MySQL supports transaction processing, and uses the InnoDB storage engine to ensure data consistency and integrity. 1. Transactions are a set of SQL operations, either all succeed or all fail to roll back; 2. ACID attributes include atomicity, consistency, isolation and persistence; 3. The statements that manually control transactions are STARTTRANSACTION, COMMIT and ROLLBACK; 4. The four isolation levels include read not committed, read submitted, repeatable read and serialization; 5. Use transactions correctly to avoid long-term operation, turn off automatic commits, and reasonably handle locks and exceptions. Through these mechanisms, MySQL can achieve high reliability and concurrent control.

Character set and sorting rules issues are common when cross-platform migration or multi-person development, resulting in garbled code or inconsistent query. There are three core solutions: First, check and unify the character set of database, table, and fields to utf8mb4, view through SHOWCREATEDATABASE/TABLE, and modify it with ALTER statement; second, specify the utf8mb4 character set when the client connects, and set it in connection parameters or execute SETNAMES; third, select the sorting rules reasonably, and recommend using utf8mb4_unicode_ci to ensure the accuracy of comparison and sorting, and specify or modify it through ALTER when building the library and table.

To design a reliable MySQL backup solution, 1. First, clarify RTO and RPO indicators, and determine the backup frequency and method based on the acceptable downtime and data loss range of the business; 2. Adopt a hybrid backup strategy, combining logical backup (such as mysqldump), physical backup (such as PerconaXtraBackup) and binary log (binlog), to achieve rapid recovery and minimum data loss; 3. Test the recovery process regularly to ensure the effectiveness of the backup and be familiar with the recovery operations; 4. Pay attention to storage security, including off-site storage, encryption protection, version retention policy and backup task monitoring.

CTEs are a feature introduced by MySQL8.0 to improve the readability and maintenance of complex queries. 1. CTE is a temporary result set, which is only valid in the current query, has a clear structure, and supports duplicate references; 2. Compared with subqueries, CTE is more readable, reusable and supports recursion; 3. Recursive CTE can process hierarchical data, such as organizational structure, which needs to include initial query and recursion parts; 4. Use suggestions include avoiding abuse, naming specifications, paying attention to performance and debugging methods.

MySQL query performance optimization needs to start from the core points, including rational use of indexes, optimization of SQL statements, table structure design and partitioning strategies, and utilization of cache and monitoring tools. 1. Use indexes reasonably: Create indexes on commonly used query fields, avoid full table scanning, pay attention to the combined index order, do not add indexes in low selective fields, and avoid redundant indexes. 2. Optimize SQL queries: Avoid SELECT*, do not use functions in WHERE, reduce subquery nesting, and optimize paging query methods. 3. Table structure design and partitioning: select paradigm or anti-paradigm according to read and write scenarios, select appropriate field types, clean data regularly, and consider horizontal tables to divide tables or partition by time. 4. Utilize cache and monitoring: Use Redis cache to reduce database pressure and enable slow query

TooptimizecomplexJOINoperationsinMySQL,followfourkeysteps:1)EnsureproperindexingonbothsidesofJOINcolumns,especiallyusingcompositeindexesformulti-columnjoinsandavoidinglargeVARCHARindexes;2)ReducedataearlybyfilteringwithWHEREclausesandlimitingselected

MySQL's EXPLAIN is a tool used to analyze query execution plans. You can view the execution process by adding EXPLAIN before the SELECT query. 1. The main fields include id, select_type, table, type, key, Extra, etc.; 2. Efficient query needs to pay attention to type (such as const, eq_ref is the best), key (whether to use the appropriate index) and Extra (avoid Usingfilesort and Usingtemporary); 3. Common optimization suggestions: avoid using functions or blurring the leading wildcards for fields, ensure the consistent field types, reasonably set the connection field index, optimize sorting and grouping operations to improve performance and reduce capital

The aggregation function is used to perform calculations on a set of values ??and return a single value. Common ones include COUNT, SUM, AVG, MAX, and MIN; GROUPBY groups data by one or more columns and applies an aggregation function to each group. For example, GROUPBYuser_id is required to count the total order amount of each user; SELECTuser_id, SUM(amount)FROMordersGROUPBYuser_id; non-aggregated fields must appear in GROUPBY; multiple fields can be used for multi-condition grouping; HAVING is used instead of WHERE after grouping; application scenarios such as counting the number of classified products, maximum ordering users, monthly sales trends, etc. Mastering these can effectively solve the number