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大家好,我是 V 哥。SQL調(diào)優(yōu)對于提升數(shù)據(jù)庫查詢性能至關重要,特別是當數(shù)據(jù)量大時。以下是20個詳細的SQL調(diào)優(yōu)指南和高級技巧,結合案例說明,幫助優(yōu)化SQL查詢的性能。
SELECT name FROM employees WHERE department_id = 10;
department_id
創(chuàng)建索引:CREATE INDEX idx_department_id ON employees(department_id);
SELECT * FROM employees WHERE department_id = 10;
SELECT name FROM employees WHERE department_id = 10;
SELECT name FROM employees WHERE department_id IN (SELECT id FROM departments WHERE location = 'New York');
SELECT e.name FROM employees e JOIN departments d ON e.department_id = d.id WHERE d.location = 'New York';
EXPLAIN
或EXPLAIN ANALYZE
來查看SQL查詢的執(zhí)行計劃,找到性能瓶頸。EXPLAIN SELECT name FROM employees WHERE department_id = 10;
ORDER BY
會消耗大量資源,尤其是大數(shù)據(jù)量時,只有在需要排序時才使用。SELECT name FROM employees WHERE department_id = 10 ORDER BY hire_date;
ORDER BY
。LIMIT
,對于大偏移量的查詢,可以通過索引或緩存減少開銷。SELECT name FROM employees ORDER BY hire_date LIMIT 100000, 10;
SELECT name FROM employees WHERE id > 100000 ORDER BY hire_date LIMIT 10;
SELECT name FROM employees WHERE YEAR(hire_date) = 2023;
SELECT name FROM employees WHERE hire_date BETWEEN '2023-01-01' AND '2023-12-31';
status
放在索引前面:CREATE INDEX idx_status_department ON employees(status, department_id);
INSERT INTO employees (name, department_id) VALUES ('John', 10);
INSERT INTO employees (name, department_id) VALUES ('John', 10), ('Alice', 20), ('Bob', 30);
NOT IN
性能較差,改用NOT EXISTS
或LEFT JOIN
。SELECT name FROM employees WHERE department_id NOT IN (SELECT id FROM departments);
LEFT JOIN
:SELECT e.name FROM employees e LEFT JOIN departments d ON e.department_id = d.id WHERE d.id IS NULL;
DISTINCT
。SELECT DISTINCT name FROM employees WHERE department_id = 10;
DISTINCT
。INNER JOIN
,除非明確需要所有數(shù)據(jù),避免使用LEFT JOIN
或RIGHT JOIN
。SELECT e.name, d.name FROM employees e LEFT JOIN departments d ON e.department_id = d.id;
INNER JOIN
:SELECT e.name, d.name FROM employees e INNER JOIN departments d ON e.department_id = d.id;
CREATE TABLE employees (
id INT,
name VARCHAR(50),
hire_date DATE
)
PARTITION BY RANGE (YEAR(hire_date)) (
PARTITION p2020 VALUES LESS THAN (2021),
PARTITION p2021 VALUES LESS THAN (2022)
);
GROUP BY
查詢。SELECT department_id, COUNT(*) FROM employees GROUP BY department_id;
SELECT name FROM employees WHERE department_id IN (1, 2, 3, 4, 5);
CREATE TEMPORARY TABLE temp_ids (id INT);
INSERT INTO temp_ids (id) VALUES (1), (2), (3), (4), (5);
SELECT e.name FROM employees e JOIN temp_ids t ON e.department_id = t.id;
LOCK IN SHARE MODE
)。SELECT * FROM employees WHERE id = 10 FOR UPDATE;
INSERT INTO SELECT
