ctrie-java
multiversion-concurrency-control
ctrie-java | multiversion-concurrency-control | |
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1 | 19 | |
1 | 67 | |
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10.0 | 7.3 | |
almost 4 years ago | 4 months ago | |
Java | Java | |
Apache License 2.0 | - |
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ctrie-java
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Ask HN: What are some 'cool' but obscure data structures you know about?
Concurrent tries with non-blocking snapshots [0]
Say that you have a dataset that needs to be ordered, easily searchable, but is also updated quite frequently. Fast accesses are a pain if you decide to use traditional read-write locks.
Ctries are entirely lock-free, thus there is no waiting for your read operations when an update is happening, i.e. you run lookups on snapshots while updates happen.
They are also a lot of fun to implement, especially if you aren't familiar with lock-free algorithms! I did learn a lot doing it myself [1]
[0] http://aleksandar-prokopec.com/resources/docs/ctries-snapsho...
[1] https://github.com/mabeledo/ctrie-java
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In my experiments with multithreaded software I simulate a bank where many bankaccounts are randomly withdrawn from and deposited to.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?
PSI - Private Set Intersection Cardinality protocol based on ECDH and Bloom Filters
electric - Local-first sync layer for web and mobile apps. Build reactive, realtime, local-first apps directly on Postgres.
minisketch - Minisketch: an optimized library for BCH-based set reconciliation
glibc - GNU Libc
sdsl-lite - Succinct Data Structure Library 2.0
tree-flat - TreeFlat is the simplest way to build & traverse a pre-order Tree in Rust
CPython - The Python programming language
marisa-trie - MARISA: Matching Algorithm with Recursively Implemented StorAge
Folly - An open-source C++ library developed and used at Facebook.
pybktree - Python BK-tree data structure to allow fast querying of "close" matches
RoaringBitmap - A better compressed bitset in Java: used by Apache Spark, Netflix Atlas, Apache Pinot, Tablesaw, and many others
abseil-cpp - Abseil Common Libraries (C++)