diff --git a/.eslintrc.js b/.eslintrc.js new file mode 100644 index 0000000..5e5075e --- /dev/null +++ b/.eslintrc.js @@ -0,0 +1,22 @@ +module.exports = { + ignorePatterns: ['**/*.d.ts', '**/*.test.ts', '**/*.js'], + parser: '@typescript-eslint/parser', + extends: ['plugin:@typescript-eslint/recommended'], + plugins: ['header'], + parserOptions: { + ecmaVersion: 2018, // Allows for the parsing of modern ECMAScript features + sourceType: 'module', // Allows for the use of imports + }, + rules: { + '@typescript-eslint/no-use-before-define': 'off', + '@typescript-eslint/explicit-function-return-type': 'off', + '@typescript-eslint/explicit-module-boundary-types': 'off', + 'header/header': [ + 'error', + 'block', + '---------------------------------------------------------\n * Copyright (C) Microsoft Corporation. All rights reserved.\n *--------------------------------------------------------', + ], + // Place to specify ESLint rules. Can be used to overwrite rules specified from the extended configs + // e.g. "@typescript-eslint/explicit-function-return-type": "off", + }, +}; diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..f9ba8cf --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,9 @@ +# Microsoft Open Source Code of Conduct + +This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). + +Resources: + +- [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/) +- [Microsoft Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) +- Contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with questions or concerns diff --git a/LICENSE b/LICENSE index 15f7017..9e841e7 100644 --- a/LICENSE +++ b/LICENSE @@ -1,21 +1,21 @@ -MIT License + MIT License -Copyright (c) 2016 Beam Interactive Inc. + Copyright (c) Microsoft Corporation. -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to deal + in the Software without restriction, including without limitation the rights + to use, copy, modify, merge, publish, distribute, sublicense, and/or sell + copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. + The above copyright notice and this permission notice shall be included in all + copies or substantial portions of the Software. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + SOFTWARE diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 0000000..424cd50 --- /dev/null +++ b/package-lock.json @@ -0,0 +1,2297 @@ +{ + "name": "uts", + "version": "1.1.3", + "lockfileVersion": 1, + "requires": true, + "dependencies": { + "@babel/code-frame": { + "version": "7.10.4", + "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.10.4.tgz", + "integrity": "sha512-vG6SvB6oYEhvgisZNFRmRCUkLz11c7rp+tbNTynGqc6mS1d5ATd/sGyV6W0KZZnXRKMTzZDRgQT3Ou9jhpAfUg==", + "dev": true, + "requires": { + "@babel/highlight": "^7.10.4" + } + }, + "@babel/helper-validator-identifier": { + "version": "7.10.4", + "resolved": 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+ "printWidth": 100, + "tabWidth": 2, + "arrowParens": "avoid" + }, "homepage": "https://github.com/WatchBeam/uts#readme", "devDependencies": { - "chai": "^3.5.0", - "mocha": "^3.1.0", - "typescript": "^2.0.3", - "sinon": "^1.17.6" + "@types/chai": "^4.2.12", + "@types/mocha": "^8.0.3", + "@types/sinon": "^9.0.5", + "@typescript-eslint/eslint-plugin": "^4.1.1", + "@typescript-eslint/parser": "^4.1.1", + "chai": "^4.2.0", + "eslint": "^7.9.0", + "eslint-plugin-header": "^3.1.0", + "mocha": "^8.1.3", + "prettier": "^2.1.1", + "sinon": "^9.0.3", + "typescript": "^4.0.2" } } diff --git a/readme.md b/readme.md index ca2c680..dfc1469 100644 --- a/readme.md +++ b/readme.md @@ -1,6 +1,8 @@ # μts [![Build Status](https://travis-ci.org/mixer/uts.svg?branch=master)](https://travis-ci.org/mixer/uts) ![npm](https://img.shields.io/npm/dt/uts.svg) ![npm bundle size](https://img.shields.io/bundlephobia/minzip/uts.svg) -μts is a miniature time-series database suitable for embedded or frontend web applications, weighing in at about 1.5 KB minified and gzipped. +μts is a miniature time-series database utility suitable for embedded or frontend web applications, weighing in at about 1.5 KB minified and gzipped. + +This was originally written [at Mixer](https://github.com/mixer/uts). ### Installation @@ -10,7 +12,7 @@ npm install --save uts ### Usage -This is an evolving project. Reading the source and the [tests](./test.js) are