Identify complex structures such as subqueries, related queries, and aggregate functions in SQL

Identify multi-table joins, sorting, grouping and other operations in SQL

Break complex SQL into multiple simple single-table queries

Reduce operations such as multi-table joins, sorting, and grouping

Use index

Reduce data volume

Optimize query conditions

Use operations such as UNION and UNION ALL to merge single table query results

Avoid using JOIN operations to combine results

Reduce the amount of data in merged results

Optimize sorting, grouping and other operations of merged results;

View execution plan

Analyze index usage

Check data distribution

Suitable for most scenarios

Applies to unique value fields

Suitable for multiple field combinations

Suitable for spatial data

Good for text search

Advantages: Reduce the number of table query times and improve query efficiency

Disadvantages: It may cause the index to be too large, affecting write performance

Select frequently used columns in query statements as index columns

Select columns with high distinction as index columns

Combine multiple columns into a composite index

Composite indexes can improve query efficiency and reduce the number of indexes

Function operations may cause index failure

Type conversion may cause index failure

Calculation may cause index failure

Fuzzy queries may cause index failure

Sorting may cause index failure

Pagination may cause index failure

Aggregation may cause index failure;

Make sure the query criteria fields are indexed

Avoid using functions or operators, which may cause index failure

Use LIMIT to limit the amount of data returned

Filter data using the WHERE clause

Use JOIN statement instead of subquery

Use the EXISTS clause instead of a subquery

Use UNION instead of OR condition

Use IN instead of OR conditions

Using transactions for batch updates

Using stored procedures for batch updates

Avoid holding locks for long periods of time

Lower transaction isolation level

Reasons for data carry forward

How data is carried forward

Direct copying is suitable for small data volumes

Export and import are suitable for large amounts of data

Database connection works with real-time data

Increase network bandwidth

Optimize database queries

Optimize data format

Use encrypted transmission

Restrict access

Use transaction processing

Back up data regularly;

Column redundancy can reduce the number of connections and increase query speed

The more disk I/O times, the slower the query speed.

Column redundancy can reduce disk I/O and increase query speed

Column redundancy can reduce query complexity and improve query speed

Column redundancy can improve query performance and increase query speed;

Split according to business functions

Can be maintained independently after splitting

Reduce coupling

Split by data range

Improve query performance

Reduce data redundancy

Avoid over-splitting

Reduce maintenance costs

Improve query performance

Reduce hardware costs

Reduce data inconsistency

Improve data accuracy

Reduce data coupling

Improve data maintainability;