...
Observations
- Storing data nodes has linear time complexity (as expected).
- Raw performance is roughly 3200 fragments per second for the given test setup.
- Performance can be improved by enabling write batching (CPS-1795)
- There are edge cases with exponential complexity.
...
Observations
- Updating data nodes has linear time complexity (as expected).
- Raw performance is roughly 650 fragments per second for the given model and test setup.
- Updating data nodes is approximately 5.5 times slower than storing data nodes (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.
Example JSON payload for updating two leaves ('status' and 'ne-state') for one device:
Code Block | ||
---|---|---|
| ||
{
'openroadm-device': [
{'device-id':'C201-7-1A-1', 'status':'fail', 'ne-state':'jeopardy'},
]
} |
Device nodes | 1 | 100 | 200 | 300 | 400 | 500 | 600 | 700 | 800 | 900 | 1000 |
Time (seconds) | .201 | .266 | .276 | .280 | .317 | .379 | .385 | .465 | .485 | .520 | .561 |
...
Observations
- Updating data leaves has linear time complexity.
Reading data nodes
...