def METHOD_NAME(benchmark, prefix, first, io_backend):
    io_backend = backends_by_name[io_backend]
    mib_hdr = os.path.join(prefix, MIB_FILE)
    flist = filelist(mib_hdr)
    with api.Context() as ctx:
        ds = ctx.load(filetype="mib", path=mib_hdr, io_backend=io_backend)
        def mask():
            return np.ones(ds.shape.sig, dtype=bool)
        udf = ApplyMasksUDF(mask_factories=[mask], backends=('numpy', ))
        if first == "warm_executor":
            ctx.run_udf(udf=udf, dataset=ds)
        elif first == "cold_executor":
            pass
        else:
            raise ValueError("bad param")
        warmup_cache(flist)
        benchmark.pedantic(
            ctx.run_udf, kwargs=dict(udf=udf, dataset=ds),
            warmup_rounds=0,
            rounds=1,
            iterations=1
        )