PostgreSQL中带投影与连接查询的优质索引方案咨询

Hey there! Let's break down exactly what indexes you should create for each query, plus figure out why your testing was giving those confusing "performance stays even after deleting indexes" results.

Scenario A: Multi-Join Query with Content Filter #

Your query:

SELECT p.content, u.name 
FROM posts p, admins a, users u 
WHERE p.tag = a.tag and a.id = u.id and p.content = 'Hello World';

Here are the targeted indexes to maximize performance:

• On posts: Create INDEX idx_posts_content_tag (content, tag)
  • This index starts with content to quickly filter rows where p.content = 'Hello World', then includes tag to directly join with the admins table without needing to hit the main table (it's a covering index for the filter and join step, plus we're selecting p.content which is already in the index).
• On admins: Create INDEX idx_admins_tag_id (tag, id)
  • Starts with tag to match the join from posts, then includes id to join with the users table. No need for extra columns since we don't select anything from admins.
• On users: Create INDEX idx_users_id_name (id, name)
  • Uses id for the join with admins, and includes name so the database can pull the selected value directly from the index (another covering index, no need to access the main user table).

Scenario B: User-Post Join with Content Filter #

Your query:

SELECT u.name, p.date 
FROM users u, posts p 
WHERE u.userid = p.userid and p.content = 'Hello World';

Optimal indexes here:

• On posts: Create INDEX idx_posts_content_userid_date (content, userid, date)
  • Filters by content first, then uses userid to join with users, and includes date so we don't have to go back to the main posts table to fetch the selected value.
• On users: Create INDEX idx_users_userid_name (userid, name)
  • Joins via userid and includes name as a covering index for the selected column.

Why Your Testing Results Were Misleading #

That "performance stays after deleting indexes" issue is almost certainly due to database caching. Databases like MySQL, PostgreSQL, etc., cache frequently accessed data pages and even query results in memory. Once you run the query once, the relevant data is loaded into the cache—so subsequent runs (even without indexes) will be fast because they're pulling from memory instead of disk.

To get accurate, comparable test results:

• Clear the cache before each test: For example, in MySQL you can run FLUSH TABLES; (to clear table buffers). For PostgreSQL, use SELECT pg_stat_reset(); and SELECT pg_prewarm('tablename', 'buffer'); to reset stats and clear cached pages.
• Use EXPLAIN instead of just timing: Run EXPLAIN before your query to see exactly which indexes the database is using. This is more reliable than execution time because it shows the execution plan directly, regardless of cache state.

内容的提问来源于stack exchange，提问作者Gouz