Files
Roland Hummel 86d333ee94 feat: Test running overhaul, switch to Prettier & reformat everything (#1407)
* chore: Switch to Node 20 + Vitest

* chore: migrate to vitest mock functions

* chore: code style (switch to prettier)

* test: re-enable long-running test

Seems the switch to Node 20 and Vitest has vastly improved the code's and / or the test's runtime!

see #1193

* chore: code style

* chore: fix failing tests

* Updated Documentation in README.md

* Update contribution guidelines to state usage of Prettier

* fix: set prettier printWidth back to 80

* chore: apply updated code style automatically

* fix: set prettier line endings to lf again

* chore: apply updated code style automatically

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Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: Lars Müller <34514239+appgurueu@users.noreply.github.com>
2023-10-04 02:38:19 +05:30

97 lines
2.6 KiB
JavaScript

/*
Given a data set of an unknown size,
Get a random sample in a random order
It's used in data analytics, often as a way to get a small random sample from a data lake or warehouse, or from a large CSV file
*/
function shuf(datasetSource, sampleSize) {
const output = fillBaseSample(datasetSource, sampleSize)
return randomizeOutputFromDataset(datasetSource, output)
}
/**
* Fills the output if possible, with the minimum number of values
* @param {Iterable.<T>} datasetSource The iterable source of data
* @param {number} sampleSize The size of the sample to extract from the dataset
* @returns {Array.<T>} The random sample, as an array
* @template T
*/
function fillBaseSample(datasetSource, sampleSize) {
let filledIndexes = []
let output = new Array(sampleSize)
// Spread data out filling the array
while (true) {
const iterator = datasetSource.next()
if (iterator.done) break
let insertTo = Math.floor(Math.random() * output.length)
while (filledIndexes.includes(insertTo)) {
insertTo++
if (insertTo === output.length) {
insertTo = 0
}
}
output[insertTo] = {
value: iterator.value
}
filledIndexes = [...filledIndexes, insertTo]
if (filledIndexes.length === sampleSize) {
break
}
}
if (filledIndexes.length < output.length) {
// Not a large enough dataset to fill the sample - trim empty values
output = output.filter((_, i) => filledIndexes.includes(i))
}
return output.map((o) => o.value)
}
/**
* Replaces values in the output randomly with new ones from the dataset
* @param {Iterable.<T>} datasetSource The iterable source of data
* @param {Array.<T>} output The output so far, filled with data
* @returns {Array.<T>} The random sample, as an array
* @template T
*/
function randomizeOutputFromDataset(datasetSource, output) {
const newOutput = [...output]
let readSoFar = output.length
while (true) {
const iterator = datasetSource.next()
if (iterator.done) break
readSoFar++
const insertTo = Math.floor(Math.random() * readSoFar)
if (insertTo < newOutput.length) {
newOutput[insertTo] = iterator.value
}
}
return newOutput
}
// Example
/**
* Generates a random range of data, with values between 0 and 2^31 - 1
* @param {number} length The number of data items to generate
* @returns {Iterable<number>} Random iterable data
*/
function* generateRandomData(length) {
const maxValue = Math.pow(2, 31) - 1
for (let i = 0; i < length; i++) {
yield Math.floor(Math.random() * maxValue)
}
}
// const source = generateRandomData(1000)
// const result = shuf(source, 10)
export { shuf, generateRandomData }