multiversion-concurrency-control
minisketch
multiversion-concurrency-control | minisketch | |
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19 | 10 | |
67 | 301 | |
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7.3 | 0.0 | |
4 months ago | 3 days ago | |
Java | C++ | |
- | MIT License |
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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In my experiments with multithreaded software I simulate a bank where many bankaccounts are randomly withdrawn from and deposited to.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.
minisketch
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Invertible Bloom Lookup Tables with Less Randomness and Memory
Anyone interested in IBLT with low failure probablity should also be aware of pinsketch and, particularly, our implementation of it: minisketch ( https://github.com/sipa/minisketch/ ).
Our implementation communicates a difference of N b-bit entries with exactly N*b bits with 100% success. The cost for this communications efficiency and reliability is that the decoder takes CPU time quadratic in N, instead of IBLT's linear decoder. However, when N is usually small, if the implementation is fast this can be fine -- especially since you wouldn't normally want to use set recon unless you were communications limited.
Pinsketches and iblt can also be combined-- one can use pinsketches as the cells of an iblt and one can also use a small pinsketch to improve the failure rate of an iblt (since when a correctly sized IBLT fails, it's usually just due to a single undecodable cycle).
- Minisketch: an optimized library for BCH-based set reconciliation
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Peer-to-Peer Encrypted Messaging
Since the protocol appears to use adhoc synchronization, the authors might be interested in https://github.com/sipa/minisketch/ which is a library that implements a data structure (pinsketch) that allows two parties to synchronize their sets of m b-bit elements which differ by c entries using only b*c bits. A naive protocol would use m*b bits instead, which is potentially much larger.
I'd guess that under normal usage the message densities probably don't justify such efficient means-- we developed this library for use in bitcoin targeting rates on the order of a dozen new messages per second and where every participant has many peers with potentially differing sets--, but it's still probably worth being aware of. The pinsketch is always equal or more efficient than a naive approach, but may not be worth the complexity.
The somewhat better known IBLT data structure has constant overheads that make it less efficient than even naive synchronization until the set differences are fairly large (particular when the element hashes are small); so some applications that evaluated and eschewed IBLT might find pinsketch applicable.
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Ask HN: What are some 'cool' but obscure data structures you know about?
I love the set reconciliation structures like the IBLT (Iterative Bloom Lookup Table) and BCH set digests like minisketch.
https://github.com/sipa/minisketch
Lets say you have a set of a billion items. Someone else has mostly the same set but they differ by 10 items. These let you exchange messages that would fit in one UDP packet to reconcile the sets.
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Here is how Ethereum COULD scale without increasing centralisation and without depending on layer two's.
Sipa is working on a better version of that for a while. The technical term is a "set reconciliation protocol", but Bitcoin Core been doing a more basic version of this for a while. Note that the "BCH" there isn't the same as Bcash
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ish: Sketches for Zig
I'd also have to say that Zig is a pretty neat library for this. In order to implement PBS I needed the MiniSketch-library (written in C/C++) and I'll have to say that integrating with it has been a breeze. Some fiddling in build.zig so that I can avoid Makefile, and after that everything has worked amazingly.
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The Pinecone Overlay Network
Networks that need to constrain themselves to limited typologies to avoid traffic magnification do so at the expense of robustness, especially against active attackers that grind their identifiers to gain privileged positions.
Maybe this is a space where efficient reconciliation ( https://github.com/sipa/minisketch/ ) could help-- certainly if the goal were to flood messages to participants reconciliation can give almost optimal communication without compromising robustness.
- Is it any easier to find A, B such that sha256(A) ^ sha256(B) = sha256(C)?
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