the best way to see what it can do. +Reading the source and the [tests](./test.js) are the best way to see what it can do. μts is schemaless, data is arranged in points, which contain one more columns, within series. Aggregations can be run which operate on points or columns. Currently supported aggregations are: @@ -50,3 +52,16 @@ db.series('bandwidth').query({ ] ``` +# Contributing + +This project welcomes contributions and suggestions. Most contributions require you to agree to a +Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us +the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com. + +When you submit a pull request, a CLA bot will automatically determine whether you need to provide +a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions +provided by the bot. You will only need to do this once across all repos using our CLA. + +This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). +For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or +contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. diff --git a/security.md b/security.md new file mode 100644 index 0000000..a050f36 --- /dev/null +++ b/security.md @@ -0,0 +1,41 @@ + + +## Security + +Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), and [our GitHub organizations](https://opensource.microsoft.com/). + +If you believe you have found a security vulnerability in any Microsoft-owned repository that meets [Microsoft's definition of a security vulnerability](https://docs.microsoft.com/en-us/previous-versions/tn-archive/cc751383(v=technet.10)), please report it to us as described below. + +## Reporting Security Issues + +**Please do not report security vulnerabilities through public GitHub issues.** + +Instead, please report them to the Microsoft Security Response Center (MSRC) at [https://msrc.microsoft.com/create-report](https://msrc.microsoft.com/create-report). + +If you prefer to submit without logging in, send email to [secure@microsoft.com](mailto:secure@microsoft.com). If possible, encrypt your message with our PGP key; please download it from the [Microsoft Security Response Center PGP Key page](https://www.microsoft.com/en-us/msrc/pgp-key-msrc). + +You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Additional information can be found at [microsoft.com/msrc](https://www.microsoft.com/msrc). + +Please include the requested information listed below (as much as you can provide) to help us better understand the nature and scope of the possible issue: + + * Type of issue (e.g. buffer overflow, SQL injection, cross-site scripting, etc.) + * Full paths of source file(s) related to the manifestation of the issue + * The location of the affected source code (tag/branch/commit or direct URL) + * Any special configuration required to reproduce the issue + * Step-by-step instructions to reproduce the issue + * Proof-of-concept or exploit code (if possible) + * Impact of the issue, including how an attacker might exploit the issue + +This information will help us triage your report more quickly. + +If you are reporting for a bug bounty, more complete reports can contribute to a higher bounty award. Please visit our [Microsoft Bug Bounty Program](https://microsoft.com/msrc/bounty) page for more details about our active programs. + +## Preferred Languages + +We prefer all communications to be in English. + +## Policy + +Microsoft follows the principle of [Coordinated Vulnerability Disclosure](https://www.microsoft.com/en-us/msrc/cvd). + + diff --git a/src/test.ts b/src/test.ts new file mode 100644 index 0000000..fd66e93 --- /dev/null +++ b/src/test.ts @@ -0,0 +1,329 @@ +/*--------------------------------------------------------- + * Copyright (C) Microsoft Corporation. All rights reserved. + *--------------------------------------------------------*/ + +import sinon from 'sinon'; +import { expect } from 'chai'; +import { TSDB } from './uts'; + +describe('querying', () => { + let tsdb: TSDB; + let clock: sinon.SinonFakeTimers; + let now: number; + + beforeEach(() => { + clock = sinon.useFakeTimers(1000); + tsdb = new TSDB(); + + now = Date.now(); + for (let i = 0; i < 5; i++) { + tsdb.series('a').insert( + { + my_col1: i, + my_col2: i * 2, + }, + now - (4 - i) * 100, + ); + } + for (let i = 0; i < 5; i++) { + tsdb.series('b').insert( + { + my_col1: