Merge pull request #2233 from waku-org/feat/init-sds

feat(sds): create package for sds and add protobuf def
This commit is contained in:
Arseniy Klempner 2025-01-29 11:48:29 -08:00 committed by GitHub
commit 6abd2d18a1
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
16 changed files with 642 additions and 90 deletions

186
package-lock.json generated
View File

@ -19,7 +19,8 @@
"packages/tests",
"packages/browser-tests",
"packages/build-utils",
"packages/react-native-polyfills"
"packages/react-native-polyfills",
"packages/sds"
],
"devDependencies": {
"@size-limit/preset-big-lib": "^11.0.2",
@ -10805,6 +10806,10 @@
"resolved": "packages/sdk",
"link": true
},
"node_modules/@waku/sds": {
"resolved": "packages/sds",
"link": true
},
"node_modules/@waku/tests": {
"resolved": "packages/tests",
"link": true
@ -11684,64 +11689,6 @@
"ajv": "^6.9.1"
}
},
"node_modules/allure-commandline": {
"version": "2.32.0",
"resolved": "https://registry.npmjs.org/allure-commandline/-/allure-commandline-2.32.0.tgz",
"integrity": "sha512-W03ors+ks8uy0SgQILHQvtvR0iadAfDYmTFC3p8Pk4pi8KXUW1cF+z8FN2+7deH3FE2cuYgjhhA+CdLdJfzOMQ==",
"dev": true,
"license": "Apache-2.0",
"bin": {
"allure": "bin/allure"
}
},
"node_modules/allure-js-commons": {
"version": "2.15.1",
"resolved": "https://registry.npmjs.org/allure-js-commons/-/allure-js-commons-2.15.1.tgz",
"integrity": "sha512-5V/VINplbu0APnfSZOkYpKOzucO36Q2EtTD1kqjWjl7n6tj7Hh+IHCZsH3Vpk/LXRDfj9RuXugBBvwYKV5YMJw==",
"dev": true,
"license": "Apache-2.0",
"dependencies": {
"md5": "^2.3.0",
"properties": "^1.2.1",
"strip-ansi": "^5.2.0"
}
},
"node_modules/allure-js-commons/node_modules/ansi-regex": {
"version": "4.1.1",
"resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-4.1.1.tgz",
"integrity": "sha512-ILlv4k/3f6vfQ4OoP2AGvirOktlQ98ZEL1k9FaQjxa3L1abBgbuTDAdPOpvbGncC0BTVQrl+OM8xZGK6tWXt7g==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=6"
}
},
"node_modules/allure-js-commons/node_modules/strip-ansi": {
"version": "5.2.0",
"resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-5.2.0.tgz",
"integrity": "sha512-DuRs1gKbBqsMKIZlrffwlug8MHkcnpjs5VPmL1PAh+mA30U0DTotfDZ0d2UUsXpPmPmMMJ6W773MaA3J+lbiWA==",
"dev": true,
"license": "MIT",
"dependencies": {
"ansi-regex": "^4.1.0"
},
"engines": {
"node": ">=6"
}
},
"node_modules/allure-mocha": {
"version": "2.15.1",
"resolved": "https://registry.npmjs.org/allure-mocha/-/allure-mocha-2.15.1.tgz",
