Application of Solong Collections framework technical principles in the Java class library
Application of Solong Collections framework technical principles in the Java class library
Overview:
Solong Collections is a Java framework for handling large data sets.The design goal of this framework is to provide efficient data processing and analysis functions, and reduce memory occupation and improve performance.Solong Collections framework can save memory and time when using a specific data structure and algorithm to save memory and time when processing large -scale data sets.
Application in the Java library:
The technical principles of the Solong Collections framework are widely used in the Java class library.Here are some common application scenarios and Java code examples:
1. Efficient data filtering:
Using Solong Collections framework, we can perform efficient filtering operations on large data sets to meet specific conditions.For example, we can use the Filter method to filter a List containing integer, which only retains more than 10 elements.
import io.github.konohiroaki.slc.SlcList;
import java.util.List;
public class Main {
public static void main(String[] args) {
List<Integer> numbers = List.of(5, 10, 15, 20);
SlcList<Integer> slcList = SlcList.from(numbers);
SlcList<Integer> filteredList = slcList.filter(n -> n > 10);
System.out.println (FilteredList); // Output: [15, 20]
}
}
2. Memory optimization:
One of the design goals of the Solong Collections framework is to reduce memory occupation.The framework uses a data structure called Roaring Bitmaps, which can effectively compress and store a large amount of integer.This is particularly useful in applications containing a large amount of data.
import io.github.konohiroaki.slc.bitmap.RoaringBitmaps;
public class Main {
public static void main(String[] args) {
RoaringBitmaps bitSet = new RoaringBitmaps();
bitSet.add(1);
bitSet.add(100);
bitSet.add(1000);
bitSet.add(10000);
System.out.println (bitset.contains (1)); // Output: true
}
}
3. Parallel data processing:
The Solong Collections framework makes full use of the advantages of multi -core processors, which can be processed in parallel in the multi -threaded environment.This parallel performance improvement can significantly reduce the time for processing large -scale data sets.The following is an example of using multi -threaded parallel computing average.
import io.github.konohiroaki.slc.SlcList;
import java.util.List;
import java.util.stream.Collectors;
public class Main {
public static void main(String[] args) {
List<Integer> numbers = List.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
SlcList<Integer> slcList = SlcList.from(numbers);
double average = slcList.parallelStream()
.mapToInt(Integer::intValue)
.average()
.getAsDouble();
System.out.println (AVERAGE); // Output: 5.5
}
}
Summarize:
The technical principles of Solong Collections framework are widely used in the Java library.It provides efficient data processing and analysis functions by using specific data structures and algorithms.In addition, this framework also improves the processing speed of large -scale data sets by reducing the advantages of memory occupation and using parallel processing.In big data applications, using Solong Collections framework can significantly improve performance and efficiency.
