mirror of https://github.com/grpc/grpc.git
The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
https://grpc.io/
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67 lines
2.3 KiB
67 lines
2.3 KiB
## Multiprocessing with gRPC Python |
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Multiprocessing allows application developers to sidestep the Python global |
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interpreter lock and achieve true concurrency on multicore systems. |
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Unfortunately, using multiprocessing and gRPC Python is not yet as simple as |
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instantiating your server with a `futures.ProcessPoolExecutor`. |
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The library is implemented as a C extension, maintaining much of the state that |
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drives the system in native code. As such, upon calling |
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[`fork`](http://man7.org/linux/man-pages/man2/fork.2.html), much of the |
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state copied into the child process is invalid, leading to hangs and crashes. |
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However, calling `fork` without `exec` in your python process is supported |
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*before* any gRPC servers have been instantiated. Application developers can |
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take advantage of this to parallelize their CPU-intensive operations. |
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## Calculating Prime Numbers with Multiple Processes |
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This example calculates the first 10,000 prime numbers as an RPC. We instantiate |
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one server per subprocess, balancing requests between the servers using the |
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[`SO_REUSEPORT`](https://lwn.net/Articles/542629/) socket option. Note that this |
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option is not available in `manylinux1` distributions, which are, as of the time |
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of writing, the only gRPC Python wheels available on PyPI. To take advantage of this |
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feature, you'll need to build from source, either using bazel (as we do for |
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these examples) or via pip, using `pip install grpcio --no-binary grpcio`. |
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```python |
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_PROCESS_COUNT = multiprocessing.cpu_count() |
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``` |
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On the server side, we detect the number of CPUs available on the system and |
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spawn exactly that many child processes. If we spin up fewer, we won't be taking |
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full advantage of the hardware resources available. |
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## Running the Example |
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To run the server, |
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[ensure `bazel` is installed](https://docs.bazel.build/versions/master/install.html) |
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and run: |
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``` |
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bazel run //examples/python/multiprocessing:server & |
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``` |
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Note the address at which the server is running. For example, |
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``` |
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... |
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[PID 107153] Binding to '[::]:33915' |
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[PID 107507] Starting new server. |
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[PID 107508] Starting new server. |
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... |
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``` |
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Note that several servers have been started, each with its own PID. |
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Now, start the client by running |
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``` |
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bazel run //examples/python/multiprocessing:client -- [SERVER_ADDRESS] |
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``` |
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For example, |
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``` |
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bazel run //examples/python/multiprocessing:client -- [::]:33915 |
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```
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