Hello all, I am attempting to use the retry strategy as in example below

withLabel: ld_annotation {
        cpus          = 2
        memory        = { [8.GB, 24.GB, 48.GB][Math.min(task.attempt - 1, 2)] }
        time          = 60.m
        maxRetries    = 2
        errorStrategy = { task.exitStatus in [137, 50002] ? 'retry' : 'terminate' }
    }

The ld_annotation job is running over the google cloud batch and it sometimes needs retries to get a machine with bigger memory. When that happens (retry kicks in) and later in the pipeline I encounter another failure on that branch, if I resume, the cache is invalid and the whole branch restarts from the ld_annotation yet again. Is it something obvious that could explain the cache invalidation on retry? I have never stamped into this problem before, but can see a few folks have lately similar issues github.com/nextflow-io/nextflow/issues/6884 @Evangelos Karatzas FYI

Last time I checked, the fix for this had not yet been merged in..it was being worked on though

In my case the source of failure was that after the first failing task I used

.collect()

on the set of outputs before it passed it to the next task, before I passed it to the next task resulting in barrier between the two. The suspicious thing was that the second task, was not starting at all before the first did not finish fully, when I removed the operator, cache works again with retries

Then in your case, probably the order was changing, that's why it wasnt properly cached