Impact of Reflection on Object Creation Performance in Java
When developers utilize Java's reflection capabilities to instantiate objects, concerns often arise about the subsequent performance implications. To evaluate these concerns, let's examine whether creating objects using reflection rather than directly invoking the class constructor introduces significant performance differences.
According to Java's official documentation on reflection, there is indeed a notable performance impact. Since reflection involves dynamically resolving types, certain JVM optimizations cannot be applied. This leads to reflective operations being inherently slower compared to non-reflective counterparts.
To quantify this difference, consider the following code snippet:
public class Main { public static void main(String[] args) throws Exception { doRegular(); doReflection(); } public static void doRegular() throws Exception { long start = System.currentTimeMillis(); for (int i = 0; i < 1,000,000; i++) { A a = new A(); a.doSomeThing(); } System.out.println(System.currentTimeMillis() - start); } public static void doReflection() throws Exception { long start = System.currentTimeMillis(); for (int i = 0; i < 1,000,000; i++) { A a = (A) Class.forName("misc.A").newInstance(); a.doSomeThing(); } System.out.println(System.currentTimeMillis() - start); } } class A { public void doSomeThing() { // Perform some task } }
Executing this code on a Sun JRE 6u10 system yields the following results:
These results demonstrate a significant performance penalty when using reflection, which is attributed to the cost of performing runtime class lookups and instantiation.
Even if we optimize the reflection code by performing the class lookup only once before instantiating multiple objects, there is still a performance hit:
In conclusion, reflection in Java incurs a substantial performance overhead compared to direct constructor invocations. While there may be specific use cases where reflection is necessary, it is important to factor in the potential performance implications when considering its usage, especially in performance-critical applications.
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