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| Code Block | ||
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echo -e "Threads\tTime" for threads in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 20 30 40 50; do echo -n -e "$threads\t" /usr/bin/time -f "%e" curl --silent --output /dev/null --fail --show-error \ --header "Authorization: Basic Y3BzdXNlcjpjcHNyMGNrcyE=" \ --get "http://localhost:8883/cps/api/v1/dataspaces/openroadm/anchors/owb-msa221-anchor/node?xpath=/openroadm-devices/openroadm-device\[@device-id='C201-7-[1-25]A-[1-40]A1'\]&include-descendants=true" \ --parallel --parallel-max $threads --parallel-immediate done |
Results
| Threads | Time (s) | Speedup | Comments |
| 1 | 140.4 | 1.0 | |
| 2 | 71.6 | 2.0 | 2 threads is 2x faster than 1 thread |
| 3 | 48.5 | 2.9 | |
| 4 | 37.2 | 3.8 | |
| 5 | 31.0 | 4.5 | |
| 6 | 26.6 | 5.3 | |
| 7 | 23.8 | 5.9 | |
| 8 | 21.6 | 6.5 | |
| 9 | 20.0 | 7.0 | |
| 10 | 18.7 | 7.5 | 10 threads is 7.5x faster than 1 thread |
| 11 | 17.7 | 7.9 | |
| 12 | 16.8 | 8.4 | There are exactly 12 CPU cores (logical) on test machine |
| 13 | 16.7 | 8.4 | |
| 14 | 16.7 | 8.4 | |
| 15 | 16.8 | 8.4 | |
| 20 | 16.8 | 8.4 | |
| 30 | 16.7 | 8.4 | |
| 40 | 16.8 | 8.4 | |
| 50 | 16.7 | 8.4 |
Observations
- There were no failures during the tests (e.g. timeouts or refused connections).
- Performance increases nearly linearly with increasing thread count, up to the number of CPU cores.
- Performance stops increasing when the number of threads equals the number of CPU cores (expected).
- Verbose statistics show that each individual request takes around 0.14 seconds, regardless of thread count (but with multiple CPU cores, requests are really done in parallel)
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