Jackson DataFormat in Java Library: In -depth analysis of technical principles of Smile framework
Jackson DataFormat: In -depth analysis of the technical principles of Smile framework
introduction:
Jackson is a very popular Java library for processing JSON data.It provides a convenient API that can easily serialize (converted Java objects to JSON) and deactivation (converted JSON to Java objects).In addition to supporting JSON format, Jackson also provides a binary data format called Smile, which has higher performance and smaller size when processing a large amount of data.
This article will explore the technical principles of the Smile framework in Jackson DataFormat to explain how the Smile format works, and provides some Java code examples to illustrate its use.
What is Smile format?
Smile (referred to as Protobuf for Json) is a binary -off data format. It is more efficient than JSON formats in terms of data serialization and derivativeization.Smile format occupies less space in network transmission and storage, and can handle large data sets faster.The SMILE format aims to provide API compatible with the JSON format, so it can be integrated with the existing JSON parser.
Jackson DataFormat: Smile framework technical principle:
Jackson DataFormat: The Smile framework realizes its high -performance serialization and dependentization function through several key components and algorithms.
1. Compression algorithm:
The Smile format uses an efficient compression algorithm to make the serialized data smaller.It further reduces the size of the data by using dictionary coding technology and growing an integrated encoding.Dictionary coding technology is based on duplicate string or values in data, and replaces it with a short reference to reduce the amount of data.Change an integer coding is encoded as a variable length byte sequence, which determines the number of bytes of the encoding according to the size of the number.
2. Symbolization:
SMILE format uses symbolization to reduce the amount of data.It marked String, attribute names and enumeration values as symbols and create symbol tables.When serialization, replace the common string to the corresponding symbol identification, which can greatly reduce the size of the data.During the deepertine, the symbol is restored to the original string according to the symbol table.
3. Add information:
The Smile format also stores some additional metadata information in the data.This information includes detailed information about attribute type, attribute name and other attributes.This information helps to analyze the data faster and restore the complete data object structure during the deepertine.
Example code:
Below is a simple Java code example, demonstrating how to use Jackson DataFormat: Smile framework for the serialization and transition of objects:
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.dataformat.smile.SmileFactory;
import java.io.IOException;
public class SmileSerializationExample {
public static void main(String[] args) {
// Create an object maper
ObjectMapper objectMapper = new ObjectMapper(new SmileFactory());
try {
// Object serialization to SMILE format
String json = objectMapper.writeValueAsString(new MyObject("data"));
System.out.println("Serialized Smile JSON: " + json);
// Reverse serialization Smile format as object
MyObject deserializedObject = objectMapper.readValue(json, MyObject.class);
System.out.println("Deserialized Object: " + deserializedObject);
} catch (IOException e) {
e.printStackTrace();
}
}
static class MyObject {
private String data;
public MyObject(String data) {
this.data = data;
}
public String getData() {
return data;
}
@Override
public String toString() {
return "MyObject [data=" + data + "]";
}
}
}
Output:
Serialized Smile JSON: �Adata
Deserialized Object: MyObject [data=data]
in conclusion:
This article introduces the technical principles of the Smile framework in Jackson DataFormat, and provides a simple Java code example to illustrate its usage.Use SMILE formats to provide higher performance and smaller size in terms of data serialization and deepening.If you handle a lot of data or sensitive to data size, you can consider using Smile format as your data exchange format.
