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在Scala中可以利用第三方庫來進行Protobuf或Avro的序列化和反序列化操作。以下是在Scala中使用Protobuf和Avro的示例代碼:
build.sbt
中添加依賴:libraryDependencies += "com.thesamet.scalapb" %% "scalapb-runtime" % "0.11.5"
.proto
文件定義消息格式:syntax = "proto3";
message Person {
string name = 1;
int32 age = 2;
}
scalapb
插件生成Scala代碼:sbt 'protoc-gen-scala'
import com.thesamet.scalapb.GeneratedMessage
import com.thesamet.scalapb.json.JsonFormat
// 創建一個Person對象
val person = Person(name = "Alice", age = 30)
// 將Person對象序列化為字節數組
val bytes: Array[Byte] = person.toByteArray
// 將字節數組反序列化為Person對象
val newPerson: Person = Person.parseFrom(bytes)
// 將Person對象轉換為JSON字符串
val json: String = JsonFormat.toJsonString(person)
// 將JSON字符串轉換為Person對象
val newPersonFromJson: Person = JsonFormat.fromJsonString(json)
build.sbt
中添加依賴:libraryDependencies += "org.apache.avro" % "avro" % "1.10.2"
{
"type": "record",
"name": "Person",
"fields": [
{"name": "name", "type": "string"},
{"name": "age", "type": "int"}
]
}
sbt 'runMain org.apache.avro.tool.Main compile schema person.avsc src/main/scala'
import org.apache.avro.Schema
import org.apache.avro.io.{BinaryDecoder, BinaryEncoder, DecoderFactory, EncoderFactory}
import org.apache.avro.specific.{SpecificDatumReader, SpecificDatumWriter}
// 創建一個Person對象
val person = Person("Alice", 30)
// 創建Avro schema
val schema: Schema = new Schema.Parser().parse(new File("person.avsc"))
// 創建Avro writer
val writer = new SpecificDatumWriter[Person](schema)
val out = new ByteArrayOutputStream()
val encoder: BinaryEncoder = EncoderFactory.get().binaryEncoder(out, null)
// 將Person對象序列化為字節數組
writer.write(person, encoder)
encoder.flush()
val bytes: Array[Byte] = out.toByteArray
// 創建Avro reader
val reader = new SpecificDatumReader[Person](schema)
val decoder: BinaryDecoder = DecoderFactory.get().binaryDecoder(bytes, null)
// 將字節數組反序列化為Person對象
val newPerson: Person = reader.read(null, decoder)
通過以上步驟,您可以在Scala中利用Protobuf或Avro來更高效地進行序列化和反序列化操作。
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