"integrity": "sha512-4Hk2qUR6LdAUXNpPe73MV3DPKrBH7zy57lbAdb/D0poNIkdGEkzUYkpVPtW1imYfjqFXKBFEPOSJWqznGuiyjg==",
"dev": true,
"license": "Apache-2.0",
"dependencies": {
"allure-js-commons": "2.15.1"
},
"peerDependencies": {
"mocha": ">=6.2.x"
}
},
"node_modules/anser": {
"version": "1.4.10",
"resolved": "https://registry.npmjs.org/anser/-/anser-1.4.10.tgz",
@ -25835,23 +25782,6 @@
"node": ">= 14.0.0"
}
},
"node_modules/mocha-multi-reporters": {
"version": "1.5.1",
"resolved": "https://registry.npmjs.org/mocha-multi-reporters/-/mocha-multi-reporters-1.5.1.tgz",
"integrity": "sha512-Yb4QJOaGLIcmB0VY7Wif5AjvLMUFAdV57D2TWEva1Y0kU/3LjKpeRVmlMIfuO1SVbauve459kgtIizADqxMWPg==",
"dev": true,
"license": "MIT",
"dependencies": {
"debug": "^4.1.1",
"lodash": "^4.17.15"
},
"engines": {
"node": ">=6.0.0"
},
"peerDependencies": {
"mocha": ">=3.1.2"
}
},
"node_modules/mocha/node_modules/cliui": {
"version": "7.0.4",
"resolved": "https://registry.npmjs.org/cliui/-/cliui-7.0.4.tgz",
@ -33016,16 +32946,6 @@
"integrity": "sha512-wnD2ZE+l+SPC/uoS0vXeE9L1+0wuaMqKlfz9AMUo38JsyLSBWSFcHR1Rri62LZc12vLr1gb3jl7iwQhgwpAbGQ==",
"license": "ISC"
},
"node_modules/properties": {
"version": "1.2.1",
"resolved": "https://registry.npmjs.org/properties/-/properties-1.2.1.tgz",
"integrity": "sha512-qYNxyMj1JeW54i/EWEFsM1cVwxJbtgPp8+0Wg9XjNaK6VE/c4oRi6PNu5p7w1mNXEIQIjV5Wwn8v8Gz82/QzdQ==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=0.10"
}
},
"node_modules/proto-list": {
"version": "1.2.4",
"resolved": "https://registry.npmjs.org/proto-list/-/proto-list-1.2.4.tgz",
@ -40715,6 +40635,24 @@
}
}
},
"packages/scalable-data-sync": {
"version": "0.0.1",
"extraneous": true,
"license": "MIT OR Apache-2.0",
"devDependencies": {
"@rollup/plugin-commonjs": "^25.0.7",
"@rollup/plugin-json": "^6.0.0",
"@rollup/plugin-node-resolve": "^15.2.3",
"@waku/build-utils": "*",
"cspell": "^8.6.1",
"fast-check": "^3.19.0",
"npm-run-all": "^4.1.5",
"rollup": "^4.12.0"
},
"engines": {
"node": ">=20"
}
},
"packages/sdk": {
"name": "@waku/sdk",
"version": "0.0.29",
@ -40841,6 +40779,79 @@
"url": "https://opencollective.com/sinon"
}
},
"packages/sds": {
"name": "@waku/sds",
"version": "0.0.1",
"license": "MIT OR Apache-2.0",
"dependencies": {
"chai": "^5.1.2"
},
"devDependencies": {
"@rollup/plugin-commonjs": "^25.0.7",
"@rollup/plugin-json": "^6.0.0",
"@rollup/plugin-node-resolve": "^15.2.3",
