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The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
https://grpc.io/
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134 lines
5.3 KiB
134 lines
5.3 KiB
# Overview of performance test suite, with steps for manual runs: |
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For design of the tests, see |
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https://grpc.io/docs/guides/benchmarking.html. |
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## Pre-reqs for running these manually: |
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In general the benchmark workers and driver build scripts expect |
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[linux_performance_worker_init.sh](../../gce/linux_performance_worker_init.sh) to have been ran already. |
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### To run benchmarks locally: |
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* From the grpc repo root, start the |
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[run_performance_tests.py](../run_performance_tests.py) runner script. |
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### On remote machines, to start the driver and workers manually: |
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The [run_performance_test.py](../run_performance_tests.py) top-level runner script can also |
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be used with remote machines, but for e.g., profiling the server, |
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it might be useful to run workers manually. |
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1. You'll need a "driver" and separate "worker" machines. |
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For example, you might use one GCE "driver" machine and 3 other |
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GCE "worker" machines that are in the same zone. |
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2. Connect to each worker machine and start up a benchmark worker with a "driver_port". |
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* For example, to start the grpc-go benchmark worker: |
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[grpc-go worker main.go](https://github.com/grpc/grpc-go/blob/master/benchmark/worker/main.go) --driver_port <driver_port> |
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#### Comands to start workers in different languages: |
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* Note that these commands are what the top-level |
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[run_performance_test.py](../run_performance_tests.py) script uses to |
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build and run different workers through the |
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[build_performance.sh](./build_performance.sh) script and "run worker" |
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scripts (such as the [run_worker_java.sh](./run_worker_java.sh)). |
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##### Running benchmark workers for C-core wrapped languages (C++, Python, C#, Node, Ruby): |
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* These are more simple since they all live in the main grpc repo. |
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``` |
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$ cd <grpc_repo_root> |
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$ tools/run_tests/performance/build_performance.sh |
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$ tools/run_tests/performance/run_worker_<language>.sh |
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``` |
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* Note that there is one "run_worker" script per language, e.g., |
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[run_worker_csharp.sh](./run_worker_csharp.sh) for c#. |
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##### Running benchmark workers for gRPC-Java: |
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* You'll need the [grpc-java](https://github.com/grpc/grpc-java) repo. |
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``` |
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$ cd <grpc-java-repo> |
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$ ./gradlew -PskipCodegen=true :grpc-benchmarks:installDist |
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$ benchmarks/build/install/grpc-benchmarks/bin/benchmark_worker --driver_port <driver_port> |
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``` |
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##### Running benchmark workers for gRPC-Go: |
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* You'll need the [grpc-go repo](https://github.com/grpc/grpc-go) |
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``` |
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$ cd <grpc-go-repo>/benchmark/worker && go install |
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$ # if profiling, it might be helpful to turn off inlining by building with "-gcflags=-l" |
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$ $GOPATH/bin/worker --driver_port <driver_port> |
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``` |
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#### Build the driver: |
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* Connect to the driver machine (if using a remote driver) and from the grpc repo root: |
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``` |
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$ tools/run_tests/performance/build_performance.sh |
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``` |
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#### Run the driver: |
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1. Get the 'scenario_json' relevant for the scenario to run. Note that "scenario |
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json" configs are generated from [scenario_config.py](./scenario_config.py). |
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The [driver](../../../test/cpp/qps/qps_json_driver.cc) takes a list of these configs as a json string of the form: `{scenario: <json_list_of_scenarios> }` |
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in its `--scenarios_json` command argument. |
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One quick way to get a valid json string to pass to the driver is by running |
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the [run_performance_tests.py](./run_performance_tests.py) locally and copying the logged scenario json command arg. |
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2. From the grpc repo root: |
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* Set `QPS_WORKERS` environment variable to a comma separated list of worker |
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machines. Note that the driver will start the "benchmark server" on the first |
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entry in the list, and the rest will be told to run as clients against the |
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benchmark server. |
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Example running and profiling of go benchmark server: |
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``` |
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$ export QPS_WORKERS=<host1>:<10000>,<host2>,10000,<host3>:10000 |
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$ bins/opt/qps_json_driver --scenario_json='<scenario_json_scenario_config_string>' |
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``` |
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### Example profiling commands |
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While running the benchmark, a profiler can be attached to the server. |
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Example to count syscalls in grpc-go server during a benchmark: |
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* Connect to server machine and run: |
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``` |
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$ netstat -tulpn | grep <driver_port> # to get pid of worker |
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$ perf stat -p <worker_pid> -e syscalls:sys_enter_write # stop after test complete |
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``` |
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Example memory profile of grpc-go server, with `go tools pprof`: |
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* After a run is done on the server, see its alloc profile with: |
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``` |
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$ go tool pprof --text --alloc_space http://localhost:<pprof_port>/debug/heap |
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``` |
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### Configuration environment variables: |
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* QPS_WORKER_CHANNEL_CONNECT_TIMEOUT |
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Consuming process: qps_worker |
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Type: integer (number of seconds) |
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This can be used to configure the amount of time that benchmark |
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clients wait for channels to the benchmark server to become ready. |
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This is useful in certain benchmark environments in which the |
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server can take a long time to become ready. Note: if setting |
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this to a high value, then the scenario config under test should |
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probably also have a large "warmup_seconds". |
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* QPS_WORKERS |
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Consuming process: qps_json_driver |
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Type: comma separated list of host:port |
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Set this to a comma separated list of QPS worker processes/machines. |
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Each scenario in a scenario config has specifies a certain number |
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of servers, `num_servers`, and the driver will start |
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"benchmark servers"'s on the first `num_server` `host:port` pairs in |
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the comma separated list. The rest will be told to run as clients |
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against the benchmark server.
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