很多人用不同的东西来解决易语言难题,咱也凑个热闹。如果用存储过程的话,和一般的编程语言也就雷同了,这里就用SQL的思想,在MySQL中实现一次。 MySQL drop table if exists n1;create temporary table n1(num int (1));insert into n1 values(1), (2), (3)
很多人用不同的东西来解决易语言难题,咱也凑个热闹。如果用存储过程的话,和一般的编程语言也就雷同了,这里就用SQL的思想,在MySQL中实现一次。MySQL
drop table if exists n1; create temporary table n1(num int (1)); insert into n1 values(1), (2), (3), (4), (5), (6), (7), (8), (9); drop table if exists n2; create temporary table n2 select * from n1; drop table if exists n3; create temporary table n3 select * from n1; drop table if exists nums1; create temporary table nums1 select n1.num * 100 + n2.num * 10 + n3.num as num from n1 left join n2 on n1.num <> n2.num left join n3 on n1.num <> n3.num and n2.num <> n3.num; drop table if exists nums2; create temporary table nums2 select * from nums1; drop table if exists nums3; create temporary table nums3 select * from nums1; select * from nums1 as n1 left join nums2 as n2 on n1.num <> n2.num left join nums3 as n3 on n1.num <> n3.num and n2.num <> n3.num where n1.num * 2 = n2.num and n1.num * 3 = n3.num and n1.num not rlike concat("[", n2.num, "]") and n1.num not rlike concat("[", n3.num, "]") and n2.num not rlike concat("[", n3.num, "]"); drop table if exists n1; drop table if exists n2; drop table if exists n3; drop table if exists nums1; drop table if exists nums2; drop table if exists nums3; 结果: mysql> select * -> from nums1 as n1 left join nums2 as n2 -> on n1.num <> n2.num -> left join nums3 as n3 -> on n1.num <> n3.num and n2.num <> n3.num -> where n1.num * 2 = n2.num and n1.num * 3 = n3.num -> and n1.num not rlike concat("[", n2.num, "]") -> and n1.num not rlike concat("[", n3.num, "]") -> and n2.num not rlike concat("[", n3.num, "]"); +------+------+------+ | num | num | num | +------+------+------+ | 192 | 384 | 576 | | 219 | 438 | 657 | | 273 | 546 | 819 | | 327 | 654 | 981 | +------+------+------+ 4 rows in set (0.03 sec)

MySQL'sBLOBissuitableforstoringbinarydatawithinarelationaldatabase,whileNoSQLoptionslikeMongoDB,Redis,andCassandraofferflexible,scalablesolutionsforunstructureddata.BLOBissimplerbutcanslowdownperformancewithlargedata;NoSQLprovidesbetterscalabilityand

ToaddauserinMySQL,use:CREATEUSER'username'@'host'IDENTIFIEDBY'password';Here'showtodoitsecurely:1)Choosethehostcarefullytocontrolaccess.2)SetresourcelimitswithoptionslikeMAX_QUERIES_PER_HOUR.3)Usestrong,uniquepasswords.4)EnforceSSL/TLSconnectionswith

ToavoidcommonmistakeswithstringdatatypesinMySQL,understandstringtypenuances,choosetherighttype,andmanageencodingandcollationsettingseffectively.1)UseCHARforfixed-lengthstrings,VARCHARforvariable-length,andTEXT/BLOBforlargerdata.2)Setcorrectcharacters

MySQloffersechar, Varchar, text, Anddenumforstringdata.usecharforfixed-Lengthstrings, VarcharerForvariable-Length, text forlarger text, AndenumforenforcingdataAntegritywithaetofvalues.

Optimizing MySQLBLOB requests can be done through the following strategies: 1. Reduce the frequency of BLOB query, use independent requests or delay loading; 2. Select the appropriate BLOB type (such as TINYBLOB); 3. Separate the BLOB data into separate tables; 4. Compress the BLOB data at the application layer; 5. Index the BLOB metadata. These methods can effectively improve performance by combining monitoring, caching and data sharding in actual applications.

Mastering the method of adding MySQL users is crucial for database administrators and developers because it ensures the security and access control of the database. 1) Create a new user using the CREATEUSER command, 2) Assign permissions through the GRANT command, 3) Use FLUSHPRIVILEGES to ensure permissions take effect, 4) Regularly audit and clean user accounts to maintain performance and security.

ChooseCHARforfixed-lengthdata,VARCHARforvariable-lengthdata,andTEXTforlargetextfields.1)CHARisefficientforconsistent-lengthdatalikecodes.2)VARCHARsuitsvariable-lengthdatalikenames,balancingflexibilityandperformance.3)TEXTisidealforlargetextslikeartic

Best practices for handling string data types and indexes in MySQL include: 1) Selecting the appropriate string type, such as CHAR for fixed length, VARCHAR for variable length, and TEXT for large text; 2) Be cautious in indexing, avoid over-indexing, and create indexes for common queries; 3) Use prefix indexes and full-text indexes to optimize long string searches; 4) Regularly monitor and optimize indexes to keep indexes small and efficient. Through these methods, we can balance read and write performance and improve database efficiency.


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