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Code Block
languagebash
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

Note the above curl command performs 1000 requests. It is based on globbing in the URL - curl allows ranges such as [1-25]  in the URL, for example:

  http://example.com/archive[1996-1999]/vol[1-4].html

which would expand into a series of 16 requests to:

  • http://example.com/archive1996/vol1.html
  • http://example.com/archive1996/vol2.html
  • ...
  • http://example.com/archive1999/vol4.html

Results

ThreadsTime (s)SpeedupComments
1140.41.0
271.62.02 threads is 2x faster than 1 thread
348.52.9
437.23.8
531.04.5
626.65.3
723.85.9
821.66.5
920.07.0
1018.77.510 threads is 7.5x faster than 1 thread
1117.77.9
1216.88.4There are exactly 12 CPU cores (logical) on test machine
1316.78.4
1416.78.4
1516.88.4
2016.88.4
3016.78.4
4016.88.4
5016.78.4

Graphs

Image Added

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).

Data sheets

View file
nameCpsPerformance.xlsx
height250
View file
nameperformanceTest.zip
height250
View file
namePerformance test.postman_collection.json
height250

Test scripts overview 

- performanceTest.sh
   Get 1000 times single large object from thousands of devices (1000, 2000, ..., 10000) and create metric after each run
- performanceRootTest.sh
   Get 10 times the whole data tree as one object from thousands of devices (1000, 2000, ..., 10000) and create metric after each run
- parallelGetRequestTest.sh
   Get one devices parallel from a database with 10000 devices, executed 10 times sequential

- buildup.sh
   Create the dataspace, create the schemaset, create the anchor and create the root node
- owb-msa221.zip
   The schemaset for the tests
- outNode.json
   The input for the root node creation
- createThousandNode.sh
   Helper script for the database creation
- innerNode.json
   The input for the sub node creation
- createMetric.sh
   Helper script for metric creation