multiversion-concurrency-control
marisa-trie
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multiversion-concurrency-control | marisa-trie | |
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19 | 1 | |
67 | 485 | |
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7.3 | 0.0 | |
4 months ago | about 1 month ago | |
Java | C++ | |
- | GNU General Public License v3.0 or later |
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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In my experiments with multithreaded software I simulate a bank where many bankaccounts are randomly withdrawn from and deposited to.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.
marisa-trie
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Ask HN: What are some 'cool' but obscure data structures you know about?
My favorite one that I've had the chance to use professionally is the Marisa trie[0].
Context is a data scientist had written a service that essentially was just lookups on a trie. He'd left and the service was starting to have memory problems so I dug in and swapped the implementation. Iirc swapping the trie implementation changed memory usage from 8gb to 100mb and sped everything up as well.
The actual data structure is equivalent to a trie, but cannot be modified once it's been built (I think it may be the same as a LOUDS trie, I don't remember the specifics)
[0] https://github.com/s-yata/marisa-trie
What are some alternatives?
electric - Local-first sync layer for web and mobile apps. Build reactive, realtime, local-first apps directly on Postgres.
glibc - GNU Libc
tree-flat - TreeFlat is the simplest way to build & traverse a pre-order Tree in Rust
pybktree - Python BK-tree data structure to allow fast querying of "close" matches
abseil-cpp - Abseil Common Libraries (C++)
gring - Golang circular linked list with array backend
sync
plurid-data-structures-typescript - Utility Data Structures Implemented in TypeScript
multiversion-concurrency-contro
pvfmm - A parallel kernel-independent FMM library for particle and volume potentials
hamt - A hash array-mapped trie implementation in C