This repository was archived by the owner on Aug 19, 2024. It is now read-only.
rpc: lower the memory consumption with fasthttp rpc server #1650
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Proposed changes
valyala fasthttp
requesthandler in default for high speed rpc serving. However, it uses its own bytebufferpool library, and it specializes in reuse of memory. I'm not sure, but guessing, reusing memory left some memory segments and it leads to a such memory leak even though it is intended. Unlike typical fasthttp services, the klaytn rpc request consumes different size of memory. For example,getBlockByNumber
andgetBlocknumber
memory consumption is very different.klay_getBlockByNumber(randomblocknumber) load test memory result
v1.9.1

soon, it leads to a out-of-memory
v1.9.1 + PR

BTW, the continuous rising of memory is caused by accumulating trie cache
Types of changes
Please put an x in the boxes related to your change.
Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your code.
$ make test
)Related issues
Further comments
If this is a relatively large or complex change, kick off the discussion by explaining why you chose the solution you did and what alternatives you considered, etc...