BTreeMap compaction
Nobody has claimed this yet.
- Dominant language
- Java
- Stars
- 5.1k
- Forks
- 877
- PR merge metrics
- No merged PRs in 30d
Description
Hello Jan,
We recently started to use BTreeMap in our project and tested its performance according to this note Massive deletion causes empty nodes and performance lost. We've found that insertion after massive deletion works very slow. But we're very interested in using this map and going to create compaction algorithm for it. We believe that you already have thoughts about its implementation. Could you please share them with us? some links to possible algorithms and your points to the code would be very helpful.
Kind regards,
Mikhail
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the BTreeMap implementation and the referenced note, focusing on how massive deletion affects later insertion performance. Identify the compaction behavior and any relevant existing tests or entry points before proposing an algorithm; done would mean restoring acceptable insertion performance after large deletions with coverage for that scenario.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- java
- Domain
- database
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100