"@waku/build-utils": "*",
"cspell": "^8.6.1",
"fast-check": "^3.19.0",
"npm-run-all": "^4.1.5",
"rollup": "^4.12.0"
},
"engines": {
"node": ">=20"
}
},
"packages/sds/node_modules/assertion-error": {
"version": "2.0.1",
"resolved": "https://registry.npmjs.org/assertion-error/-/assertion-error-2.0.1.tgz",
"integrity": "sha512-Izi8RQcffqCeNVgFigKli1ssklIbpHnCYc6AknXGYoB6grJqyeby7jv12JUQgmTAnIDnbck1uxksT4dzN3PWBA==",
"engines": {
"node": ">=12"
}
},
"packages/sds/node_modules/chai": {
"version": "5.1.2",
"resolved": "https://registry.npmjs.org/chai/-/chai-5.1.2.tgz",
"integrity": "sha512-aGtmf24DW6MLHHG5gCx4zaI3uBq3KRtxeVs0DjFH6Z0rDNbsvTxFASFvdj79pxjxZ8/5u3PIiN3IwEIQkiiuPw==",
"dependencies": {
"assertion-error": "^2.0.1",
"check-error": "^2.1.1",
"deep-eql": "^5.0.1",
"loupe": "^3.1.0",
"pathval": "^2.0.0"
},
"engines": {
"node": ">=12"
}
},
"packages/sds/node_modules/check-error": {
"version": "2.1.1",
"resolved": "https://registry.npmjs.org/check-error/-/check-error-2.1.1.tgz",
"integrity": "sha512-OAlb+T7V4Op9OwdkjmguYRqncdlx5JiofwOAUkmTF+jNdHwzTaTs4sRAGpzLF3oOz5xAyDGrPgeIDFQmDOTiJw==",
"engines": {
"node": ">= 16"
}
},
"packages/sds/node_modules/deep-eql": {
"version": "5.0.2",
"resolved": "https://registry.npmjs.org/deep-eql/-/deep-eql-5.0.2.tgz",
"integrity": "sha512-h5k/5U50IJJFpzfL6nO9jaaumfjO/f2NjK/oYB2Djzm4p9L+3T9qWpZqZ2hAbLPuuYq9wrU08WQyBTL5GbPk5Q==",
"engines": {
"node": ">=6"
}
},
"packages/sds/node_modules/loupe": {
"version": "3.1.3",
"resolved": "https://registry.npmjs.org/loupe/-/loupe-3.1.3.tgz",
"integrity": "sha512-kkIp7XSkP78ZxJEsSxW3712C6teJVoeHHwgo9zJ380de7IYyJ2ISlxojcH2pC5OFLewESmnRi/+XCDIEEVyoug=="
},
"packages/sds/node_modules/pathval": {
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/pathval/-/pathval-2.0.0.tgz",
"integrity": "sha512-vE7JKRyES09KiunauX7nd2Q9/L7lhok4smP9RZTDeD4MVs72Dp2qNFVz39Nz5a0FVEW0BJR6C0DYrq6unoziZA==",
"engines": {
"node": ">= 14.16"
}
},
"packages/tests": {
"name": "@waku/tests",
"version": "0.0.1",
@ -40875,8 +40886,6 @@
"@waku/message-encryption": "*",
"@waku/relay": "*",
"@waku/sdk": "*",
"allure-commandline": "^2.27.0",
"allure-mocha": "^2.9.2",
"chai": "^4.3.10",
"cspell": "^8.6.1",
"datastore-core": "^10.0.2",
@ -40884,7 +40893,6 @@
"interface-datastore": "^8.2.10",
"libp2p": "2.1.8",
"mocha": "^10.3.0",
"mocha-multi-reporters": "^1.5.1",
"npm-run-all": "^4.1.5"
},
"engines": {

