OLTPisusedforreal-timetransactionprocessing,highconcurrency,anddataintegrity,whileOLAPisusedfordataanalysis,reporting,anddecision-making.1)UseOLTPforapplicationslikebankingsystems,e-commerceplatforms,andCRMsystemsthatrequirequickandaccuratetransactio

Toduplicateatable'sstructurewithoutcopyingitscontentsinSQL,use"CREATETABLEnew_tableLIKEoriginal_table;"forMySQLandPostgreSQL,or"CREATETABLEnew_tableASSELECT*FROMoriginal_tableWHERE1=2;"forOracle.1)Manuallyaddforeignkeyconstraintsp

To improve pattern matching techniques in SQL, the following best practices should be followed: 1. Avoid excessive use of wildcards, especially pre-wildcards, in LIKE or ILIKE, to improve query efficiency. 2. Use ILIKE to conduct case-insensitive searches to improve user experience, but pay attention to its performance impact. 3. Avoid using pattern matching when not needed, and give priority to using the = operator for exact matching. 4. Use regular expressions with caution, as they are powerful but may affect performance. 5. Consider indexes, schema specificity, testing and performance analysis, as well as alternative methods such as full-text search. These practices help to find a balance between flexibility and performance, optimizing SQL queries.

IF/ELSE logic is mainly implemented in SQL's SELECT statements. 1. The CASEWHEN structure can return different values ??according to the conditions, such as marking Low/Medium/High according to the salary interval; 2. MySQL provides the IF() function for simple choice of two to judge, such as whether the mark meets the bonus qualification; 3. CASE can combine Boolean expressions to process multiple condition combinations, such as judging the "high-salary and young" employee category; overall, CASE is more flexible and suitable for complex logic, while IF is suitable for simplified writing.

The method of obtaining the current date and time in SQL varies from database system. The common methods are as follows: 1. MySQL and MariaDB use NOW() or CURRENT_TIMESTAMP, which can be used to query, insert and set default values; 2. PostgreSQL uses NOW(), which can also use CURRENT_TIMESTAMP or type conversion to remove time zones; 3. SQLServer uses GETDATE() or SYSDATETIME(), which supports insert and default value settings; 4. Oracle uses SYSDATE or SYSTIMESTAMP, and pay attention to date format conversion. Mastering these functions allows you to flexibly process time correlations in different databases

The DISTINCT keyword is used in SQL to remove duplicate rows in query results. Its core function is to ensure that each row of data returned is unique and is suitable for obtaining a list of unique values ??for a single column or multiple columns, such as department, status or name. When using it, please note that DISTINCT acts on the entire row rather than a single column, and when used in combination with multiple columns, it returns a unique combination of all columns. The basic syntax is SELECTDISTINCTcolumn_nameFROMtable_name, which can be applied to single column or multiple column queries. Pay attention to its performance impact when using it, especially on large data sets that require sorting or hashing operations. Common misunderstandings include the mistaken belief that DISTINCT is only used for single columns and abused in scenarios where there is no need to deduplicate D

Create temporary tables in SQL for storing intermediate result sets. The basic method is to use the CREATETEMPORARYTABLE statement. There are differences in details in different database systems; 1. Basic syntax: Most databases use CREATETEMPORARYTABLEtemp_table (field definition), while SQLServer uses # to represent temporary tables; 2. Generate temporary tables from existing data: structures and data can be copied directly through CREATETEMPORARYTABLEAS or SELECTINTO; 3. Notes include the scope of action is limited to the current session, rename processing mechanism, performance overhead and behavior differences in transactions. At the same time, indexes can be added to temporary tables to optimize

The main difference between WHERE and HAVING is the filtering timing: 1. WHERE filters rows before grouping, acting on the original data, and cannot use the aggregate function; 2. HAVING filters the results after grouping, and acting on the aggregated data, and can use the aggregate function. For example, when using WHERE to screen high-paying employees in the query, then group statistics, and then use HAVING to screen departments with an average salary of more than 60,000, the order of the two cannot be changed. WHERE always executes first to ensure that only rows that meet the conditions participate in the grouping, and HAVING further filters the final output based on the grouping results.