**Index** is a special data structure in the database that helps the database management system (DBMS) quickly access specific information in the data table. The index is similar to the table of contents of a book and can speed up data retrieval.
2. The role of index
Improve query efficiency: Through indexes, the database system can quickly locate data in the table, reducing the need for full table scans.
Optimize data sorting and grouping: In sorting and grouping operations, indexes can significantly reduce the number of data comparisons and movements.
Ensure data uniqueness: By creating a unique index or primary key index, you can ensure the uniqueness of the data in the table.
Support efficient table joins: In queries involving multiple tables, indexes can speed up the join process between tables.
3. Classification of Indexes
SQL indexes can be classified according to different standards. Common classification methods include:
Classification by storage structure：
B-Tree Index: Including B-Tree and B+Tree, it is the most commonly used index type in the database.
Hash Index: Use hash functions to calculate the hash value of the index column to quickly locate data.
Full-text index: Used to search text content and supports complex query syntax.
Spatial index: Used to store geospatial data, such as coordinate data in a geographic information system (GIS).
Classification by function：
Normal index: The most basic index type, without any restrictions.
Unique Index: Requires that the values of the index column must be unique.
Primary key index: A special unique index used to uniquely identify each row of data in a table.
Composite Index: An index containing multiple columns, used to improve the performance of multi-column queries.
4. Advantages and disadvantages of indexes
advantage：
Improve query efficiency.
Optimize data sorting and grouping.
Supports efficient table joins.
Ensure the uniqueness of data.
shortcoming：
Increased I/O cost: Index files take up additional disk space and may increase the number of disk I/O operations.
Reduced write performance: When inserting, updating, or deleting data, the index also needs to be updated, which may reduce the performance of write operations.
Too many indexes may lead to poor performance: Inappropriate indexes or too many indexes may reduce the overall performance of the database.
5. Index usage scenarios
The use of indexes should be based on specific business needs and data characteristics. The following are some common usage scenarios:
Columns that frequently appear in query conditions.
The columns that participate in the sorting or grouping operation.
Columns that often participate in table joins.
Columns with high uniqueness requirements, such as user ID, email address, etc.
6. Index creation and maintenance
Create Index：
can useCREATE INDEXThe statement creates an index in the database. For example:
CREATEINDEX idx_name ON table_name (column_name);
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Deleting an Index：
When the index is no longer needed, you can useDROP INDEXstatement to delete it. For example:
DROPINDEX idx_name ON table_name;
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Maintaining Indexes：
Rebuild indexes regularly: As data is added and modified, the index may become fragmented, and regular rebuilding of the index can restore its performance.
Monitoring index usage: Monitor index usage through database management tools or SQL statements to promptly identify and resolve index-related issues.
7. Best Practices for Indexing
Create indexes only for columns you need: Avoid creating indexes for columns that are not frequently used or have a high duplication rate.
Consider using composite indexes: When the query conditions involve multiple columns, consider creating a composite index to improve query performance.
Avoid Over-Indexing: Although indexes can improve query performance, too many indexes will reduce the performance of write operations and increase storage space consumption.
Covering scan using index: Try to obtain the required data through indexes only, and avoid table queries.
The basic principle of indexing
data structure: Indexes usually use a data structure to store data, such as B-trees (the most common is B+ trees), hash tables, etc. These data structures allow database systems to find, insert, delete, and update data faster than full table scans.
Sorting and storage: When creating an index, the database sorts the data according to the values of the index columns and stores these values in the index structure. For balanced tree structures such as B-trees, this sorting and hierarchical storage method can ensure query efficiency.
Key-value pairs: Indexes are usually stored as key-value pairs, where the key is the value of the index column and the value is a pointer or row number pointing to the corresponding row in the table. In this way, when a query uses the index column, the database can quickly locate the physical location of the data.
The role of indexes
Speed up data retrieval: The main function of index is to speed up data retrieval. Through the index, the database can quickly locate the storage location of the data without scanning the entire table. This is especially important for tables with large data volumes.
Reduce I/O costs: The performance bottleneck of database operations (especially query operations) is often disk I/O. Indexes can significantly reduce the amount of data that needs to be read during the query process, thereby reducing I/O costs.
Support sorting and grouping: With an index, the database can perform sorting and grouping operations more efficiently because the index itself has already sorted the data.
