perf: Prevent wasted time on adding to LRU cache during large commits

[ValarDragon]

This PR optimizes LRU cache usage on large commits.

If the amount of internal nodes added exceeds cache capacity, only add the first $CAPACITY nodes to the LRU cache. Anything else we add thrashes something we just added, hence is a wasted overhead.

[coderabbitai]

Walkthrough

The recent updates across several Go files primarily enhance the caching mechanism and node handling in a data structure system. The introduction of a Capacity() method in caches and an additional boolean parameter in SaveNode method calls are key changes. These modifications aim to optimize node storage and retrieval by leveraging cache capacities more effectively.

Changes

File(s)	Change Summary
cache/cache.go	Introduced Capacity() in Cache interface and implemented in lruCache to return max elements.
mutable_tree.go, nodedb.go	Modified SaveNode method to include a boolean parameter for conditional caching. Adjusted method calls in MutableTree to utilize new cache capacity logic.
tree_test.go	Updated cacheSize in tests to accommodate additional nodes, reflecting the increased caching requirements.

---

Recent Review Details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between f0c4102 and af8cf93.

Files selected for processing (4)

• cache/cache.go (2 hunks)
• mutable_tree.go (2 hunks)
• nodedb.go (3 hunks)
• tree_test.go (1 hunks)

Additional comments not posted (7)

cache/cache.go (2)

36-37: The addition of the Capacity() method to the Cache interface is well-implemented and aligns with the PR's objectives to manage cache capacity efficiently.

---

102-104: The implementation of the Capacity() method in lruCache correctly returns the maximum element count, which is essential for controlling cache additions based on capacity.

mutable_tree.go (2)

748-748: Ensuring the root node is always cached by passing true to SaveNode() in the SaveVersion() method aligns with the PR's objectives to optimize cache usage.

---

1047-1051: The modifications to saveNewNodes() to include a check against the cache's capacity before caching nodes are well-implemented and crucial for preventing cache thrashing.

nodedb.go (2)

Line range hint 207-230: The changes to the SaveNode method align well with the PR's objectives to optimize cache usage by conditionally adding nodes to the LRU cache based on the useLruCache parameter. Good use of locking and error handling.

---

391-391: The modification to include the useLruCache parameter in the SaveNode call within the deleteVersion method is a thoughtful addition, ensuring that the root node is cached during the deletion process. This aligns with the PR's objectives to optimize cache usage.

tree_test.go (1)

1778-1778: Adjust the cache size setting in tests to reflect the new cache behavior.

The cache size has been adjusted to 2 * numKeyVals to ensure it covers all inner nodes during testing. Please verify that this setting aligns with the expected cache behavior changes introduced in the PR, especially in terms of handling large datasets and preventing cache thrashing.

---

Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

Share

• X
• Mastodon
• Reddit
• LinkedIn

Tips

Chat

There are 3 ways to chat with CodeRabbit:

Note: Auto-reply has been disabled for this repository by the repository owner. The CodeRabbit bot will not respond to your replies unless it is explicitly tagged.

• Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
  • @coderabbitai generate unit testing code for this file.
  • @coderabbitai modularize this function.
• PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
  • @coderabbitai generate interesting stats about this repository and render them as a table.
  • @coderabbitai show all the console.log statements in this repository.
  • @coderabbitai read src/utils.ts and generate unit testing code.
  • @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.

Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

CodeRabbit Commands (invoked as PR comments)

• @coderabbitai pause to pause the reviews on a PR.
• @coderabbitai resume to resume the paused reviews.
• @coderabbitai review to trigger a review. This is useful when automatic reviews are disabled for the repository.
• @coderabbitai resolve resolve all the CodeRabbit review comments.
• @coderabbitai help to get help.

Additionally, you can add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.

CodeRabbit Configration File (.coderabbit.yaml)

• You can programmatically configure CodeRabbit by adding a .coderabbit.yaml file to the root of your repository.
• Please see the configuration documentation for more information.
• If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: # yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json

Documentation and Community

• Visit our Documentation for detailed information on how to use CodeRabbit.
• Join our Discord Community to get help, request features, and share feedback.
• Follow us on X/Twitter for updates and announcements.

[cool-develope]

I agree that cache optimization is important here, but I see it as more of a temporary fix. I think we need a more in-depth approach. Analyzing cache usage patterns could be helpful.
I also created the related issue: #936