Java Framework Performance Optimization FAQs

Java Framework Performance Optimization FAQ

Introduction

In high concurrency and data throughput In high-volume systems, performance optimization of the Java framework is crucial. This article explores some common performance optimization problems and their corresponding solutions.

1. Database connection management

Problem: The application creates too many database connections, causing resource exhaustion.

Solution: Use a connection pool to manage database connections. It can reuse connections and avoid frequent creation and destruction of connections.

import java.sql.DriverManager;
import javax.sql.DataSource;
import com.jolbox.bonecp.BoneCPDataSource;

public class DatabaseConnectionPool {
  private static DataSource dataSource;

  public static DataSource getDataSource() {
    if (dataSource == null) {
      BoneCPDataSource cpds = new BoneCPDataSource();
      cpds.setJdbcUrl("jdbc:mysql://localhost:3306/mydatabase");
      cpds.setUser("root");
      cpds.setPassword("password");
      cpds.setMinConnectionsPerPartition(5);
      cpds.setMaxConnectionsPerPartition(20);
      dataSource = cpds;
    }
    return dataSource;
  }
}

2. Object cache

Problem: The application frequently creates objects, causing performance overhead.

Solution: Use caching technology to store frequently used objects to avoid repeated creation.

import java.util.HashMap;
import java.util.Map;

public class ObjectCache {
  private static Map<String, Object> cache = new HashMap<>();

  public static Object get(String key) {
    return cache.get(key);
  }

  public static void put(String key, Object value) {
    cache.put(key, value);
  }
}

3. Lazy loading

Problem:The application loads all data at once, occupying a lot of memory.

Solution: Use lazy loading technology to load data only when needed.

import org.hibernate.annotations.LazyCollection;
import org.hibernate.annotations.LazyCollectionType;

@Entity
public class Order {
  @Id
  @GeneratedValue
  private Long id;

  @LazyCollection(LazyCollectionType.EXTRA)
  private List<OrderItem> items;
}

4. Lazy loading of collections using Select In

Problem: When using Hibernate to lazily load collections, it causes N+1 query problems.

Solution: Use Hibernate's @BatchSize annotation to specify the maximum number of collection elements that can be loaded in one query, or optimize through the select in statement Inquire.

@Entity
public class Order {
  @Id
  @GeneratedValue
  private Long id;

  @BatchSize(size = 10)
  private List<OrderItem> items;
}

5. Redis as a cache

Problem:Using memory cache (such as Ehcache) as a cache results in data loss or inconsistency.

Solution: Use Redis as a persistent cache, which can avoid data loss and improve availability.

import redis.clients.jedis.Jedis;

public class RedisCache {
  private static Jedis jedis;

  public static void set(String key, String value) {
    jedis.set(key, value);
  }

  public static String get(String key) {
    return jedis.get(key);
  }
}

Practical case

Question: Highly concurrent transaction system for e-commerce websites.

Optimization measures:

• Use connection pool to manage database connections.
• Use Caffeine as a caching tool to cache popular product information.
• Use Redis as a persistent distributed cache to store shopping cart information and order information.

Through the above optimization measures, the concurrency performance and response time of the trading system have been significantly improved.

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