Achieving data uniqueness: A unique index ensures that the values of the indexed column are unique in the table, which helps maintain data integrity and consistency.
Optimizing connection queries: In a join query involving multiple tables, an index can significantly reduce the number of rows that need to be compared and matched during the join process, thereby improving query efficiency.
Precautions
While indexes can significantly improve query performance, they also have their limitations:
Index maintenance costs: The index itself requires additional storage space, and when data is inserted, updated, and deleted, the index also needs to be updated accordingly, which will increase additional maintenance costs.
Query Optimizer: The database query optimizer will automatically choose whether to use an index and which index to use based on factors such as query conditions and table structure. Therefore, not all queries will use indexes.
Index selection: When designing an index, you need to carefully select index columns and index types to balance query performance and maintenance costs. Too many indexes may reduce data update performance and increase storage costs.
Different types of indexes have their own unique characteristics and applicable scenarios in the database. The following is a detailed analysis of the characteristics and applicable scenarios of several common index types:
1. General Index
Features：
The most basic index type, with no uniqueness restriction.
NULL values are allowed.
Cannot be referenced as a foreign key.
A table can have multiple normal indexes.
Applicable scene：
Used to speed up access and retrieval of data in the table, especially creating common indexes on columns with large data volumes and frequent queries, which can significantly improve query efficiency.
When the query conditions do not involve uniqueness requirements, ordinary indexes can be used.
2. Unique Index
Features：
Data columns do not allow duplication, but allow NULL values (but there can only be one NULL value in a table because NULL is treated as a special value in uniqueness comparison).
Cannot be referenced as a foreign key.
A table allows multiple columns to create unique indexes.
Applicable scene：
Used to ensure the uniqueness of data and avoid data duplication.
In scenarios where you need to ensure that the value of a column or a combination of columns is unique, using a unique index can ensure data accuracy.
When the query conditions involve uniqueness requirements, using a unique index can speed up the query.
3. Primary key index
Features：
A primary key index is a special unique index that not only requires the value of the data column to be unique, but also does not allow NULL.
Each table can have only one primary key index.
Primary key indexes can be referenced as foreign keys.
Applicable scene：
Used to uniquely identify each row of data in the table to ensure data integrity and consistency.
In scenarios where you need to quickly access specific rows in a table, using a primary key index can significantly improve query efficiency.
The primary key index is a very important aspect in table design and database optimization. It has a significant impact on the performance and maintainability of the database.
4. Composite Index
Features：
Use multiple columns to form an index.
Queries that include these columns can be more efficient, especially when these columns often appear together in query conditions.
The order of composite indexes is important because it affects the query optimizer's choice and use of indexes.
Applicable scene：
When the query conditions involve multiple columns, using a composite index can significantly reduce the amount of data that needs to be scanned and improve query efficiency.
In scenarios where multiple columns need to be queried, sorted, or filtered, composite indexes can be used to optimize query performance.
5. Other index types (such as full-text index)
Features：
A full-text index is a special type of index that is used to search for keywords in text data.
It differs from regular indexes in data structure and usage and is usually used in full-text search scenarios.
Applicable scene：
Applicable to keyword fuzzy search of massive data, such as the text search function in search engines.
When you need to perform complex searches in text fields (such as searches containing wildcards, synonym searches, and so on), full-text indexing can provide a more efficient solution.
Here are detailed steps on how to create, view, and delete indexes:
Create Index
There are many ways to create indexes, but they can be summarized as follows:
Specify the index when creating the table：
In useCREATE TABLEWhen creating a table using a statement, you can specify an index directly after the column definition. This includes primary key indexes, unique indexes, etc.
Example (assuming you create astudentstable, and inidCreate a primary key index on the column):
CREATETABLE students (
id INTAUTO_INCREMENTPRIMARYKEY,
name VARCHAR(100),
age INT,INDEX idx_name (name)-- 在name列上创建普通索引);
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Adding an index using the ALTER TABLE statement：
If the table already exists, you can useALTER TABLEStatement to add an index to a table.
Example (forstudentsTableageAdd a normal index to the column):
ALTERTABLE students ADDINDEX idx_age (age);
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Create an index using the CREATE INDEX statement：
Another way to create an index for an existing table is to useCREATE INDEXstatement.
