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What are the common serialization protocols in RPC frameworks? What are their advantages and disadvantages?

2月22日 14:05

Serialization is a core component in RPC frameworks, directly affecting performance and efficiency. Common serialization protocols have their own characteristics:

1. Protobuf (Protocol Buffers)

  • Features: Developed by Google, binary format, efficient and compact
  • Advantages:
    • Fast serialization/deserialization
    • Small data size, high transmission efficiency
    • Supports multiple languages (Java, Python, Go, C++, etc.)
    • Good backward compatibility
    • Clearly defined data structures (.proto files)
  • Disadvantages:
    • Poor readability, requires .proto files
    • Does not support dynamic types
  • Applicable Scenarios: Microservice communication with high performance requirements

2. Thrift

  • Features: Developed by Facebook, supports multiple protocols and transport methods
  • Advantages:
    • Supports multiple serialization formats (Binary, JSON, Compact)
    • Supports multiple transport protocols (TCP, HTTP, Memory)
    • Powerful code generation capabilities
    • Supports both asynchronous and synchronous calls
  • Disadvantages:
    • Steep learning curve
    • Relatively less documentation
  • Applicable Scenarios: Complex cross-language, multi-protocol scenarios

3. JSON

  • Features: Text format, easy to read and write
  • Advantages:
    • Human-readable, easy to debug
    • Strong universality, supported by all languages
    • Flexible, supports dynamic types
    • Native browser support
  • Disadvantages:
    • Large data size, low transmission efficiency
    • Slow serialization/deserialization
    • Poor type safety
  • Applicable Scenarios: External APIs, Web applications

4. Avro

  • Features: Apache project, supports schema evolution
  • Advantages:
    • Supports dynamic schemas, no code generation needed
    • Strong schema evolution capabilities
    • High compression rate
    • Suitable for big data scenarios
  • Disadvantages:
    • High learning cost
    • Relatively niche
  • Applicable Scenarios: Big data processing, log collection

5. MessagePack

  • Features: Binary JSON, efficient and compact
  • Advantages:
    • Smaller and faster than JSON
    • Maintains JSON's data types
    • Supports multiple languages
  • Disadvantages:
    • Less readable than JSON
    • Relatively small ecosystem
  • Applicable Scenarios: Scenarios requiring JSON compatibility but higher performance

6. Hessian

  • Features: Binary serialization, dynamic types
  • Advantages:
    • Fast serialization
    • Supports dynamic types
    • Cross-language support
  • Disadvantages:
    • Relatively large data size
    • Low community activity
  • Applicable Scenarios: RPC calls in Java ecosystem

Performance Comparison (Approximate Ranking):

  • Serialization Speed: Protobuf > Hessian > Thrift > MessagePack > Avro > JSON
  • Data Size: Protobuf > MessagePack > Thrift > Hessian > Avro > JSON
  • Readability: JSON > Avro > MessagePack > Thrift > Protobuf > Hessian

Selection Recommendations:

  • High-performance Internal Services: Protobuf, Thrift
  • External APIs: JSON
  • Big Data Scenarios: Avro
  • Need JSON Compatibility: MessagePack
  • Java Ecosystem: Hessian
标签:RPC