The performance comparison and test of the Underscore framework in the Java library
The performance comparison and test of the Underscore framework in the Java library
introduction:
UNDERSCORE is a Java class library for functional programming. It provides a series of functions and tools to simplify operations to simplify data structures such as collection and array.This article will compare the performance and test of the UNDERSCORE framework to evaluate its performance in different scenarios.
Frame introduction:
The UNDERSCORE framework is based on functional programming concepts and provides a series of functional tool methods to achieve operations and array operations.This framework has the characteristics of simple and easy -to -use, simple code, and functional style, which is popular with Java developers.
Performance comparison:
In order to evaluate the performance of the UNDERSCORE framework, we have selected several common collection operation scenarios, used the Underscore framework for processing, and compared with the traditional Java collection operation.
The following is an example code that uses the UNDERSCORE framework to filter operation:
import com.github.underscore.Predicate;
import com.github.underscore.Underscore;
public class Main {
public static void main(String[] args) {
Integer[] numbers = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
Predicate<Integer> isEven = number -> number % 2 == 0;
Integer[] evenNumbers = Underscore.<Integer>filter(numbers, isEven);
System.out.println ("even number:" + underscore.join (Evennumbers, ",");
}
}
In the above code, we used the `Filter` method of the Underscore framework to filter the array` numbers`, only the even number was retained, and the result was converted into a string output through the `Join` method.
Performance Testing:
We conducted performance tests on the above example code and several other commonly used operations (such as mapping, return, etc.) and compared with the traditional Java collection operation.The test uses data sets of different sizes, and repeatedly executes, and the average execution time is calculated.
The following is an example of the performance test code of filtering using the UNDERSCORE framework and the traditional Java collection operation:
import com.github.underscore.Predicate;
import com.github.underscore.Underscore;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class Main {
public static void main(String[] args) {
Integer[] numbers = new Integer[1000000];
for (int i = 0; i < 1000000; i++) {
numbers[i] = i;
}
Predicate<Integer> isEven = number -> number % 2 == 0;
long startTime = System.nanoTime();
Integer[] evenNumbers = Underscore.<Integer>filter(numbers, isEven);
long endTime = System.nanoTime();
System.out.println ("The execution time filtered with the Underscore framework:" + (Endtime -Starttime) + "NS");
List<Integer> numberList = new ArrayList<>(Arrays.asList(numbers));
startTime = System.nanoTime();
List<Integer> evenNumberList = new ArrayList<>();
for (Integer number : numberList) {
if (isEven.test(number)) {
evenNumberList.add(number);
}
}
endTime = System.nanoTime();
System.out.println ("" Endtime -Starttime) + "NS");
}
}
in conclusion:
By comparison and testing of the performance of the UNDERSCORE framework and the traditional Java collection operation, we can find that in most cases, the function operation method provided by the UNDERSCORE framework has high performance.Especially when processing large -scale datasets, the Underscore framework can complete the operation more efficiently.However, in a small number of data sets or some special scenarios, the traditional Java collection operation may still be competitive.
Although the UNDERSCORE framework is performing well in terms of performance, it is necessary to pay attention to the application of scenes and methods when using to avoid misuse or performance loss.
references:
1. [Underscore GitHub repository](https://github.com/javadev/underscore-java)
2. [Underscore Java Documentation](https://javadev.github.io/underscore-java/)
