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Test data used complies with Open ROADM YANG model.

Storing data nodes

A number of openroadm device nodes will be stored using CpsService::saveData.

Device nodes11002003004005006007008009001000

Time (seconds)

0.2952.364.367.159.7611.5014.7718.4319.7922.1626.54

Observations

  • Storing data nodes has linear time complexity (as expected).
  • There are edge cases with worse complexity.
  • Performance can be improved by enabling write batching (CPS-1795)
  • There are edge cases with exponential complexity.

Updating data nodes

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In this scenario, 1000 devices nodes are already defined. A number of these existing data nodes will be updated using CpsService::updateDataNodeAndDescendants.

Device nodes11002003004005006007008009001000

Time (seconds)

0.21512.7928.3844.2351.55

69.46

85.6795.02109.16117.00131.15

Observations

  • Updating data nodes has linear time complexity (as expected).
  • Updating is approximately 5.5 times slower than storing data nodes .

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  • (even if the updated data is identical to the existing data).

Updating data leaves

In this scenario, 1000 devices nodes are already defined. The data leaves of a number of these existing data nodes will be updated using CpsService::updateNodeLeaves.

Device nodes11002003004005006007008009001000

Time (seconds)

.201.266.276.280.317.379.385.465.485.520

.561

Observations

  • Updating data leaves has linear time complexity.

Reading data

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nodes


Cps Path Queries


Deleting data nodes

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