View File

@ -16,7 +16,8 @@
"packages/tests",
"packages/browser-tests",
"packages/build-utils",
"packages/react-native-polyfills"
"packages/react-native-polyfills",
"packages/sds"
],
"scripts": {
"prepare": "husky",

View File

@ -0,0 +1,126 @@
/* eslint-disable import/export */
/* eslint-disable complexity */
/* eslint-disable @typescript-eslint/no-namespace */
/* eslint-disable @typescript-eslint/no-unnecessary-boolean-literal-compare */
/* eslint-disable @typescript-eslint/no-empty-interface */
import { type Codec, decodeMessage, type DecodeOptions, encodeMessage, MaxLengthError, message } from 'protons-runtime'
import type { Uint8ArrayList } from 'uint8arraylist'
export interface SdsMessage {
messageId: string
channelId: string
lamportTimestamp?: number
causalHistory: string[]
bloomFilter?: Uint8Array
content?: Uint8Array
}
export namespace SdsMessage {
let _codec: Codec<SdsMessage>
export const codec = (): Codec<SdsMessage> => {
if (_codec == null) {
_codec = message<SdsMessage>((obj, w, opts = {}) => {
if (opts.lengthDelimited !== false) {
w.fork()
}
if ((obj.messageId != null && obj.messageId !== '')) {
w.uint32(18)
w.string(obj.messageId)
}
if ((obj.channelId != null && obj.channelId !== '')) {
w.uint32(26)
w.string(obj.channelId)
}
if (obj.lamportTimestamp != null) {
w.uint32(80)
w.int32(obj.lamportTimestamp)
}
if (obj.causalHistory != null) {
for (const value of obj.causalHistory) {
w.uint32(90)
w.string(value)
}
}
if (obj.bloomFilter != null) {
w.uint32(98)
w.bytes(obj.bloomFilter)
}
if (obj.content != null) {
w.uint32(162)
w.bytes(obj.content)
}
if (opts.lengthDelimited !== false) {
w.ldelim()
}
}, (reader, length, opts = {}) => {
const obj: any = {
messageId: '',
channelId: '',
causalHistory: []
}
const end = length == null ? reader.len : reader.pos + length
while (reader.pos < end) {
const tag = reader.uint32()
switch (tag >>> 3) {
case 2: {
obj.messageId = reader.string()
break
}
case 3: {
obj.channelId = reader.string()
break
}
case 10: {
obj.lamportTimestamp = reader.int32()
break
}
case 11: {
if (opts.limits?.causalHistory != null && obj.causalHistory.length === opts.limits.causalHistory) {
throw new MaxLengthError('Decode error - map field "causalHistory" had too many elements')
}
obj.causalHistory.push(reader.string())
break
}
case 12: {
obj.bloomFilter = reader.bytes()
break
}
case 20: {
obj.content = reader.bytes()
break
}
default: {
reader.skipType(tag & 7)
break
}
}
}
return obj
})
}
return _codec
}
export const encode = (obj: Partial<SdsMessage>): Uint8Array => {
return encodeMessage(obj, SdsMessage.codec())
}
export const decode = (buf: Uint8Array | Uint8ArrayList, opts?: DecodeOptions<SdsMessage>): SdsMessage => {
return decodeMessage(buf, SdsMessage.codec(), opts)
}
}

View File

@ -0,0 +1,11 @@
syntax = "proto3";
message SdsMessage {
// 1 Reserved for sender/participant id
string message_id = 2; // Unique identifier of the message
string channel_id = 3; // Identifier of the channel to which the message belongs
optional int32 lamport_timestamp = 10; // Logical timestamp for causal ordering in channel
repeated string causal_history = 11; // List of preceding message IDs that this message causally depends on. Generally 2 or 3 message IDs are included.
optional bytes bloom_filter = 12; // Bloom filter representing received message IDs in channel
optional bytes content = 20; // Actual content of the message
}

View File

@ -0,0 +1,6 @@
module.exports = {
parserOptions: {
tsconfigRootDir: __dirname,
project: "./tsconfig.dev.json",
},
};

27
packages/sds/.mocharc.cjs Normal file
View File

@ -0,0 +1,27 @@
const config = {
extension: ['ts'],
spec: 'src/**/*.spec.ts',
require: ['ts-node/register', 'isomorphic-fetch'],
loader: 'ts-node/esm',
'node-option': [
'experimental-specifier-resolution=node',
'loader=ts-node/esm'
],
exit: true,
retries: 4
};
if (process.env.CI) {
console.log("Running tests in parallel");
config.parallel = true;
config.jobs = 6;
console.log("Using JSON reporter for test results");
config.reporter = 'json';
config.reporterOptions = {
output: 'reports/mocha-results.json'
};
} else {
console.log("Running tests serially. To enable parallel execution update mocha config");
}
module.exports = config;

3
packages/sds/README.md Normal file
View File

@ -0,0 +1,3 @@
# Scalable Data Sync
Typescript implementation of the [Scalable Data Sync protocol](https://github.com/vacp2p/rfc-index/blob/main/vac/raw/sds.md) for message reliability of distributed logs in the browser.

