us
multiversion-concurrency-control
us | multiversion-concurrency-control | |
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2 | 19 | |
55 | 67 | |
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1.5 | 7.3 | |
4 months ago | 4 months ago | |
Go | Java | |
MIT License | - |
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us
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Ask HN: What are some 'cool' but obscure data structures you know about?
It might be easier to think about it as a stack, rather than a tree. Each element of the stack represents a subtree -- a perfect binary tree. If you ever have two subtrees of height k, you merge them together into one subtree of height k+1. Your stack might already have another subtree of height k+1; if so, you repeat the process, until there's at most one subtree of each height.
This process is isomorphic to binary addition. Worked example: let's start with a single leaf, i.e. a subtree of height 0. Then we "add" another leaf; since we now have a pair of two equally-sized leaves, we merge them into one subtree of height 1. Then we add a third leaf; now this one doesn't have a sibling to merge with, so we just keep it. Now our "stack" contains two subtrees: one of height 1, and one of height 0.
Now the isomorphism: we start with the binary integer 1, i.e. a single bit at index 0. We add another 1 to it, and the 1s "merge" into a single 1 bit at index 1. Then we add another 1, resulting in two 1 bits at different indices: 11. If we add one more bit, we'll get 100; likewise, if we add another leaf to our BNT, we'll get a single subtree of height 2. Thus, the binary representation of the number of leaves "encodes" the structure of the BNT.
This isomorphism allows you to do some neat tricks, like calculating the size of a Merkle proof in 3 asm instructions. There's some code here if that helps: https://github.com/lukechampine/us/blob/master/merkle/stack....
You could also check out section 5.1 of the BLAKE3 paper: https://github.com/BLAKE3-team/BLAKE3-specs/blob/master/blak...
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My proposal to the Foundation: add first-class S3 provider support
This isn't what I'm asking for - I don't care if it's baked into us, exists as a backend for minio, uses PseudoKV https://github.com/lukechampine/us/issues/67, or whatever the case may be. I see no value in sending any third party my private data in an unencrypted form (uploading to your server, even if over HTTPS, you got my data).
multiversion-concurrency-control
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Statelines - an idea for representing asynchronicity elegantly
The code is in this repository https://github.com/samsquire/multiversion-concurrency-control in MultiplexingThread.java and MultiplexProgramParser.java
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CRDT-richtext: Rust implementation of Peritext and Fugue
https://github.com/samsquire/multiversion-concurrency-contro...
And I implemented a 3 way text diff with myers algorithm based on https://blog.jcoglan.com/2017/02/12/the-myers-diff-algorithm...
https://github.com/samsquire/text-diff
I implemented an eventually consistent mesh protocol that uses timestamps to provide last write wins
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A collection of lock-free data structures written in standard C++11
I think I lean towards per-thread sharding instead of mutex based or lock free data structures except for lockfree ringbuffers.
You can get embarassingly parallel performance if you split your data by thread and aggregate periodically.
If you need a consistent view of your entire set of data, that is slow path with sharding.
In my experiments with multithreaded software I simulate a bank where many bankaccounts are randomly withdrawn from and deposited to. https://github.com/samsquire/multiversion-concurrency-contro...
I get 700 million requests per second due to the sharding of money over accounts.
- How to get started?
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The “Build Your Own Database” book is finished
If you want some sample code to implement MVCC, I implemented MVCC in multithreaded Java as a toy example
https://github.com/samsquire/multiversion-concurrency-contro...
First read TransactionC.java then read MVCC.java
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Let's write a setjmp
I wrote an unrolled switch statement in Java to simulate eager async/await across treads.
https://github.com/samsquire/multiversion-concurrency-contro...
The goal is that a compiler should generate this for you. This code is equivalent to the following:
task1:
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Structured Concurrency Definition
https://doc.rust-lang.org/book/ch16-00-concurrency.html
I've been working on implementing Java async/await state machine with switch statements and a scheduling loop. If the user doesn't await the async task handle, then the task's returnvalue is never handled. This is similar to the Go problem with the go statement.
https://github.com/samsquire/multiversion-concurrency-contro...
If your async call returns a handle and
- Are there any languages with transactions as a first-class concept?
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Small VMs and Coroutines
yield value2++
https://github.com/samsquire/multiversion-concurrency-contro...
I am still working on allowing multiple coroutines to be in flight in parallel at the same time. At the moment the tasks share the same background thread.
I asked this stackoverflow question regarding C++ coroutines, as I wanted to use coroutines with a thread pool.
https://stackoverflow.com/questions/74520133/how-can-i-pass-...
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Hctree is an experimental high-concurrency database back end for SQLite
This is very interesting. Thank you for submitting this and thank you for working on this.
I am highly interested in parallelism and high concurrency. I implemented multiversion concurrency control in Java.
https://github.com/samsquire/multiversion-concurrency-contro...
I am curious how to handle replication with high concurrency. I'm not sure how you detect dangerous reads+writes to the same key (tuples/fields) across different replica machines. In other words, multiple master.
I am aware Google uses truetime and some form of timestamp ordering and detection of interfering timestamps. But I'm not sure how to replicate that.
I began working on an algorithm to synchronize database records, do a sort, then a hash for each row where hash(row) = hash(previous_row.hash + row.data)
Then do a binary search on hashes matching/not matching. This is a synchronization algorithm I'm designing that requires minimal data transfer but multiple round trips.
The binary search would check the end of the data set for hash(replica_a.row[last]) == hash(replica_b.row[last]) then split the hash list in half and check the middle item, this shall tell you which row and which columns are different.
What are some alternatives?
lnd - Lightning Network Daemon ⚡️
electric - Local-first sync layer for web and mobile apps. Build reactive, realtime, local-first apps directly on Postgres.
ego - EGraphs in OCaml
glibc - GNU Libc
swift - the multiparty transport protocol (aka "TCP with swarming" or "BitTorrent at the transport layer")
tree-flat - TreeFlat is the simplest way to build & traverse a pre-order Tree in Rust
pvfmm - A parallel kernel-independent FMM library for particle and volume potentials
marisa-trie - MARISA: Matching Algorithm with Recursively Implemented StorAge
gring - Golang circular linked list with array backend
pybktree - Python BK-tree data structure to allow fast querying of "close" matches
ctrie-java - Java implementation of a concurrent trie
abseil-cpp - Abseil Common Libraries (C++)