Caching Method References for Performance Optimization in Java 8
In Java 8, method references provide a concise way to access methods dynamically. However, the question arises whether it's beneficial to cache method references at frequently called positions in the code.
Method Reference Caching
Caching method references means storing the method handle in a variable to avoid the overhead of generating a new handle each time the method is invoked. This is based on the assumption that the Java Virtual Machine (JVM) creates an anonymous class object for each method reference, which can be costly in high-frequency scenarios.
JVM Optimization
The JVM does optimize method reference caching to a certain extent. It maintains a cache of call sites, which are effectively the method handles of frequently used method references. For stateless method references, this optimization ensures that the same handle is reused across call sites.
Caching State-Aware Method References
Caching method references with state, such as non-static method references, is not as effective. The state associated with the method call requires the creation of a new lambda instance for each invocation, even when caching is used.
Caching Stateless Method References
Caching stateless method references, such as static method references, can provide a performance boost in certain scenarios:
General Best Practices
As a general rule, it's not recommended to manually cache method references in most cases. The JVM's optimizations are usually sufficient to handle performance concerns. However, in specific cases where performance profiling identifies a bottleneck related to frequent method handle creation, caching stateless method references at a single call site can be considered.
Conclusion
Caching method references for performance optimization in Java 8 is a complex topic with nuances related to method reference types and JVM behavior. While caching can be beneficial in specialized situations, it's important to assess the specific use case and measure the actual performance impact before implementing it.
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