Want to merge functionality of `events` into `combine`

[FaroutYLq]

It is known that somehow with the current structure, in SR1 there is a ~10% chance that plugins computed in peaklets level (like veto_interval and peaklets) end up having different length when processing (peaks, peaklet_classification) and (event_info, veto_proximity).

We suspect something tricky happened when combining. To make these runs fail immediately when issues happen, even before we upload their combined peaklets, we want to load test in combine job after computing:

st.get_array(run, ("peaks", "peak_basics", "peak_positions")) 
st.get_array(run, ("event_info", "cut_daq_veto"))

Once failed, nothing will be uploaded.

[FaroutYLq]

If it is indeed something tricky happens in combine, shouldn't the problematic runs' peaklets and lone_hits always trigger a trouble. Let's try erase those who failed down to peaklets+lone_hits, and then reprocess on RCC.

• If you can succeed, then peaklets+lone_hits are OK, and after we merge events into combine we will forever solve the length mismatch problem
• If you cannot, and keep running into same length problem, it means somehow the peaklets+lone_hits themselves are broken. We want to check the loaded length and the length promised in meta data.

[FaroutYLq]

Additionally, such merging will benefit us in the sense that we will have less time wasted in transferring between sites, and search for nodes. The downside will be losing the flexibility of computing peaks/events only. I would suggest we add a super_events instead of overwriting existing combine workflow.

[FaroutYLq]

Test: some outputs from combined jobs keep getting same error, even erasing everything above peaklets and reprocess on dali, it keeps failing. Example run 049374, using /scratch/midway2/yuanlq/corruption_museum/. It means, indeed something tricky happened in combine. The

ValueError: Cannot merge chunks with different number of items: [[049374.peaklets: 1670689659sec 188225560 ns - 1670689702sec 137898520 ns, 83481 items, 8.2 MB/s], [049374.peaklet_classification: 1670689659sec 188225560 ns - 1670689702sec 137898520 ns, 83482 items, 0.0 MB/s]]
Python script failed with exit code 1

Edit: it turns out to be an old peaklet_classification causing the trouble

yuanlq@dali003:/dali/lgrandi/xudc/scratch-midway2/bk/bk-0602_del/nton/Make/logs$ ls -lh /gpfs3/cap/.snapshots/weekly-2024-06-02.04h07/dali/lgrandi/xenonnt/processed/049374-peaklet_classification-p3m6pr2fhz
total 2.5K
-rw-rwxr--+ 1 yuanlq yuanlq  92M Feb  4 23:57 peaklet_classification-p3m6pr2fhz-000000
-rw-rwxr--+ 1 yuanlq yuanlq  93M Feb  4 23:57 peaklet_classification-p3m6pr2fhz-000001
-rw-rwxr--+ 1 yuanlq yuanlq  93M Feb  4 23:57 peaklet_classification-p3m6pr2fhz-000002
-rw-rwxr--+ 1 yuanlq yuanlq  52M Feb  4 23:57 peaklet_classification-p3m6pr2fhz-000003
-rw-rwxr--+ 1 yuanlq yuanlq 6.1K Feb  4 23:57 peaklet_classification-p3m6pr2fhz-metadata.json

[FaroutYLq]

Now we want to download rr and process same run from scratch and compare the peaklets

[FaroutYLq]

We did some test on 049374. Starting from raw_records, while processing on OSG, the total length of peaklets is 37572935, while on DaLI it is 37572938. Both can get ("peaklets", "peaklet_classification") without problem. Those missing peaklets from OSG is not having patterns in relative timing to chunk boundaries. See lots of truncation at the end, but no other waveform feature. Are they near DAQ veto?

[FaroutYLq]

Example

[FaroutYLq]

Two things need to be understood:

• In a peaklets job, do we rechunk: No
• In a combine job, how do we rechunk: Yes. By copy_to_frontend

[FaroutYLq]

More investigation shows that split peaks perform differently on different machines. Suspected to be floating point issue. Example here.

Processed on DaLI: max_goodness_of_split
[0.3362855  0.6615487  0.19245173 0.33158863 0.7406279  0.79679215
 0.80455685 0.         0.         0.         0.5374566  0.59021497
 0.40632284 0.53420705 0.         0.3954491  0.         0.8004727
 0.46013355 0.79623634 0.48184547 0.4689006 ]
Processed on OSG: max_goodness_of_split
[0.4330755  0.18698996 0.3486709  0.7406338  0.79679585 0.8045561
 0.         0.         0.         0.5374318  0.5903075  0.40630853
 0.53418773 0.         0.3954804  0.         0.8004847  0.46006623
 0.7962359  0.48178786 0.46880245]