WIP PR in progress here: https://github.com/jenkinsci/pipeline-stage-view-plugin/pull/4

Current approaches being used:

• Caching of post-analysis stage view results
• Revise existing caching to use standard caching library (Guava or possibly Caffeine) rather than ad-hoc Actions with transient cache fields, and a WeakHashMap
• Use more efficient algorithm to scan the FlowGraph rapidly for key stats and information
• Cap number of returned child nodes in a stage
• Avoid materializing API return objects unless needed

Benchmark results using the following optimizations, but not the optimized flow scanner (separate PR until refactors and edge cases are solved):

• Cache the completely analyzed RunExt response object for each run, which includes fully realized Stage nodes
• Use standardized caching implementation
• Use non-recursive method calls for all flow walking, to avoid StackOverflow issues
• Cap number of returned nodes in a stage
• Avoid materializing unneeded API return objects
• When returning RunExt objects, use a wrapper to hide the child nodes in each stage until details of the stage are requested via the Describe API

Benchmark:

• Old 1.0 plugin:
• Initial runs data: 1220 ms, then
• Getting stage descriptions (describe API): 780 + 43 +792 + 40 = 1655 ms
• Total on first load: 2875s
• On page refresh (hitting caches): runs = 12ms, description of stages = 669ms, 10ms, 680ms, 18ms = 1389 ms total (every load)
• New plugin (snapshot):
• Initial runs data: 1.08s, then
• Getting stage descriptions (describe API): 65 s + 54 ms + 64 ms + 52 ms = total 235 ms for stages
• Total on first load: 1315 ms
• On page refresh (hitting caches): 3ms to get runs, descriptions of stages = 12ms + 10ms + 4 ms + 10ms = 39 ms total

Speedup:

• First load is roughly 2x as fast, 35x as fast on refreshes. This scales even better as the number of stages and nodes increases.
• No stack overflows on large stages.
• Memory is bounded by cache sizes

Benchmark job:

stage 'long stage'
for(int i=0; i<999; i++) {
  echo "Output $i"
}
stage 'short stage'
echo 'finished second stage'

Run this 2x to generate runs data. On larger flow graphs (10k+ nodes), or with numerous complex stages, speedups from caching the stage data along with the run (and only analyzing a run a single time) are 100x or more.

Unfortunately I can't benchmark that because it hits the stack overflow.

Released and verified as working by users.