ENH: Reduce number of processes spawned by ProcessPoolExecutor in blocked_io.py

[amitpendharkar]

Issue:
ProcessPoolExecutor spawns the processes based on max_workers argument. Total number of logical cpus are currently used as default value for max_workers

mdio-python/src/mdio/segy/blocked_io.py

Line 124 in 1475793

executor = ProcessPoolExecutor(max_workers=num_workers, mp_context=context)

This spawns too many processes. Based of the size of the segy file, resource contention and context switching bogs the machine down and eventually the run get's terminated.

Suggested solution:
Make default value of max_workers as either number of cores or limit it to 80% of available logical cpus.(discuss)

[tasansal]

Hi, thanks for looking into it. The max cpus is a good approximate for normal sized machines. If we are using a large machine with 48+ cores I can see where this could start trashing the machine.

MDIO takes the following environment variable to control number of CPUs used in ingestion: MDIO__IMPORT__CPU_COUNT.
I propose, instead of changing the default, you should set this value based on your machine.

[amitpendharkar]

We noticed this issue only after we saw some random ingestion failures. Out of two similar files, one fails and other other succeeds. The failed one would sometimes succeed if re-submitted multiple times. This causes loss of time in production.

I believe setting the value to 80% of available logical cpus would take care of the issue. It would also leave some room to other processes (like opentelemetry) to run.

[amitpendharkar]

I believe, setting MDIO_IMPORT_CPUT_COUNT when pod get's launched makes things really unclear. One would not know why it's only using few resources. Coming up with right value for MDIO_IMPORT_CPUT_COUNT is also difficult.

Also, setting MDIO_IMPORT_CPUT_COUNT should not be the norm. It should be a one off thing.

We can make
default_cpus = cpu_count(logical=False) below and other such places.

mdio-python/src/mdio/segy/blocked_io.py

Line 40 in 1475793

default_cpus = cpu_count(logical=True)

FYI: We routinely use 48+ core machines in production

I will update here with some benchmarking results to validate the change.