MySQL 8.0引入了多個高級SQL功能,顯著提升了數(shù)據(jù)操作的效率和表達(dá)能力。1. 公用表表達(dá)式(CTEs)替代復(fù)雜嵌套子查詢,使邏輯更清晰、可維護(hù)性更高;2. 遞歸查詢結(jié)合CTEs支持層級數(shù)據(jù)處理,如組織結(jié)構(gòu)或分類樹遍歷;3. 窗口函數(shù)實(shí)現(xiàn)行間計(jì)算而無需分組聚合,適用于排名、累計(jì)統(tǒng)計(jì)等場景;4. JSON增強(qiáng)功能優(yōu)化了對JSON字段的查詢與索引,提升半結(jié)構(gòu)化數(shù)據(jù)處理性能。這些特性不僅簡化了SQL編寫,也增強(qiáng)了數(shù)據(jù)庫的功能邊界。
MySQL 8.0 brought a bunch of advanced SQL features that can really change how you work with data. If you're still using basic queries and haven’t looked into what’s new, you’re probably missing out on some powerful tools. These aren’t just for DBAs or hardcore developers — they can make your day-to-day SQL writing cleaner, faster, and more expressive.

Let’s go over a few key features that stand out and how you can start using them in real scenarios.
Common Table Expressions (CTEs)
CTEs are like temporary result sets you can reference in a SELECT, INSERT, UPDATE, or DELETE statement. They make complex queries easier to read and maintain — especially when dealing with nested subqueries.

Before CTEs, you might have written something like:
SELECT * FROM ( SELECT id, name FROM users WHERE created_at > '2023-01-01' ) AS new_users;
Now with CTEs:

WITH new_users AS ( SELECT id, name FROM users WHERE created_at > '2023-01-01' ) SELECT * FROM new_users;
This becomes really useful when chaining logic. For example, if you need to calculate user growth month-over-month, you can break it down step by step.
Use CTEs when:
- You have deeply nested subqueries
- You want to reuse a query block multiple times
- You're building recursive queries (more on that next)
Recursive Queries with CTEs
This is where CTEs get really powerful. Recursive queries let you traverse hierarchical data — like organizational charts, categories with subcategories, or threaded comments.
Here’s a simple example for building a hierarchy:
WITH RECURSIVE category_tree AS ( SELECT id, name, parent_id FROM categories WHERE parent_id IS NULL UNION ALL SELECT c.id, c.name, c.parent_id FROM categories c INNER JOIN category_tree ct ON c.parent_id = ct.id ) SELECT * FROM category_tree;
What’s happening here:
- The first part selects the root categories (no parent)
- The second part keeps joining until all child levels are found
- The recursion stops when there are no more matches
This is super handy when you need to flatten or analyze nested data without relying on application logic.
Window Functions
Window functions let you perform calculations across a set of table rows that are somehow related to the current row — without collapsing the result set like GROUP BY does.
For example, calculating a running total:
SELECT id, amount, SUM(amount) OVER (ORDER BY id) AS running_total FROM sales;
Or comparing each row to its group average:
SELECT product_id, price, AVG(price) OVER (PARTITION BY category_id) AS avg_price FROM products;
Some common use cases:
- Ranking rows (ROW_NUMBER, RANK, DENSE_RANK)
- Cumulative sums or averages
- Comparing current row with previous/next rows (LAG, LEAD)
They’re a bit tricky to get right at first, but once you understand how the window frame works (ROWS BETWEEN ...), they become indispensable.
JSON Enhancements
MySQL has been improving JSON support for a while, and 8.0 continues that trend. You can now do more with JSON data types without having to extract everything in your app code.
For example, querying nested JSON:
SELECT * FROM orders WHERE JSON_EXTRACT(details, '$.items[0].product_id') = '123';
And there’s better indexing support for JSON columns using virtual columns:
ALTER TABLE orders ADD COLUMN product_id VARCHAR(50) GENERATED ALWAYS AS (JSON_UNQUOTE(JSON_EXTRACT(details, '$.items[0].product_id'))) STORED; CREATE INDEX idx_product_id ON orders(product_id);
This makes querying JSON fields more performant and practical — especially if you're storing semi-structured data.
These features aren’t just bells and whistles. They solve real problems in data modeling, performance, and readability. You don’t need to use all of them all the time, but knowing when to reach for a CTE, a window function, or a recursive query can make a big difference.
And honestly, once you get used to them, going back to older SQL syntax feels like driving without power steering.
基本上就這些。
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