us
asami
us | asami | |
---|---|---|
2 | 6 | |
55 | 626 | |
- | 0.0% | |
1.5 | 0.0 | |
4 months ago | about 2 years ago | |
Go | Clojure | |
MIT License | Eclipse Public License 1.0 |
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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).
asami
- Ask HN: What are some 'cool' but obscure data structures you know about?
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Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
Unlike some other commenters, I agree that graph models are usually a better fit for most data than relational models. There's been some interesting work in recent years developing this idea: in the Clojure world there's Datomic, XTDB, and a host of competitors, all of which build on work from Semantic Web/SPARQL/triplestores and logic programming. Some are even intended to be used as primary datastores: they support some amount of schema and constraints, have well-defined consistency and ACID guarantees, etc. This makes them unlike graph databases like Neo4J and others, which fill an architectural role more like Elasticsearch as a read-optimization tool. Here's an interesting talk making a case for triple-based databases.
- Introduction to the Asami Graph Database
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How to query Datomic, Datascript, Asami, or other graph databases
Despite the documentation that exists, I've heard many people who have been confused about how to query Datomic, Datascript, Asami, or other graph databases. So I've made an attempt at explaining it https://github.com/threatgrid/asami/wiki/Introduction
- Introduction (To Graph Databases)
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Asami
The first Graph implementation for Asami was a simple in-memory data structure, described in my ClojureD talk. The code for this appears in asami.index. This file started much smaller (as referenced above), but has since expanded with the needs extended functionality, such as transactions, and transitive closure operations.
What are some alternatives?
lnd - Lightning Network Daemon ⚡️
datascript - Immutable database and Datalog query engine for Clojure, ClojureScript and JS
ego - EGraphs in OCaml
crux - General purpose bitemporal database for SQL, Datalog & graph queries. Backed by @juxt [Moved to: https://github.com/xtdb/xtdb]
swift - the multiparty transport protocol (aka "TCP with swarming" or "BitTorrent at the transport layer")
datahike - A durable Datalog implementation adaptable for distribution.
pvfmm - A parallel kernel-independent FMM library for particle and volume potentials
datalevin - A simple, fast and versatile Datalog database
gring - Golang circular linked list with array backend
Apache AGE - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL. [Moved to: https://github.com/apache/age]
ctrie-java - Java implementation of a concurrent trie
naga - Datalog based rules engine