84
packages/sds/package.json Normal file
View File

@ -0,0 +1,84 @@
{
"name": "@waku/sds",
"version": "0.0.1",
"description": "Scalable Data Sync implementation for the browser. Based on https://github.com/vacp2p/rfc-index/blob/main/vac/raw/sds.md",
"types": "./dist/index.d.ts",
"module": "./dist/index.js",
"exports": {
".": {
"types": "./dist/index.d.ts",
"import": "./dist/index.js"
}
},
"typesVersions": {
"*": {
"*": [
"*",
"dist/*",
"dist/*/index"
]
}
},
"type": "module",
"author": "Waku Team",
"homepage": "https://github.com/waku-org/js-waku/tree/master/packages/scalable-data-sync#readme",
"repository": {
"type": "git",
"url": "https://github.com/waku-org/js-waku.git"
},
"bugs": {
"url": "https://github.com/waku-org/js-waku/issues"
},
"license": "MIT OR Apache-2.0",
"keywords": [
"waku",
"decentralized",
"secure",
"communication",
"web3",
"ethereum",
"dapps",
"privacy"
],
"scripts": {
"build": "run-s build:**",
"build:esm": "tsc",
"build:bundle": "rollup --config rollup.config.js",
"fix": "run-s fix:*",
"fix:lint": "eslint src *.js --fix",
"check": "run-s check:*",
"check:lint": "eslint src *.js",
"check:spelling": "cspell \"{README.md,src/**/*.ts}\"",
"check:tsc": "tsc -p tsconfig.dev.json",
"prepublish": "npm run build",
"reset-hard": "git clean -dfx -e .idea && git reset --hard && npm i && npm run build",
"test": "NODE_ENV=test run-s test:*",
"test:node": "NODE_ENV=test TS_NODE_PROJECT=./tsconfig.dev.json mocha"
},
"engines": {
"node": ">=20"
},
"dependencies": {
"chai": "^5.1.2"
},
"devDependencies": {
"@rollup/plugin-commonjs": "^25.0.7",
"@rollup/plugin-json": "^6.0.0",
"@rollup/plugin-node-resolve": "^15.2.3",
"@waku/build-utils": "*",
"cspell": "^8.6.1",
"fast-check": "^3.19.0",
"npm-run-all": "^4.1.5",
"rollup": "^4.12.0"
},
"files": [
"dist",
"bundle",
"src/**/*.ts",
"!**/*.spec.*",
"!**/*.json",
"CHANGELOG.md",
"LICENSE",
"README.md"
]
}

View File

@ -0,0 +1,24 @@
import commonjs from "@rollup/plugin-commonjs";
import json from "@rollup/plugin-json";
import { nodeResolve } from "@rollup/plugin-node-resolve";
import { extractExports } from "@waku/build-utils";
import * as packageJson from "./package.json" assert { type: "json" };
const input = extractExports(packageJson);
export default {
input,
output: {
dir: "bundle",
format: "esm"
},
plugins: [
commonjs(),
json(),
nodeResolve({
browser: true,
preferBuiltins: false
})
]
};

