Negative Cell Offload – One reason
April 29, 2020 Leave a comment
This is a post that has been sitting around for while… just an illustration of one of the reasons for negative cell offload numbers,
Global Stats ========================================================================================================================= | Elapsed | Cpu | IO | Application | Concurrency | Cluster | Buffer | Read | Read | Write | Write | Cell | | Time(s) | Time(s) | Waits(s) | Waits(s) | Waits(s) | Waits(s) | Gets | Reqs | Bytes | Reqs | Bytes | Offload | ========================================================================================================================= | 2234 | 1660 | 574 | 0.00 | 0.00 | 0.01 | 5M | 206K | 54GB | 106K | 21GB | -29.87% | ========================================================================================================================= Parallel Execution Details (DOP=4 , Servers Allocated=8) =========================================================================================================================================================================================== | Name | Type | Group# | Server# | Elapsed | Cpu | IO | Application | Concurrency | Cluster | Buffer | Read | Read | Write | Write | Cell | Wait Events | | | | | | Time(s) | Time(s) | Waits(s) | Waits(s) | Waits(s) | Waits(s) | Gets | Reqs | Bytes | Reqs | Bytes | Offload | (sample #) | =========================================================================================================================================================================================== | j012 | QC | | | 173 | 173 | | 0.00 | | | 13 | | . | | . | NaN% | | | p032 | Set 1 | 1 | 1 | 23 | 23 | 0.70 | | | | 1M | 13352 | 9GB | | . | 51.46% | | | p033 | Set 1 | 1 | 2 | 23 | 22 | 0.73 | | | | 1M | 13057 | 9GB | | . | 51.22% | cell smart table scan (1) | | p034 | Set 1 | 1 | 3 | 23 | 23 | 0.71 | | | | 1M | 13322 | 9GB | | . | 51.22% | | | p035 | Set 1 | 1 | 4 | 23 | 23 | 0.80 | | | | 1M | 13220 | 9GB | | . | 51.22% | | | p028 | Set 1 | 2 | 1 | 492 | 349 | 143 | | 0.00 | 0.00 | 7100 | 38385 | 4GB | 26400 | 5GB | -112.77% | direct path read temp (129) | | | | | | | | | | | | | | | | | | direct path write temp (21) | | p029 | Set 1 | 2 | 2 | 492 | 346 | 146 | | 0.00 | 0.00 | 6745 | 37827 | 4GB | 26393 | 5GB | -112.77% | direct path read temp (122) | | | | | | | | | | | | | | | | | | direct path write temp (17) | | p030 | Set 1 | 2 | 3 | 491 | 352 | 139 | | 0.00 | 0.00 | 6590 | 38809 | 4GB | 26390 | 5GB | -108.33% | direct path read temp (109) | | | | | | | | | | | | | | | | | | direct path write temp (15) | | p031 | Set 1 | 2 | 4 | 492 | 349 | 143 | | 0.00 | 0.00 | 6710 | 38313 | 4GB | 26391 | 5GB | -112.77% | direct path read temp (136) | | | | | | | | | | | | | | | | | | direct path write temp (14) |
Here is an illustration I’ve been hanging on to for ages – one reason why you might get negative cell offload numbers – temp.
SQL Monitor uses something like the following for calculating cell offload:
Cell Offload = 100 * ((PHYSICAL_READ_BYTES + PHYSICAL_WRITE_BYTES) – IO INTERCONNECT_BYTES)/NULLIF((PHYSICAL_READ_BYTES + PHYSICAL_WRITE_BYTES),0)
Whilst the PHYSICAL_%_BYTES metrics are measured above the ASM level, ASM then mirrors any writes so these can be tripled for redundancy and counted in IO_INTERCONNECT_BYTES.
So actually it’s often a bit of an apples vs oranges metric…
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