語句中使用索引,提高性能。INSERT INTO employees_backup (id, name) SELECT id, name FROM employees WHERE hire_date < '2020-01-01';
innodb_buffer_pool_size
)來匹配查詢需求。這些技巧可以幫助大多數(shù)SQL查詢在不同場景下提高性能,但每種數(shù)據(jù)庫和業(yè)務場景都有其特定的優(yōu)化需求,因此調(diào)優(yōu)時應根據(jù)實際情況靈活應用。
以下是 更復雜的情況 SQL 優(yōu)化技巧
高級SQL優(yōu)化技巧通常涉及到復雜的數(shù)據(jù)庫結構、查詢計劃的深入理解、并發(fā)控制和事務處理等領域。以下是更復雜的SQL優(yōu)化技巧和相關案例,適用于大型數(shù)據(jù)庫和復雜查詢場景。
SELECT e.name, d.name
FROM employees e JOIN departments d
ON e.department_id = d.id
WHERE e.location = 'New York';
location
相關的數(shù)據(jù)先在本地節(jié)點處理,再進行全局數(shù)據(jù)匯總,避免跨節(jié)點傳輸。SELECT * FROM orders WHERE customer_id = 10 AND product_id = 5;
customer_id
和product_id
的單列索引合并執(zhí)行。結合EXPLAIN分析,數(shù)據(jù)庫是否使用了索引合并功能。CUBE
和ROLLUP
進行多維聚合分析,減少多次單獨的GROUP BY
操作。GROUP BY
分析 SELECT department_id, SUM(sales) FROM sales_data GROUP BY department_id;
SELECT region, SUM(sales) FROM sales_data GROUP BY region;
ROLLUP
進行多層次的聚合分析,減少多次查詢 SELECT department_id, region, SUM(sales) FROM sales_data
GROUP BY department_id, region WITH ROLLUP;
ROW_NUMBER()
、RANK()
、LAG()
、LEAD()
)進行復雜分析,避免自連接或嵌套查詢。 SELECT a.*, (SELECT sales FROM sales_data b WHERE b.id = a.id - 1) AS previous_sales
FROM sales_data a;
SELECT id, sales, LAG(sales, 1) OVER (ORDER BY id) AS previous_sales
FROM sales_data;
SELECT * FROM transactions WHERE transaction_date BETWEEN '2023-01-01' AND '2023-01-31';
CREATE TABLE transactions (
id INT,
amount DECIMAL(10, 2),
transaction_date DATE
)
PARTITION BY RANGE (YEAR(transaction_date)) (
PARTITION p2023 VALUES LESS THAN (2024)
);
CREATE TEMPORARY TABLE temp_sales AS
SELECT department_id, SUM(sales) FROM sales_data GROUP BY department_id;
WITH temp_sales AS (
SELECT department_id, SUM(sales) FROM sales_data GROUP BY department_id
)
SELECT * FROM temp_sales;
SELECT SUM(sales) FROM sales_data;
ALTER SESSION ENABLE PARALLEL QUERY;
SELECT /*+ PARALLEL(sales_data, 4) */ SUM(sales) FROM sales_data;
SELECT department_id, SUM(sales) FROM sales_data GROUP BY department_id;
CREATE MATERIALIZED VIEW mv_sales_data AS
SELECT department_id, SUM(sales) AS total_sales FROM sales_data GROUP BY department_id;
SELECT * FROM orders WHERE status = 'pending' FOR UPDATE;
SELECT * FROM orders WHERE order_id = 123 FOR UPDATE;
BEGIN;
UPDATE accounts SET balance = balance - 100 WHERE account_id = 1;
UPDATE accounts SET balance = balance + 100 WHERE account_id = 2;
COMMIT;
BEGIN;
UPDATE accounts SET balance = balance - 100 WHERE account_id = 1;
COMMIT;
BEGIN;
UPDATE accounts SET balance = balance + 100 WHERE account_id = 2;
COMMIT;
這些高級技巧需要結合具體的數(shù)據(jù)庫環(huán)境(如MySQL、PostgreSQL、Oracle等)進行細化和測試,同時也需要對數(shù)據(jù)庫的執(zhí)行計劃和鎖定機制有深入的理解。關注威哥愛編程,跟技術死磕到底。
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