The technical principles and best practice of the Java class library in JSONITER Scala Core framework

JSONITER Scala Core is a high -performance JSON library for Scala language. It borrows Java's JSONITER library and optimizes the SCALA language.In the process of using the JSONiter Scala Core framework, there are some technical principles and best practices to follow to obtain the best performance and effect. 1. Use the compile timing code to generate: JSONITER Scala Core framework can achieve fast JSON parsing and serialization by compiling the timing.By using the @JSONCODEC annotation mark, the class that needs to be parsed and serialized can be generated by compiling the timing code to generate efficient analysis and serialized code.The following is an example: scala import com.jsoniter.annotation._ @JsonCodec case class User(name: String, age: Int) val json = """{"name": "John", "age": 30}""" val user = JsoniterScala.parse[User](json) Println (user) // Output: user (John, 30) val jsonString = JsoniterScala.toJson(user) Println (jsonstring) // Output: {"name": "John", "Age": 30} 2. Avoid reflex: JSONITER Scala Core framework is used to avoid reflection by compiling the timing of the timing, which greatly improves performance.Therefore, when using JSONITER Scala Core, you should try to avoid using reflex operations to avoid affecting performance.You can use the `@Transient` parameter in the @jsoniter annotation to mark the fields that do not require serialized to avoid reflection operations. 3. Use a custom encoder and decoder: JSONITER Scala Core framework allows custom encoders and decoders to meet specific needs.You can define custom encoders and decoders by implementing the `ENCODER` and` decoder` tract.The following is an example: scala import com.jsoniter.spi._ case class Point(x: Int, y: Int) implicit val pointEncoder: Encoder[Point] = (obj: Point, output: JsonStream) => { output.writeVal(s"${obj.x}:${obj.y}") } implicit val pointDecoder: Decoder[Point] = (input: JsonReader) => { val pointString = input.readString() val pointArray = pointString.split(":") Point(pointArray(0).toInt, pointArray(1).toInt) } val point = Point(10, 20) val jsonString = JsoniterScala.toJson(point) Println (jsonstring) // Output: "10:20" val parsedPoint = JsoniterScala.parse[Point](jsonString) Println (Parsedpoint) // Output: Point (10,20) 4. Use cache: JSONITER Scala Core framework uses a cache to improve performance when parsing and serialized JSON.In some cases, the performance can be optimized by adjusting the cache size.Set up the cache size by setting the `SerializationConfig.cachesize` and` PARSINGCONFIG.CACHESIZE`.The larger cache size can improve performance, but it also consumes more memory. To sum up, the technical principles and best practices of the Java class library in the JSONITER Scala Core framework include the use of compile timing to generate, avoid reflexes, use custom encoders and decoders, and use the cache in a timely manner.By following these principles and practices, high -performance and efficient JSON parsing and serialization can be obtained.