1. Numerical auxiliary table
Numerical auxiliary table is a simple table containing only N integers from 1 to N. N is usually very large. The numeric auxiliary table is a very powerful tool, so we create a persistent numeric auxiliary table:
CREATETABLENums( a INTUNSIGNED NOTNULLPRIMARYKRY )ENGINE=InnoDB; CREATEPRODURE CreateNums (t INTUNSIGNED ) BEGIN DECLAREs INTUNSIGNED DEFAULT1; TRUNCATETABLENums; INSERTINTONums SELECTs; WHILE s*2 <= t DO BEGIN INSERTINTONums SELECTa+s FROMNums; SETs = s*2 END; ENDWHILE; END;
2. Continuous range
CREATETABLEt (a INTUNSIGNED NOTNULLPRIMARYKEY); INSERTINTOt VALUES(1); INSERTINTOt VALUES(2); INSERTINTOt VALUES(3); INSERTINTOt VALUES(100); INSERTINTOt VALUES(101); INSERTINTOt VALUES(103); INSERTINTOt VALUES(104); INSERTINTOt VALUES(105);
How to get the following output result?
SELECTMIN(a) start,MAX(a) endFROM( SELECTa,rn,a-rn ASdiff FROM(SELECTa,@a:=@a+1 rn FROMt,(SELECT@a:=0) ASa) ASb )ASc GROUPBYdiff;
3. Minimum missing value
Click (here) to collapse or open
CREATETABLEx( a INTUNSIGNED PRIMARYKEY, b CHAR(1) NOTNULL )ENGINE = InnoDB; INSERTINTOx SELECT3,'a'; INSERTINTOx SELECT4,'b'; INSERTINTOx SELECT6,'c'; INSERTINTOx SELECT7,'d';
Note that column a must be a positive integer, so the type here is INT UNSGINED. The problem with minimum missing values is that assuming column a starts at 1, for data 3, 4, 6, 7 in the current table, the query should return 1. If the data in the current table is 1, 2, 3, 4, 6, 7, then 5 is returned.
The solution is as follows:
SELECT CASE WHENNOTEXISTS (SELECTa FROMx WHEREa=1)THEN1 ELSE (SELECTMIN(a)+1 ASmissing FROMx ASA WHERENOTEXISTS (SELECT* FROMx ASB WHEREA.a+1=B.a)) ENDASmissing;
Run the above SQL and get the result 1. If you insert 1 and 2 into column a, the result will be 5.
To fill in the minimum missing value, the solution is as follows:
INSERTINTOx SELECT CASE WHENNOTEXISTS (SELECTa FROMx WHEREa=1)THEN1 ELSE (SELECTMIN(a)+1 ASmissing FROMx ASA WHERENOTEXISTS (SELECT* FROMx ASB WHEREA.a+1=B.a)) ENDASmissing, 'p';
Run the above SQL, we will insert 5 in column a and 'p' in column b.
4. Get the row number
The row number refers to the consecutive integer assigned to the rows of the query result set in order.
CREATETABLEsales ( empid varchar(10) NOTNULL, mgrid varchar(10) NOTNULL, qty` int(11) NOTNULL, PRIMARYKEY(empid) ); INSER INTOsalses VALUES('A',Z',300); INSER INTO salses VALUES('B',X',100); INSER INTOsalses VALUES('C',Y',100); INSER INTO salses VALUES('D',Z',300); INSER INTOsalses VALUES('E',X',200); INSER INTO salses VALUES('F',Z',100);
Now we perform line number statistics based on empid
SELECTempid, (SELECTCOUNT(*) FROMsales AST2 WHERET2.empid <= T1.empid) ASrownum FROMsales AST1;

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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