Optimising Java Performance: Techniques and Tools

When working on Java applications, it’s essential to ensure that your code is not only clean and bug-free but also optimised for performance. Code optimization means that the execution time is within the expected limits, ensuring a smooth user experience. 

Adhering to Java coding standards and regularly reviewing your code are crucial steps in this process. However, due to tight deadlines, thorough reviews may not always be feasible. 

Here are 12 practical tips to keep in mind while coding, which can help you minimise performance issues during the testing phase or before moving to production.

1. Avoid Long Methods: Methods should be concise and focused on performing a single task. Long methods are harder to maintain and can negatively impact performance as they consume more stack memory and CPU cycles during execution. Breaking down large methods into smaller, logical units enhances readability and efficiency.
2. Minimise Multiple If-Else Statements: Excessive use of conditional statements can degrade performance, especially when used inside loops. Instead of multiple if-else statements, consider using boolean logic to simplify conditions or opt for switch statements where appropriate, as they offer better performance for multiple conditions.
3. Precompute Collection Sizes in Loops: When iterating over collections, avoid repeatedly querying the size of the collection within the loop. Instead, store the collection’s size in a variable before the loop begins. This approach reduces the overhead of size computations and improves loop performance.
4. Use StringBuilder for String Concatenation: Strings in Java are immutable, meaning each concatenation operation creates a new String object. This can lead to high memory usage and reduced performance. For efficient string concatenation, use StringBuilder or StringBuffer, with StringBuilder being preferred due to its non-synchronized nature.
5. Prefer Primitive Types Over Wrapper Classes: Primitive types (int, double, etc.) are stored on the stack and accessed faster than their corresponding wrapper classes (Integer, Double, etc.), which are stored on the heap. Whenever possible, use primitive types to improve performance.
6. Limit the Use of BigDecimal: Although BigDecimal provides precise control over decimal numbers, it is memory-intensive and slower than primitive types like long or double. Use BigDecimal only when high precision is required and consider alternatives for other cases.
7. Avoid Frequent Creation of Large Objects: Creating large objects repeatedly can consume significant memory and degrade performance. For objects like database connections or configuration settings, use the Singleton pattern to create a single instance that can be reused throughout the application.
8. Prefer Stored Procedures Over Inline Queries: Using stored procedures instead of complex inline SQL queries can enhance performance. Stored procedures are pre-compiled and stored as database objects, which reduces execution time and network traffic compared to inline queries.
9. Use PreparedStatement Instead of Statement: When executing parameterized SQL queries, PreparedStatement is more efficient than Statement. Prepared statements are compiled once and can be executed multiple times, which is faster and more secure against SQL injection attacks.
10. Optimize Logging Practices: Efficient logging is crucial for application performance. Avoid logging large objects and focus on specific parameters. Use appropriate log levels (DEBUG, ERROR) and avoid excessive INFO logging. This reduces I/O overhead and improves performance.
11. Select Only Required Columns in SQL Queries: Fetching unnecessary columns from the database increases query execution time and network traffic. Always select only the columns you need for processing or displaying, which optimizes query performance and reduces data transfer time.
12. Utilize Joins for Data Retrieval: Proper use of joins can significantly improve query performance when retrieving data from multiple tables. Avoid subqueries as they are slower compared to joins. Additionally, ensure tables are normalized and indexed to enhance query execution speed.

By following these tips, you can write optimised Java code that performs efficiently and minimises the need for extensive performance tuning during later stages of development.