jvm-serializers
janino
jvm-serializers | janino | |
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7 | 2 | |
3,275 | 1,177 | |
- | 1.6% | |
4.4 | 8.0 | |
7 months ago | 3 months ago | |
Java | Java | |
- | GNU General Public License v3.0 or later |
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jvm-serializers
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Fury: 170x faster than JDK, fast serialization powered by JIT and Zero-copy
Compared with protobuf, fury is 3.2x faster. When comparing with avro, fury is 5.3x faster. Compared with flatbuffers, fury is 4.8x faster. See https://github.com/eishay/jvm-serializers/wiki for detailed benchmark data
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The state of Java Object Serialization libraries in Q2 2023
First, there's benchmarks here if you haven't seen it: jvm-serializers. Not terribly scientific, but it's something. To make any decision, you really need to benchmark your own object graph and it's important to configure the serializer for your particular usage. Still, it is sort of useful for comparing frameworks. It would be interesting to see how Loial performs there. Ping me if you add it.
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Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19+
It depends. Some binary encodings such as flatbuffer are actually slower than some JSON libraries. There's a wide range of performance even in the JSON libraries themselves. Generally the faster JSON libraries are the ones that work on a predefined schema and so are able to generate code specifically for that JSON.
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Go standard library: structured, leveled logging
> I'm surprised this is up for debate.
I looked into logging in protobuf when I was seeing if there was a better binary encoding for ring-buffer logging, along the same lines as nanolog:
https://tersesystems.com/blog/2020/11/26/queryable-logging-w...
What I found was that it's typically not the binary encoding vs string encoding that makes a difference. The biggest factors are "is there a predefined schema", "is there a precompiler that will generate code for this schema", and "what is the complexity of the output format". With that in mind, if you are dealing with chaotic semi-structured data, JSON is pretty good, and actually faster than some binary encodings:
https://github.com/eishay/jvm-serializers/wiki/Newer-Results...
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Scala 3.0 serialization
You could use any of the JVM serialisers which should still work.
janino
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Fury: 170x faster than JDK, fast serialization powered by JIT and Zero-copy
We used https://github.com/janino-compiler/janino to compile the generated code at runtime It's stable and the compiler used by spark/flink.
Janino can generated the bytecode for fury generated java code.
I must agree that generating bytecode directly has it's advantages, the abstraction is more low-level, thus more flexible, except more complicated for developing.
- Janino is a super-small, super-fast Java compiler
What are some alternatives?
fury-benchmarks - Serialization Benchmarks for fury with other libraries
groovy - Apache Groovy: A powerful multi-faceted programming language for the JVM platform
Apache Avro - Apache Avro is a data serialization system.
MemoryPack - Zero encoding extreme performance binary serializer for C# and Unity.
zio-json - Fast, secure JSON library with tight ZIO integration.
JWebAssembly - Java bytecode to WebAssembly compiler
opentelemetry-specificatio
elementary - A suite of libraries that simplify creating and unit testing annotation processors.
grpc-dotnet - gRPC for .NET
honeycomb-opentelemetry-go - Honeycomb's OpenTelemetry Go SDK distribution
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