Example (forstudentsTablenameandageCreate an index using a combination of columns):
CREATEINDEX idx_name_age ON students (name, age);
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View Index
The method for viewing indexes varies depending on the database system, but most databases provide corresponding commands or query methods to view index information.
Using the SHOW INDEX Command (MySQL)：
For MySQL database, you can useSHOW INDEXCommand to view the index information of the table.
Example:
SHOWINDEXFROM students;
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This will liststudentsAll index information of the table, including index name, column name, index type, etc.
Query the INFORMATION_SCHEMA.STATISTICS Table (MySQL)：
Another way to view the index is to queryINFORMATION_SCHEMA.STATISTICSTable. This table stores statistics for all tables in the database, including index information.
Using system views or functions (other database systems)：
For other database systems (such as SQL Server, Oracle, etc.), you may need to use system views or specific functions to view index information. For specific methods, please refer to the official documentation of the corresponding database.
Deleting an Index
Deleting an index also requires different methods depending on the database system.
Using DROP INDEX Command：
Most database systems support the use ofDROP INDEXcommand to delete the index.
Example (MySQL):
DROPINDEX idx_name ON students;
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Note: In some database systems (such as SQL Server),DROP INDEXThe command syntax may be slightly different, requiring the table and index names to be specified but without theONKeywords.
Using the ALTER TABLE Statement：
Another way to delete an index is to useALTER TABLEstatement.
Example (MySQL):
ALTERTABLE students DROPINDEX idx_age;
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Using database management tools：
In addition to using SQL commands, you can also use database management tools (such as MySQL Workbench, SQL Server Management Studio, etc.) to graphically create, view, and delete indexes. These tools usually provide a more intuitive operation interface and rich functional options.
Precautions
When creating, viewing, and deleting indexes, make sure you have sufficient understanding of your database system to avoid unnecessary errors and data loss.
Although indexes can improve query efficiency, they also take up extra storage space and may increase the overhead of data insertion, update, and deletion operations. Therefore, when creating indexes, you need to weigh and choose according to the actual situation.
Before deleting an index, make sure that the index is no longer used or that an alternative index solution has been created. Otherwise, deleting the index may result in degraded query performance.
Indexes have a significant impact on database performance, both positively and potentially negatively. The following is a detailed analysis:
positive influence
Speed up data retrieval：
Indexes can significantly speed up data retrieval. Through indexes, the database system can directly locate the location of the target data without having to scan the entire table one by one. This is especially important in large-scale data sets and can greatly improve query efficiency.
Indexes can also reduce the number of rows that the database scans, thereby reducing I/O costs because the database system can find the required data more quickly without having to read the entire table or a large number of irrelevant rows of data.
Improve database performance：
Using indexes can reduce the number of disk I/O operations of the database system, because indexes are usually stored in memory and can be accessed quickly. This helps improve the performance of the entire database system, especially when processing complex queries and large amounts of data.
Indexes can also optimize query plans, allowing the database system to perform query operations more efficiently. The query optimizer can use indexes to generate more efficient query plans, thereby improving query response time and throughput.
Ensure data uniqueness：
Unique indexes and primary key indexes can ensure the uniqueness of data in the database. This helps maintain data integrity and consistency and prevents data duplication and errors.
Potential negative effects
Increased storage space requirements：
Indexes require additional storage space. For large databases, the storage space occupied by indexes may be quite large, which will increase the storage cost of the database.
As the number of indexes increases, the overall storage requirements of the database will also increase accordingly. Therefore, when creating indexes, you need to weigh their impact on storage space.
Increased write cost：
Every time you insert, update, or delete data, the database system not only needs to modify the data itself, but also needs to update the corresponding index, which increases the overhead of the write operation and reduces the write performance.
In a high-concurrency write operation scenario, frequent index updates may become a performance bottleneck. Therefore, when designing an index, you need to consider its impact on write performance.
Reduce the efficiency of the query optimizer：
In some cases, indexes can cause the query optimizer to choose a suboptimal query plan. This may be because the presence of the index misleads the query optimizer when evaluating the query cost.
Therefore, when creating an index, you need to carefully consider whether it really helps optimize query performance and avoid creating redundant or unnecessary indexes.
Index maintenance costs：
Indexes require regular maintenance to maintain their performance. This includes operations such as rebuilding or reorganizing indexes, updating index statistics, etc. These operations require additional resources and time, and may have a short-term impact on database performance.
