...
Starting from the worst case in the above table, more and more data is now set to a lower sampling rate, while the others remain unchanged:
| Sampling rate / Number of data points | 0 | 1000 | 2000 | 3000 | 4000 | 5000 |
|---|---|---|---|---|---|---|
| 1000 | ~67% | ~65% | ~64% | ~62% | ~60% | ~59% |
| 2000 | ~67% | ~64% | ~62% | ~59% | ~58% | ~56% |
| 5000 | ~67% | ~64% | ~61% | ~59% | ~56% | ~54% |
| Note |
|---|
A mixed operation of 1000 variables each with a sampling rate of 500, 1000, 2000, 3000, and 4000 milliseconds resulted in a CPU load of ~59%. The second conclusion can be drawn as follows:
|
...
This time as well, the values are recorded with and without the value being changed.
Again, the sampling rate is at 500 milliseconds.
| Number of data points | Without value change | With value change |
|---|---|---|
| 1000 | ~10% | ~11% |
| 2000 | ~10% | ~12% |
| 3000 | ~11% | ~13% |
| 4000 | ~11% | ~14% |
| 5000 | ~12% | ~14% |
| Tip |
|---|
Even if combining data points in different groups/arrays means more work in the actual project, this investment should be made for larger plants. |
...