The efficient data structure and algorithm implementation of the Fastutil framework
The Fastutil framework is an open source framework that provides high -efficiency data structures and algorithms in Java.When dealing with large -scale datasets, it can provide solutions that are faster and more saved than Java standard libraries.This article will introduce some commonly used high -efficiency data structures and algorithms in the FastUtil frame, and provide the corresponding Java code example.
1. Efficient data structure:
The Fastutil framework provides many efficient data structures. These data structures are more efficient than the realization of the Java standard library when processing large -scale data.Here are some commonly used examples of efficient data structure:
1.1. IntarrayList: This is an integer array implemented using a dynamic array.Compared with ArrayList in the Java Standard Library, IntarrayList provides faster reading and writing performance and smaller memory overhead.Here are a sample code that uses IntarrayList:
import it.unimi.dsi.fastutil.ints.IntArrayList;
public class IntArrayListExample {
public static void main(String[] args) {
IntArrayList list = new IntArrayList();
// Add elements
list.add(1);
list.add(2);
list.add(3);
// Traversing elements
for (int i = 0; i < list.size(); i++) {
System.out.println(list.getInt(i));
}
}
}
1.2. Int2intOpenhashmap: This is a plastic key value pair table implemented using an open address method.Compared with the HashMap in the Java Standard Library, IntopopenhashMap has smaller memory occupation and faster access speed under large -scale data sets.The following is an example code that uses Int2intopenhashMap:
import it.unimi.dsi.fastutil.ints.Int2IntOpenHashMap;
public class Int2IntOpenHashMapExample {
public static void main(String[] args) {
Int2IntOpenHashMap map = new Int2IntOpenHashMap();
// Add key value pair
map.put(1, 10);
map.put(2, 20);
map.put(3, 30);
// Traversing key value pair
map.forEach((key, value) -> System.out.println(key + ": " + value));
}
}
2. Efficient algorithm:
The Fastutil framework provides some efficient algorithm implementation. These algorithms are more efficient than the algorithm of the Java standard library when processing large -scale data.Here are some commonly used examples of high -efficiency algorithms:
2.1. Intarrays: This class provides some common integer array operations, such as sorting, searching, etc.Here are a sample code that uses Intarray for sorting:
import it.unimi.dsi.fastutil.ints.IntArrays;
public class IntArraysExample {
public static void main(String[] args) {
int[] array = {3, 1, 2};
// Sort the array
IntArrays.quickSort(array);
// Output sort results
for (int i = 0; i < array.length; i++) {
System.out.println(array[i]);
}
}
}
2.2. Object2DOBLERBTREEMAP: This class is a mapping table between the object key and dual -precision floating point value implemented by red and black trees.The following is an example code using Object2DoubleeMap:
import it.unimi.dsi.fastutil.objects.Object2DoubleRBTreeMap;
public class Object2DoubleRBTreeMapExample {
public static void main(String[] args) {
Object2DoubleRBTreeMap<String> map = new Object2DoubleRBTreeMap<>();
// Add key value pair
map.put("apple", 2.5);
map.put("banana", 1.8);
map.put("orange", 3.2);
// Traversing key value pair
map.forEach((key, value) -> System.out.println(key + ": " + value));
}
}
These are just part of the high -efficiency data structure and algorithm examples provided by the FastUtil framework. Developers can choose the appropriate data structure and algorithm according to their needs.Using the FastUtil frame can improve the performance and efficiency of large -scale data processing, and is particularly suitable for application scenarios that need to process a large amount of data.