Database administrators need to have a certain level of technical skills to effectively manage indexes, including selecting appropriate index strategies, optimizing query performance, and regularly maintaining indexes.
When a column has an index but some of the data in it is deleted, the update of the index is usually handled automatically by the database management system (DBMS) without manual intervention by the user. The purpose of database indexes is to speed up data retrieval. They are closely related to the data in the table, but the index itself does not store data, but stores pointers or location information to the data in the table.
The following is a detailed description of how the index is automatically updated to reflect data deletion operations:
Automatic update mechanism of index
Data deletion operation：
When a user performs a data deletion operation (such as usingDELETEstatement), the DBMS will first remove the specified data rows from the table.
This deletion operation not only affects the data in the table, but also the indexes associated with the data.
Index Update：
When you delete rows from a table, the DBMS automatically updates all affected indexes.
For each deleted data row, the DBMS removes the corresponding index entry (i.e., the pointer or location information pointing to the data row) from the index.
This update is immediate, meaning that once a row is deleted from the table, the corresponding index entry is also removed immediately.
Performance Considerations：
Although automatic index updates ensure the consistency of index and table data, they may also have a certain impact on performance.
Especially when performing a large number of delete operations, updating the index may become a performance bottleneck.
Therefore, before performing a large number of delete operations, you may sometimes need to consider other strategies such as bulk delete, index rebuild, etc. to optimize performance.
Index Rebuild
If the deletion operation causes severe index fragmentation and affects query performance, you can consider rebuilding the index.
Index rebuilding is an operation to rebuild the index, which can eliminate index fragmentation and improve query performance.
In MySQL, you can useALTER TABLEStatement coordinationDROP INDEXandADD INDEXoption to rebuild the index. However, it should be noted that this process may temporarily lock the table and affect other query operations.
Manually updating indexes to reflect data deletion operations is usually not necessary in most database management systems (such as MySQL, PostgreSQL, SQL Server, etc.) because the database automatically maintains the consistency of the index. When you delete data from a table, the database automatically removes the corresponding index entry from the index.
However, in some cases, if the index becomes fragmented due to frequent data modifications (including inserts, updates, and deletes), query performance may be affected. At this time, you may want to manually intervene in the maintenance of the index, including rebuilding the index or optimizing the index. Although this does not directly "update" the index to reflect a single delete operation, it can improve the performance of the index as a whole.
Here are some manual index optimization methods that can indirectly reflect the impact of data deletion operations on indexes:
Rebuild Index：
useALTER TABLEstatement to drop and re-create the index. This eliminates fragmentation of the index and makes it more compact and efficient.
For example, in MySQL, you can use the following command to rebuild the index (assuming the index is namedidx_name, the table name isusers）：
Note: Rebuilding the index may temporarily lock the table and affect other query operations, so it is recommended to do it during off-peak hours.
Optimize Table：
useOPTIMIZE TABLEstatement to reorganize the physical storage of the table, including indexes. This can help reduce table fragmentation and possibly improve query performance.
For example, in MySQL, you can use the following command to optimize the table (assuming the table is namedusers）：
OPTIMIZETABLE users;
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Note: The process of optimizing a table may take some time and may also temporarily lock the table.
Analysis Table：
useANALYZE TABLEStatement to update table statistics, including index usage. This helps the database optimizer generate more efficient query plans.
For example, in MySQL, you can use the following command to analyze the table (assuming the table is namedusers）：
ANALYZETABLE users;
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Analyzing a table does not directly affect the physical structure of the index, but it can help the database make better use of the index.
Maintain indexes regularly：
Regularly check the fragmentation of your indexes and optimize or rebuild them as needed.
Consider using database management tools or scripts to automate the index maintenance process.
It is important to note that manually updating indexes to reflect individual data deletions is usually not necessary, as the database automatically handles this situation. However, it is important to regularly maintain indexes to ensure they remain in optimal condition, which can be achieved using the methods described above.
Furthermore, if you do need to manually intervene in indexes to reflect specific data changes (although this is rare), you may need to gain a deeper understanding of the inner workings of your database management system and consider using lower-level database maintenance commands or tools. In most cases, however, simply relying on the database's automatic index maintenance features is sufficient.
