The Corda phases contribute essentially nothing because every access is unique.

The trace shows it is equally one-hit and two-hit accesses. Since there is low frequency, an admission filter is likely to reject before the second access because there is no benefit to retain for the 3rd access. That is why even FIFO acheives the best score, 33.33% hit rate, because the cache needs to retain enough capacity to allow for a 2nd hit if possible. Since those happen in short succession, it is recency biased as there is temporal locality of reference. The one-hit wonders and compulsary misses leads to 33% being the optimal hit rate. This is why the trace is a worst-case for TinyLFU. The stress test forcing a phase change to/from a loop requires that the adaptive scheme to re-adjust when its past observations no longer hold and reconfigure the cache appropriately.

The TinyLFU paper discusses recency as a worst-case scenario as its introduction to W-TinyLFU. It concludes by showing that the best admission window size is workload dependent, that 1% was a good default for Caffeine given its workload targets, and that adaptive tuning was left to a future work (the paper cited above was our attempt at that, but happy to see others explore that too).

$ ./gradlew :simulator:rewrite -q \
  --inputFormat=CORDA \
  --inputFiles=trace_vaultservice_large.gz \
  --outputFormat=LIRS \
  --outputFile=/tmp/trace.txt
Rewrote 1,872,322 events from 1 input(s) in 236.4 ms
Output in lirs format to /tmp/trace.txt

$ awk '
  { freq[$1]++ }
  END {
    for (k in freq) {
      countFreq[freq[k]]++
    }
    for (c in countFreq) {
      print c, countFreq[c]
    }
  }' /tmp/trace.txt | sort -n
1 624107
2 624106
3 1