Row-Wise Comparisons

When using PostgreSQL, database optimization is crucial, especially in cases like cursor pagination. A common question among developers is whether PostgreSQL can utilize an index for row-wise comparisons in SQL queries. This guide will explore this topic by answering a specific query and providing insights into how the indexing process works.

The Problem at Hand

Let's consider a scenario where you have a SQL query designed for pagination, which looks something like this:

[[See Video to Reveal this Text or Code Snippet]]

In this query, you want to determine if PostgreSQL can efficiently use a B-Tree index defined on (a, b, c) to answer the request. This question arises particularly when working with cursor pagination methods that require efficient data retrieval.

Your Use Case

Pagination Implementation: You are using a UUID as a primary key.

Column Requirements: You're relying on date and timestamp columns as cursors for retrieval.

Initial Observations: Your testing with EXPLAIN ANALYZE did not show any index usage, which may have been surprising.

The Solution: How PostgreSQL Uses an Index

Can PostgreSQL Use the Index?

Yes, PostgreSQL can and should use the index for the query, but only for the first two columns (a and b). Here's how it works:

Index Scanning:

PostgreSQL can efficiently scan rows based on the value of column a that you've specified. Because your index includes a, it can quickly find all matching values.

Pulling Additional Values:

Once it identifies the rows that match the condition for a, PostgreSQL can then pull values for columns b and c as per your condition (b, c) <= ....

This step enables PostgreSQL to examine a range of values for b while still being informed by the first condition.

Key Points about Index Efficiency

Up-to-date Index: It's imperative that the index is up to date and reflective of the current data in the table. If the index is stale, it might not retrieve the expected values correctly.

Table Scan vs. Index Scan:

If your table is small, PostgreSQL might resort to a full table scan as it can retrieve data faster that way. This can explain why you noticed the absence of index usage during your test.

However, as your dataset grows, relying on the index for these conditions will yield better performance.

Conclusion

In summary, PostgreSQL can effectively use a B-Tree index for row-wise comparisons in your given SQL query, specifically with respect to the first couple of columns. It's essential to understand how data retrieval works and the implications of index usage on query performance, especially in scenarios such as pagination.

By knowing how PostgreSQL interacts with indexes and optimizing your database schema accordingly, you can enhance the performance of your SQL queries and provide a smoother experience for users interacting with your application.

Feel free to dive deeper into PostgreSQL's indexing strategies and keep optimizing your database for the best performance!