67
packages/sds/src/bloom.ts Normal file
View File

@ -0,0 +1,67 @@
import { getMOverNBitsForK } from "./probabilities.js";
export interface BloomFilterOptions {
// The expected maximum number of elements for which this BloomFilter is sized.
capacity: number;
// The desired false-positive rate (between 0 and 1).
errorRate: number;
// (Optional) The exact number of hash functions, if the user wants to override the automatic calculation.
kHashes?: number;
// (Optional) Force a specific number of bits per element instead of using a table or optimal formula.
forceNBitsPerElem?: number;
}
/**
* A probabilistic data structure that tracks memberships in a set.
* Supports time and space efficient lookups, but may return false-positives.
* Can never return false-negatives.
* A bloom filter can tell us if an element is:
* - Definitely not in the set
* - Potentially in the set (with a probability depending on the false-positive rate)
*/
export abstract class BloomFilter {
public totalBits: number;
public data: Uint8Array = new Uint8Array(0);
public constructor(options: BloomFilterOptions) {
let nBitsPerElem: number;
let k = options.kHashes ?? 0;
const forceNBitsPerElem = options.forceNBitsPerElem ?? 0;
if (k < 1) {
// Calculate optimal k based on target error rate
const bitsPerElem = Math.ceil(
-1.0 * (Math.log(options.errorRate) / Math.pow(Math.log(2), 2))
);
k = Math.round(Math.log(2) * bitsPerElem);
nBitsPerElem = Math.round(bitsPerElem);
} else {
// Use specified k if possible
if (forceNBitsPerElem < 1) {
// Use lookup table
nBitsPerElem = getMOverNBitsForK(k, options.errorRate);
} else {
nBitsPerElem = forceNBitsPerElem;
}
}
const mBits = options.capacity * nBitsPerElem;
const mInts = 1 + mBits / (this.data.BYTES_PER_ELEMENT * 8);
this.totalBits = mBits;
this.data = new Uint8Array(mInts);
}
// Adds an item to the bloom filter by computing its hash values
// and setting corresponding bits in "data".
public abstract insert(item: string | Uint8Array): void;
// Checks if the item is potentially in the bloom filter.
// The method is guaranteed to return "true" for items that were inserted,
// but might also return "true" for items that were never inserted
// (purpose of false-positive probability).
public abstract lookup(item: string | Uint8Array): boolean;
}

View File

@ -0,0 +1,9 @@
import { expect } from "chai";
import { BloomFilter } from "./bloom.js";
describe("BloomFilter", () => {
it("should be defined", () => {
expect(BloomFilter).to.be.ok;
});
});

View File

@ -0,0 +1,3 @@
import { BloomFilter } from "./bloom.js";
export { BloomFilter };

