multiversion-concurrency-control
sync
Our great sponsors
multiversion-concurrency-control | sync | |
---|---|---|
19 | 2 | |
65 | 16 | |
- | - | |
7.3 | 6.2 | |
3 months ago | about 2 months ago | |
Java | C++ | |
- | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
multiversion-concurrency-control
-
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
-
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In my experiments with multithreaded software I simulate a bank where many bankaccounts are randomly withdrawn from and deposited to.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?
-
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
-
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:
-
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?
-
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-...
-
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.
-
Tail Call Optimization: The Musical
https://github.com/samsquire/multiversion-concurrency-contro...
I want to redesign the architecture of the async/await to be easier to understand. I want to use a state machine somehow.
sync
-
Correctly implementing a spinlock in Modern C++
Your reasoning is correct. Also, if it makes you sleep better :-), here's the boost implementation of a spinlock:
https://github.com/boostorg/sync/blob/dfdf317f63d26fb40c703b...
It has been written by an expert in lockfree programming (Tim Blechmann)
What are some alternatives?
electric - Local-first sync layer for web and mobile apps. Build reactive, realtime, local-first apps directly on Postgres.
marisa-trie - MARISA: Matching Algorithm with Recursively Implemented StorAge
glibc - GNU Libc
pybktree - Python BK-tree data structure to allow fast querying of "close" matches
Disruptor - High Performance Inter-Thread Messaging Library
abseil-cpp - Abseil Common Libraries (C++)
tree-flat - TreeFlat is the simplest way to build & traverse a pre-order Tree in Rust
gring - Golang circular linked list with array backend
plurid-data-structures-typescript - Utility Data Structures Implemented in TypeScript
multiversion-concurrency-contro
electric_dart - A Dart implementation for Electric (electric-sql.com).
pvfmm - A parallel kernel-independent FMM library for particle and volume potentials