Home Java javaTutorial Case sharing of database search optimization driven by Java technology

Case sharing of database search optimization driven by Java technology

Sep 18, 2023 am 09:24 AM
Database search java technology Optimization case sharing

Case sharing of database search optimization driven by Java technology

Java technology-driven database search optimization case sharing

Introduction:

With the development of the Internet and the arrival of the big data era, the use of databases As the frequency and scale continue to expand, the problem of database search efficiency has become increasingly prominent. Database search optimization is critical to improving system performance and user experience. This article will share some database search optimization cases based on Java technology and provide specific code examples to help readers better master this knowledge and skills.

1. Index Optimization

Database index is an important means to improve search speed. By properly creating and using indexes, the time complexity of queries can be greatly reduced. The following are some examples of practical index optimization cases:

  1. Use unique index: When a field has uniqueness requirements, you can create a unique index for the field. For example, in the users table, the user ID field is usually unique and a unique index can be created for this field.
CREATE UNIQUE INDEX idx_user_id ON user (user_id);
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  1. Multi-column joint index: When multiple fields participate in the search at the same time, a multi-column joint index can be created. For example, in the order table, user ID and order status usually participate in combined queries, and a joint index can be created to improve query efficiency.
CREATE INDEX idx_order_user_id_status ON order (user_id, status);
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  1. Use prefix index: When the field length is too long, you can index only the prefix of the field. For example, in the address data table, the length of the address field is long, and only the first few characters of the address field can be indexed.
CREATE INDEX idx_address_prefix ON address (address(10));
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  1. Be careful to avoid too many indexes: too many indexes not only take up storage space, but also increase the overhead of updates and insertions. Therefore, the fields and number of indexes to be created need to be chosen carefully.

2. SQL Optimization

In addition to index optimization, the optimization of SQL query statements is also an important means to improve database search efficiency. The following are some common SQL optimization case examples:

  1. Reduce the number of query fields: only select the required fields to avoid unnecessary field queries.
SELECT user_name, address FROM user;
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  1. Use the appropriate connection method: Choose the appropriate connection method according to actual needs, such as inner join, left join or right join.
SELECT user.user_name, order.order_id
FROM user
INNER JOIN order ON user.user_id = order.user_id;
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  1. Avoid using fuzzy queries: %LIKE% queries usually result in full table scans and can be replaced by prefix matching or full-text search.
SELECT user_name FROM user WHERE user_name LIKE '张%';
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  1. Use appropriate aggregation functions: avoid using too many aggregate functions that require large calculations, such as MAX, MIN, etc.
SELECT COUNT(*) FROM user;
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3. Connection pool optimization

The connection pool is introduced to reduce the cost of creating and destroying database connections. Properly configuring the connection pool can improve database search efficiency and avoid frequent creation and destruction of connections. The following are some common connection pool optimization case examples:

  1. Adjust the size of the connection pool appropriately: adjust the maximum number of connections and the minimum number of idle connections of the connection pool according to the load of the system and the performance of the database.
int maxTotal = 100; // 最大连接数
int maxIdle = 20; // 最大空闲连接数

GenericObjectPoolConfig poolConfig = new GenericObjectPoolConfig();
poolConfig.setMaxTotal(maxTotal);
poolConfig.setMaxIdle(maxIdle);

DataSource dataSource = new PoolingDataSource(poolConfig);
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  1. Configure the connection timeout: To avoid the connection not being released for a long time, you can configure the maximum idle time and maximum connection waiting time of the connection.
int maxIdleTime = 1800; // 最大空闲时间,单位:秒
int maxWaitTime = 5000; // 最大连接等待时间,单位:毫秒

poolConfig.setMinEvictableIdleTimeMillis(maxIdleTime * 1000L);
poolConfig.setMaxWaitMillis(maxWaitTime);
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  1. Reasonably utilize the connection verification function of the connection pool: By configuring appropriate verification query statements, you can avoid using invalid or failed connections.
String validationQuery = "SELECT 1";

poolConfig.setTestOnBorrow(true);
poolConfig.setValidationQuery(validationQuery);
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Conclusion:

This article shares some database search optimization cases based on Java technology and provides specific code examples. By properly optimizing indexes, SQL query statements, and connection pools, database search efficiency can be greatly improved, and system performance and user experience can be improved. I hope it will be helpful to readers for database search optimization. At the same time, we also hope that readers can flexibly use these optimization techniques according to actual conditions in practical applications, and continue to explore and improve.

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