View File

@ -0,0 +1,166 @@
// This file contains the probability tables used to determine the optimal number of
// hash functions (k) and bits per element (m/n) for a Bloom filter.
//
// These are used to determine how to construct a Bloom filter that can perform
// lookups with false-positive rate low enough to be satisfactory.
/**
* Represents the error rates for a given number of hash functions (k) across
* different (m/n) ratios (i.e., bits per element).
*/
type TErrorForK = Float32Array;
/**
* An array where each index corresponds to a value of k (the number of hash functions),
* and each element is a vector of false-positive rates for varying bits-per-element ratios.
* Example:
* ```ts
* // Probability of a false positive upon lookup when using 1 hash function (k=1)
* // and 15 bits per element (mOverN=15):
* const falsePositiveRate = kErrors[1][15];
* ```
*/
type TAllErrorRates = Array<TErrorForK>;
/**
* Table of false positive rates for values of k from 0 to 12, and bits-per-element
* ratios ranging from 0 up to around 32. Each Float32Array is indexed by mOverN,
* so kErrors[k][mOverN] gives the estimated false-positive probability.
*
* These values mirror commonly used reference data found in Bloom filter literature,
* such as:
* https://pages.cs.wisc.edu/~cao/papers/summary-cache/node8.html
* https://dl.acm.org/doi/pdf/10.1145/362686.362692
*/
// prettier-ignore
export const kErrors: TAllErrorRates = [
new Float32Array([1.0]),
new Float32Array([1.0, 1.0, 0.3930000000, 0.2830000000, 0.2210000000, 0.1810000000,
0.1540000000, 0.1330000000, 0.1180000000, 0.1050000000, 0.0952000000,
0.0869000000, 0.0800000000, 0.0740000000, 0.0689000000, 0.0645000000,
0.0606000000, 0.0571000000, 0.0540000000, 0.0513000000, 0.0488000000,
0.0465000000, 0.0444000000, 0.0425000000, 0.0408000000, 0.0392000000,
0.0377000000, 0.0364000000, 0.0351000000, 0.0339000000, 0.0328000000,
0.0317000000, 0.0308000000]),
new Float32Array([1.0, 1.0, 0.4000000000, 0.2370000000, 0.1550000000, 0.1090000000,
0.0804000000, 0.0618000000, 0.0489000000, 0.0397000000, 0.0329000000,
0.0276000000, 0.0236000000, 0.0203000000, 0.0177000000, 0.0156000000,
0.0138000000, 0.0123000000, 0.0111000000, 0.0099800000, 0.0090600000,
0.0082500000, 0.0075500000, 0.0069400000, 0.0063900000, 0.0059100000,
0.0054800000, 0.0051000000, 0.0047500000, 0.0044400000, 0.0041600000,
0.0039000000, 0.0036700000]),
new Float32Array([1.0, 1.0, 1.0, 0.2530000000, 0.1470000000, 0.0920000000,
0.0609000000, 0.0423000000, 0.0306000000, 0.0228000000, 0.0174000000,
0.0136000000, 0.0108000000, 0.0087500000, 0.0071800000, 0.0059600000,
0.0108000000, 0.0087500000, 0.0071800000, 0.0059600000, 0.0050000000,
0.0042300000, 0.0036200000, 0.0031200000, 0.0027000000, 0.0023600000,
0.0020700000, 0.0018300000, 0.0016200000, 0.0014500000, 0.0012900000,
0.0011600000, 0.0010500000, 0.0009490000, 0.0008620000, 0.0007850000,
0.0007170000]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 0.1600000000, 0.0920000000, 0.0561000000, 0.0359000000,
0.0240000000, 0.0166000000, 0.0118000000, 0.0086400000, 0.0064600000,
0.0049200000, 0.0038100000, 0.0030000000, 0.0023900000, 0.0019300000,
0.0015800000, 0.0013000000, 0.0010800000, 0.0009050000, 0.0007640000,
0.0006490000, 0.0005550000, 0.0004780000, 0.0004130000, 0.0003590000,
0.0003140000, 0.0002760000, 0.0002430000, 0.0002150000, 0.0001910000]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 0.1010000000, 0.0578000000, 0.0347000000,
0.0217000000, 0.0141000000, 0.0094300000, 0.0065000000, 0.0045900000,
0.0033200000, 0.0024400000, 0.0018300000, 0.0013900000, 0.0010700000,
0.0008390000, 0.0006630000, 0.0005300000, 0.0004270000, 0.0003470000,
0.0002850000, 0.0002350000, 0.0001960000, 0.0001640000, 0.0001380000,
0.0001170000, 0.0000996000, 0.0000853000, 0.0000733000, 0.0000633000]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0638000000, 0.0364000000, 0.0216000000,
0.0133000000, 0.0084400000, 0.0055200000, 0.0037100000, 0.0025500000,
0.0017900000, 0.0012800000, 0.0009350000, 0.0006920000, 0.0005190000,
0.0003940000, 0.0003030000, 0.0002360000, 0.0001850000, 0.0001470000,
0.0001170000, 0.0000944000, 0.0000766000, 0.0000626000, 0.0000515000,
