ZeroMQ FAQ page suggest use of Google's protobuf as a way to serialise message content.
Has anyone see a good usage example?
I also need to get the answer to "What is the biggest advantage of serialising messages?" - whether it may be something I can live without and take the advantage of slimmer pipeline.
I quite like the idea of .proto
files and the protoc
compiler.
Also, it seem that another great tool to throw at the playground would be libev
, any comments are welcome :)
A Printer converts protobuf message to JSON format. A TypeRegistry is used to resolve Any messages in the JSON conversion.
RPCZ is built on top of ZeroMQ for handling the low-level I/O details in a lock-free manner. The Python module is a Cython wrapper around the C++ API.
Proto3 is the latest version of Protocol Buffers and includes the following changes from proto2: Field presence, also known as hasField , is removed by default for primitive fields. An unset primitive field has a language-defined default value.
ZeroMQ (also spelled ØMQ, 0MQ or ZMQ) is an asynchronous messaging library, aimed at use in distributed or concurrent applications. It provides a message queue, but unlike message-oriented middleware, a ZeroMQ system can run without a dedicated message broker; the zero in the name is for zero broker.
If you are 100% certain that the programs that are going to communicate over ZMQ will at all times be capable of understanding each other's binary format (eg because they are always distributed together and were all compiled with the same compiler options anyways) I see no benefit to the overhead that's added by serialization.
As soon as the above condition cannot be satisfied (like partner programs running on different host types, programs written in different languages or even partner programs that can evolve independently in time - which may cause incompatibilities in their raw binary structures) serialization becomes quite probably a must.
It seems that nowadays everybody and their brother is creating serialization solutions, which may be an indication that there's no one size fits all solution. This page contains a pretty thorough benchmarking of serialization time, deserialization time and sizes for 27 (!!) different serialization systems. Don't skip the first paragraph of that page, it says "Warning, benchmarks can be misleading". Your application, your data are what counts for you, but the data presented there may help you narrow down the choices you want to study in detail.
Here is a sample which send and receive messages through java and in C++:
Serializing in java:
Person person = Person.newBuilder().setName("chand") .setEmail("[email protected]").setId(55555).build(); socket.send(person.toByteArray(), 0);
De-serialize in java:
byte[] reply = socket.recv(0); Person person2 = Person.parseFrom(reply);
Serializing in C++:
Person p = Person(); std::string str; p.SerializeToString(&str); int sz = str.length(); zmq::message_t *query = new message_t(sz); memcpy(query->data (), str.c_str(), sz); socket->send (*query);
De-serializign in C++
zmq::message_t resultset(100); socket->recv (&resultset); Person p = Person(); p.ParseFromArray(resultset.data(), resultset.size()); printf("\n Server : %s", p.name().c_str());
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