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✨ ♻️ Cached TrieStateStore #3489

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greymistcube
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@greymistcube greymistcube commented Nov 15, 2023

This overhauls existing caching strategy. Shows about 20% ~ 25% improvement for Block execution time with 1 million cache capacity. There is a slight change in API, but should be compatible as added parameters are all optional. This should be refactored before 3.8 release.

Edit: I'm looking into whether MerkleTrie() constructors should be made internal. 😶

@greymistcube greymistcube force-pushed the refactor/cached-trie-state-store branch from 2cb9598 to 2f67258 Compare November 15, 2023 07:24
@greymistcube greymistcube changed the title Refactor/cached trie state store ✨ ♻️ Cached TrieStateStore Nov 15, 2023
@greymistcube greymistcube self-assigned this Nov 15, 2023
@greymistcube greymistcube marked this pull request as ready for review November 15, 2023 07:28
@greymistcube greymistcube force-pushed the refactor/cached-trie-state-store branch from 3166887 to 3c4519f Compare November 15, 2023 07:49
@greymistcube greymistcube changed the base branch from 3.6-maintenance to 3.8-maintenance November 15, 2023 07:51
@greymistcube greymistcube force-pushed the refactor/cached-trie-state-store branch from 3c4519f to 23b1be4 Compare November 15, 2023 08:23
@greymistcube greymistcube force-pushed the refactor/cached-trie-state-store branch from 23b1be4 to d57b120 Compare November 15, 2023 11:43
@greymistcube greymistcube force-pushed the refactor/cached-trie-state-store branch from d57b120 to 3e6989e Compare November 15, 2023 12:35

This PR has 205 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Large
Size       : +115 -90
Percentile : 60.5%

Total files changed: 8

Change summary by file extension:
.md : +7 -1
.cs : +108 -89

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
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      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
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What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
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      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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@greymistcube
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Merged in #3495

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