MySQL 8.0 introduces window functions to simplify complex queries. 1. The window function returns statistical values ??for each row and retains the original data; 2. Common functions include ROW_NUMBER(), RANK(), DENSE_RANK(), SUM(), AVG(), etc.; 3. It can be used to rank by category, sum up, and obtain grouped head and tail records; 4. Usage techniques include clarifying PARTITION BY, ORDER BY and window range settings, and paying attention to index optimization performance.
MySQL 8.0 introduces window functions, which makes analysis tasks that originally required complex subqueries or self-connections much simpler. If you often deal with reporting, trend analysis or ranking needs, using window functions can save a lot of trouble.
What is a window function?
Window functions are a bit similar to ordinary aggregate functions, but their calculations do not merge multiple rows into one row, but return a value for each row. This is especially useful when you want to keep the original data, and add some statistics (such as rankings, cumulative sums, moving averages, etc.).
Common window functions include:
-
ROW_NUMBER(): Generate row numbers in order of specified order -
RANK()andDENSE_RANK(): used for ranking, the difference is whether the juxtaposition is skipped -
SUM(),AVG(),MIN(),MAX(): These aggregate functions can also be used as window functions
For example, if you want to see the sales ranking of each salesperson in their area, you can use RANK() and PARTITION BY to achieve it.
Common application scenarios and writing methods
Ranking by category
SELECT
Salesperson,
region,
sales_amount,
RANK() OVER (PARTITION BY region ORDER BY sales_amount DESC) AS sales_rank
FROM sales; This way you can see everyone's sales ranking in their own area. PARTITION BY region is equivalent to grouping by region and sorting it separately.
Accumulated sum/mobile average
Sometimes you want to know what the cumulative sales are as of the current record, you can use SUM() window function:
SELECT
order_date,
sales_amount,
SUM(sales_amount) OVER (ORDER BY order_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_total
FROM daily_sales; Here, ROWS BETWEEN ... is used to define the window range, indicating that it is added from the first line to the current line.
Get the first or last record of each group
Although MySQL does not have FIRST_VALUE() or LAST_VALUE() shortcuts like some databases that directly get the head and tail records, you can combine ROW_NUMBER() to achieve similar effects:
WITH ranked_sales AS (
SELECT
product_id,
sale_date,
sales_amount,
ROW_NUMBER() OVER (PARTITION BY product_id ORDER BY sale_date ASC) AS rn_asc,
ROW_NUMBER() OVER (PARTITION BY product_id ORDER BY sale_date DESC) AS rn_desc
FROM product_sales
)
SELECT * FROM ranked_sales WHERE rn_asc = 1 OR rn_desc = 1;This way, you can get the earliest and latest sales records for each product.
Tips when using window functions
- Don't forget
PARTITION BY: If not added, the entire result set will be processed as a window. - The sorting field should be clear :
ORDER BYis necessary especially when ranking or cumulative. - Note the window scope setting : the default is
RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, but in some scenarios you need to control more accurately, such as replacingRANGEwithROWS. - Pay attention to indexing in performance : Although the window function is very powerful, if the table is large, sorting will be very resource-intensive. It is recommended to establish a suitable index on commonly used sorting fields.
Basically that's it. Window functions have indeed improved MySQL's ability in data analysis. Although it seems a bit confusing at the beginning, as long as you understand the logic of "partition sorting calculation", it will not be difficult to use.
The above is the detailed content of Using window functions in MySQL 8.0 for advanced analytics. For more information, please follow other related articles on the PHP Chinese website!
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