Performance optimization techniques of Java class library moderate unit API framework
Performance optimization techniques of Java class library moderate unit API framework
introduction:
The API framework of the measurement unit is one of the components commonly used in the Java class library. It provides a standardized way to handle the conversion and calculation of the unit.However, performance may become an important consideration when dealing with a large measurement unit operation.This article will introduce some performance optimization techniques for the API framework for the medium weight unit of the Java library, and demonstrate how to improve performance through instance code.
1. Avoid creating duplicate measuring unit objects
In the API framework of the measurement unit, the measurement unit object is usually immutable.Therefore, repeating the creation of the same measurement unit object is a waste of resources and will have a negative impact on performance.We can avoid creating duplicate objects by using the cache of the measurement unit object and improving performance.
The following is an example code created by using cache to reduce the measurement of the unit object:
import javax.measure.Unit;
import tec.units.ri.quantity.Quantities;
public class UnitCacheExample {
private static final Unit METER = Quantities.getUnit("m");
private static final Unit MILLIMETER = Quantities.getUnit("mm");
private static final Unit KILOMETER = Quantities.getUnit("km");
public static void main(String[] args) {
Unit meter = Quantities.getUnit("m");
Unit millimeter = Quantities.getUnit("mm");
Unit kilometer = Quantities.getUnit("km");
System.out.println(meter == METER); // true
System.out.println(millimeter == MILLIMETER); // true
System.out.println(kilometer == KILOMETER); // true
}
}
By using the cache when the object is created, we can reduce the number of the objects of the object and improve the performance.
2. Use the basic data type for calculation
In the API framework of the measurement unit, the computing of the measurement unit usually involves the operation of floating -point numbers, and the floating -point number operations must have performance differences compared to integer operations.In order to improve performance, we can try to calculate the basic data types (such as int, long, double).
The following is an example code calculated using the basic data type:
import javax.measure.Quantity;
import javax.measure.quantity.Length;
import tec.units.ri.quantity.Quantities;
import tec.units.ri.unit.Units;
public class CalculationExample {
public static void main(String[] args) {
Quantity<Length> length1 = Quantities.getQuantity(5, Units.METER);
Quantity<Length> length2 = Quantities.getQuantity(10, Units.METER);
double result = length1.getValue().doubleValue() + length2.getValue().doubleValue();
System.out.println(result); // 15.0
}
}
By extracting the value of the unit and using the basic data type for operation, it can avoid unnecessary object creation and floating point number operations, thereby improving performance.
3. Optimization of performance of batch operations
In some cases, we may need to perform the same operation of a batch of measures, such as unit conversion or numerical calculation.In order to improve performance, we can use batch operations to reduce the number of objects creation and process data in batches.
The following is a sample code that uses batch operations to improve performance:
import javax.measure.Quantities;
import javax.measure.Unit;
import javax.measure.quantity.Length;
import tec.units.ri.quantity.Quantities;
import tec.units.ri.unit.Units;
import java.util.ArrayList;
import java.util.List;
public class BatchOperationExample {
public static void main(String[] args) {
List<Quantity<Length>> lengths = new ArrayList<>();
// Assume that there are a lot of length that requires unit conversion operations
lengths.add(Quantities.getQuantity(5, Units.METER));
lengths.add(Quantities.getQuantity(10, Units.METER));
lengths.add(Quantities.getQuantity(15, Units.METER));
// ...
// Batch conversion to kilometer
Unit<Length> kilometer = Quantities.getUnit("km");
List<Quantity<Length>> convertedLengths = new ArrayList<>();
for (Quantity<Length> length : lengths) {
Quantity<Length> convertedLength = length.to(kilometer);
convertedLengths.add(convertedLength);
}
System.out.println(convertedLengths); // [5 km, 10 km, 15 km, ...]
}
}
By applying the same operation to a batch of measurement units and stored results in the collection, we can avoid repeated object creation and the operation of a single object, thereby improving performance.
in conclusion:
By avoiding the creation of repeated measurement unit objects, calculation of basic data types, and batch operations, we can improve performance in the API framework of the measurement unit.However, performance optimization is a complex process that needs to be analyzed and optimized according to specific conditions.We should choose appropriate optimization skills to improve performance according to actual needs and performance indicators.