0.0000426000, 0.0000355000, 0.0000297000, 0.0000250000]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0229000000, 0.0135000000, 0.0081900000,
0.0051300000, 0.0032900000, 0.0021700000, 0.0014600000, 0.0010000000,
0.0007020000, 0.0004990000, 0.0003600000, 0.0002640000, 0.0001960000,
0.0001470000, 0.0001120000, 0.0000856000, 0.0000663000, 0.0000518000,
0.0000408000, 0.0000324000, 0.0000259000, 0.0000209000, 0.0000169000,
0.0000138000, 0.0000113000]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 0.0145000000, 0.0084600000, 0.0050900000, 0.0031400000, 0.0019900000,
0.0012900000, 0.0008520000, 0.0005740000, 0.0003940000, 0.0002750000,
0.0001940000, 0.0001400000, 0.0001010000, 0.0000746000, 0.0000555000,
0.0000417000, 0.0000316000, 0.0000242000, 0.0000187000, 0.0000146000,
0.0000114000, 0.0000090100, 0.0000071600, 0.0000057300]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0053100000, 0.0031700000,
0.0019400000, 0.0012100000, 0.0007750000, 0.0005050000, 0.0003350000,
0.0002260000, 0.0001550000, 0.0001080000, 0.0000759000, 0.0000542000,
0.0000392000, 0.0000286000, 0.0000211000, 0.0000157000, 0.0000118000,
0.0000089600, 0.0000068500, 0.0000052800, 0.0000041000, 0.0000032000]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0033400000,
0.0019800000, 0.0012000000, 0.0007440000, 0.0004700000, 0.0003020000,
0.0001980000, 0.0001320000, 0.0000889000, 0.0000609000, 0.0000423000,
0.0000297000, 0.0000211000, 0.0000152000, 0.0000110000, 0.0000080700,
0.0000059700, 0.0000044500, 0.0000033500, 0.0000025400, 0.0000019400]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
0.0021000000, 0.0012400000, 0.0007470000, 0.0004590000, 0.0002870000,
0.0001830000, 0.0001180000, 0.0000777000, 0.0000518000, 0.0000350000,
0.0000240000, 0.0000166000, 0.0000116000, 0.0000082300, 0.0000058900,
0.0000042500, 0.0000031000, 0.0000022800, 0.0000016900, 0.0000012600]),
new Float32Array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
0.0007780000, 0.0004660000, 0.0002840000, 0.0001760000, 0.0001110000,
0.0000712000, 0.0000463000, 0.0000305000, 0.0000204000, 0.0000138000,
0.0000094200, 0.0000065200, 0.0000045600, 0.0000032200, 0.0000022900,
0.0000016500, 0.0000012000, 0.0000008740]),
]
/**
* Given a number of hash functions (k) and a target false-positive rate (targetError),
* determines the minimum (m/n) bits-per-element that satisfies the error threshold.
*
* In the context of a Bloom filter:
* - m is the total number of bits in the filter.
* - n is the number of elements you expect to insert.
* Thus, (m/n) describes how many bits are assigned per inserted element.
*
* Example:
* ```ts
* // We want to use 3 hash functions (k=3) and a false-positive rate of 1% (targetError=0.01).
* const mOverN = getMOverNBitsForK(3, 0.01);
* // The function will iterate through the error tables and find the smallest m/n that satisfies the error threshold.
* // In this case, kErrors[3][5] is the first value in the vector kErrors[3] that is less than 0.01 (0.0920000000).
* console.log(mOverN); // 5
* ```
*
* @param k - The number of hash functions.
* @param targetError - The desired maximum false-positive rate.
* @param probabilityTable - An optional table of false-positive probabilities indexed by k.
* @returns The smallest (m/n) bit ratio for which the false-positive rate is below targetError.
* @throws If k is out of range or if no suitable ratio can be found.
*/
export function getMOverNBitsForK(
k: number,
targetError: number,
probabilityTable = kErrors
): number {
// Returns the optimal number of m/n bits for a given k.
if (k < 0 || k > 12) {
throw new Error("k must be <= 12.");
}
for (let mOverN = 2; mOverN < probabilityTable[k].length; mOverN++) {
if (probabilityTable[k][mOverN] < targetError) {
return mOverN;
}
}
throw new Error(
"Specified value of k and error rate not achievable using less than 4 bytes / element."
);
}

View File

@ -0,0 +1,3 @@
{
"extends": "../../tsconfig.dev"
}

View File

@ -0,0 +1,10 @@
{
"extends": "../../tsconfig",
"compilerOptions": {
"outDir": "dist/",
"rootDir": "src",
"tsBuildInfoFile": "dist/.tsbuildinfo"
},
"include": ["src"],
"exclude": ["src/**/*.spec.ts", "src/test_utils"]
}

View File

@ -0,0 +1,4 @@
{
"extends": ["../../typedoc.base.json"],
"entryPoints": ["src/index.ts"]
}