Math.pow(i, 2), + }, + now - (4 - i) * 100, + ); + } + }); + + afterEach(() => clock.restore()); + + it('runs map() aggregations', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + }), + ).to.deep.equal([ + { + results: { + data: [0, 1, 2, 3, 4], + }, + }, + ]); + + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map(pt => pt.get('my_col2')) }, + }), + ).to.deep.equal([ + { + results: { + data: [0, 2, 4, 6, 8], + }, + }, + ]); + }); + + it('runs mean() aggregations', () => { + expect( + tsdb.series('a').query({ + metrics: { mean: TSDB.mean('my_col1') }, + }), + ).to.deep.equal([ + { + results: { mean: 2 }, + }, + ]); + }); + + it('runs max() aggregations', () => { + expect( + tsdb.series('a').query({ + metrics: { max: TSDB.max('my_col1') }, + }), + ).to.deep.equal([ + { + results: { max: 4 }, + }, + ]); + }); + + it('runs min() aggregations', () => { + expect( + tsdb.series('a').query({ + metrics: { min: TSDB.min('my_col1') }, + }), + ).to.deep.equal([ + { + results: { min: 0 }, + }, + ]); + }); + + it('runs derivative() aggregations #1', () => { + expect( + tsdb + .series('b') + .query({ + metrics: { der: TSDB.derivative('my_col1', 100) }, + })[0] + .results.der.map(pt => pt.toObject()), + ).to.deep.equal([ + { time: now - 300, my_col1: 1 }, + { time: now - 200, my_col1: 3 }, + { time: now - 100, my_col1: 5 }, + { time: now, my_col1: 7 }, + ]); + }); + + it('runs derivative() aggregations #2', () => { + expect( + tsdb + .series('b') + .query({ + metrics: { der: TSDB.derivative('my_col1', 200) }, + })[0] + .results.der.map(pt => pt.toObject()), + ).to.deep.equal([ + { time: now - 200, my_col1: 4 }, + { time: now, my_col1: 12 }, + ]); + }); + + it('runs derivative() aggregations #4', () => { + expect( + tsdb + .series('b') + .query({ + metrics: { der: TSDB.derivative('my_col1', 500) }, + })[0] + .results.der.map(pt => pt.toObject()), + ).to.deep.equal([{ time: now, my_col1: 16 }]); + }); + + it('runs derivative() aggregations #5', () => { + expect( + tsdb + .series('q') + .query({ + metrics: { der: TSDB.derivative('my_col1', 500) }, + })[0] + .results.der.map(pt => pt.toObject()), + ).to.deep.equal([]); + }); + + it('runs last() aggregations', () => { + expect( + tsdb.series('a').query({ + metrics: { last: TSDB.last('my_col1') }, + group: TSDB.interval(250, false), + }), + ).to.deep.equal([ + { + results: { last: 4 }, + group: { start: now - 250, width: 250 }, + }, + { + results: { last: 1 }, + group: { start: now - 500, width: 250 }, + }, + ]); + }); + + it('runs last() aggregations', () => { + expect( + tsdb.series('a').query({ + metrics: { last: TSDB.last('my_col1') }, + group: TSDB.interval(250, false), + }), + ).to.deep.equal([ + { + results: { last: 4 }, + group: { start: now - 250, width: 250 }, + }, + { + results: { last: 1 }, + group: { start: now - 500, width: 250 }, + }, + ]); + }); + + it('time shifts the interval grouper', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + group: TSDB.interval(250, false, now - 100), + }), + ).to.deep.equal([ + { + results: { data: [1, 2, 3] }, + group: { start: now - 350, width: 250 }, + }, + { + results: { data: [0] }, + group: { start: now - 600, width: 250 }, + }, + ]); + }); + + it('runs grouped() aggregations #1', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + group: TSDB.interval(250, false), + }), + ).to.deep.equal([ + { + results: { data: [2, 3, 4] }, + group: { start: now - 250, width: 250 }, + }, + { + results: { data: [0, 1] }, + group: { start: now - 500, width: 250 }, + }, + ]); + }); + + it('runs grouped() aggregations #2', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + group: TSDB.interval(100, false), + where: { time: { is: '>', than: now - 300 } }, + }), + ).to.deep.equal([ + { + results: { data: [4] }, + group: { start: now - 100, width: 100 }, + }, + { + results: { data: [3] }, + group: { start: now - 200, width: 100 }, + }, + { + results: { data: [2] }, + group: { start: now - 300, width: 100 }, + }, + ]); + }); + + it('runs grouped() aggregations #3', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + group: TSDB.interval(100, false), + where: { time: { is: '>', than: now } }, + }), + ).to.deep.equal([]); + }); + + it('respects single where clauses', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + where: { time: { is: '>', than: now - 300 } }, + }), + ).to.deep.equal([ + { + results: { + data: [2, 3, 4], + }, + }, + ]); + }); + + it('respects multiple where clauses', () => { + expect( + tsdb.series('a').query({ + metrics: { data: TSDB.map('my_col1') }, + where: { + time: [ + { is: '>', than: now - 300 }, + { is: '<', than: now }, + ], + }, + }), + ).to.deep.equal([ + { + results: { + data: [2, 3], + }, + }, + ]); + }); + + it('drops all data', () => { + tsdb.series('a').remove(); + expect( + tsdb.series('a').query({ + metrics: { total: TSDB.count() }, + }), + ).to.deep.equal([ + { + results: { + total: 0, + }, + }, + ]); + }); + + it('drops data matching a clause', () => { + tsdb.series('a').remove({ + time: [ + { is: '>', than: now - 300 }, + { is: '<', than: now }, + ], + }); + + expect( + tsdb.series('a').query({ + metrics: { time: TSDB.map('time') }, + }), + ).to.deep.equal([ + { + results: { + time: [600, 700, 1000], + }, + }, + ]); + }); +}); diff --git a/src/uts.ts b/src/uts.ts new file mode 100644 index 0000000..52d4349 --- /dev/null +++ b/src/uts.ts @@ -0,0 +1,652 @@ +/*--------------------------------------------------------- + * Copyright (C) Microsoft Corporation. All rights reserved. + *--------------------------------------------------------*/ + +/** + * The Bin is used internally in the query system and holds analysis for + * a group. + */ +export class Bin { + private columns: string[]; + private metrics: { [column: string]: Aggregate } = {}; + private _size = 0; + + /** + * The bin holds data for a group of time series metrics. + * @param {Object} metrics + * @param {Object} group arbitrary object describing the grouping of + * the contained metrics. + */ + constructor(metrics: { [column: string]: () => Aggregate }, private group?: any) { + this.columns = Object.keys(metrics); + this.columns.forEach(col => { + this.metrics[col] = metrics[col](); + }); + } + + /** + * Returns the number of points in this bin. + * @return {Number} + */ + size(): number { + return this._size; + } + + /** + * Adds new data to the bin. + * @param {Point} point + * @return {Bin} + */ + push(point: Point): this { + this._size++; + + for (let i = 0; i < this.columns.length; i++) { + const col = this.columns[i]; + this.metrics[col].push(point); + } + + return this; + } + + /** + * Serializes the bin to a results object. + * @return {Object} + */ + toObject(): BinResult { + const out: BinResult = { results: {} }; + + if (this.group) { + out.group = this.group; + } + + this.columns.forEach(col => { + out.results[col] = this.metrics[col].serialize(); + }); + + return out; + } +} + +/** + * Parent class of groupers. + */ +export abstract class Group { + protected _where: { [col: string]: Comparator | Comparator[] } = {}; + + /** + * Sets the `where` object this query is being called with. + * @param {Object} where + * @return {Group} + */ + public where(where: { [col: string]: Comparator | Comparator[] }): this { + this._where = where; + return this; + } + + protected getWhere(column: string): Comparator[] { + const clause = this._where[column]; + if (!clause) { + return []; + } + + return Array.isArray(clause) ? clause : [clause]; + } + + /** + * Returns a list of bins with points added to them. + */ + abstract binify(data: Point[], metrics: { [column: string]: () => Aggregate }): Bin[]; +} + +/** + * The IntervalGrouper groups data based on time. + */ +class IntervalGrouper extends Group { + /** + * @param {Number} interval the size, in milliseconds, of each group bin + * @param {Boolean} fill whether to zero-fill bins that don't have data + */ + constructor(private interval: number, private fill: boolean, private now: number) { + super(); + } + + binify(data: Point[], metrics: { [column: string]: () => Aggregate }): Bin[] { + let start: number; + const timeBound = this.getWhere('time').find(time => time.is === '>'); + if (timeBound) { + start = timeBound.than; + } else { + start = data[0].getTime(); + } + + const { interval, now } = this; + const count = Math.floor((now - start) / interval) + 1; + + let bins = new Array(); + for (let i = 0; i < count; i++) { + bins.push( + new Bin(metrics, { + start: now - (i + 1) * interval, + width: interval, + }), + ); + } + + for (let i = 0; i < data.length; i++) { + const time = data[i].getTime(); + if (time > now) { + break; + } + + bins[Math.floor((now - time) / interval)].push(data[i]); + } + + if (!this.fill) { + bins = bins.filter(b => b.size() > 0); + } + + return bins; + } +} + +/** + * The AnyGrouper is the "base" grouper that just shoves all the data into + * a single bin. + */ +class AnyGrouper extends Group { + binify(data: Point[], metrics: { [column: string]: () => Aggregate }): Bin[] { + const bin = new Bin(metrics); + for (let i = 0; i < data.length; i++) { + bin.push(data[i]); + } + + return [bin]; + } +} + +export type PointData = { + [column: string]: any; +}; + +/** + * A Point is the minimal item of data within a Series. It stores one or more + * properties that can be analyzed, as well as the time it was inserted. + */ +export class Point { + /** + * Creates a new point for insertion into a time series. + * @param {Object} data + * @param {[Number]} time insertion time in milliseconds + */ + constructor(private data: PointData, time = Date.now()) { + this.data['time'] = time; + } + + /** + * Gets a property from the point, returning the default value if + * it doens't exist. + */ + public get(prop: string): T | undefined; + public get(prop: string, defaultValue: T): T; + public get(prop: string, defaultValue?: T): T { + return this.has(prop) ? this.data[prop] : defaultValue; + } + + /** + * Returns true if this point contains the provided property. + */ + public has(prop: string) { + return this.data.hasOwnProperty(prop); + } + + /** + * Returns the time this point was inserted at. + * @return {Number} milliseconds timestamp + */ + public getTime(): number { + return this.data['time']; + } + + /** + * Clones and converts the point to a plain object. + */ + public toObject(): PointData { + const out: PointData = {}; + Object.keys(this.data).forEach(key => (out[key] = this.data[key])); + return out; + } +} + +export type BinaryOperator = '>' | '<' | '='; + +/** + * The Comparator can be passed into the series query to compare values + * to each other. + */ +export interface Comparator { + is: BinaryOperator; + than: any; +} + +/** + * BinResults are returned from time series queries. + */ +export interface BinResult { + group?: any; + results: { [column: string]: any }; +} + +/** + * Series contains a logical grouping of results that can be aggregated. + */ +export class Series { + private interval = 0; + private data = new Array(); + + /** + * Sets how long data will be stored in the provided series. + * @param {Number} ttl duration in milliseconds + * If zero, all data will be kept + */ + public setRetention(ttl: number) { + clearInterval(this.interval); + + if (ttl === 0) { + return; + } + + this.interval = setInterval(() => { + const threshold = Date.now() - ttl; + + let i = 0; + while (this.data[i] && this.data[i].getTime() < threshold) { + i++; + } + + if (i > 0) { + this.data = this.data.slice(i); + } + }, 1000); + } + + /** + * Inserts new data into the series at the specified time, + * defaulting to the current time if not provided. + */ + public insert(data: any, time?: number) { + this.data.push(data instanceof Point ? data : new Point(data, time)); + return this; + } + + /** + * Coverts a comparator `where` from a query into a predicate function. + * @param {Object} cmp + * @return {Function} + */ + private buildComparator(cmp: { + [col: string]: Comparator | Comparator[]; + }): (pt: Point) => boolean { + const fns = Object.keys(cmp).reduce((allFns, col) => { + let comparators = cmp[col]; + if (!Array.isArray(cmp[col])) { + comparators = [comparators]; + } + + const cmpFns = (comparators).map(comp => { + const comparator = comp.is; + const value = comp.than; + + return (pt: Point): boolean => { + const v = pt.get(col); + if (v === undefined) { + return false; + } + + switch (comparator) { + case '>': + return v > value; + case '<': + return v < value; + case '=': + return v === value; + default: + throw new Error(`Unknown comparator '${comparator}'`); + } + }; + }); + + return [...allFns, ...cmpFns]; + }, [] as ((pt: Point) => boolean)[]); + + return pt => { + for (let i = 0; i < fns.length; i++) { + if (!fns[i](pt)) { + return false; + } + } + + return true; + }; + } + + /** + * deleteBy removes series data that matches the comparison. If no + * comparator is given, then all data is removed. + */ + public remove(query?: { [col: string]: Comparator | Comparator[] }): this { + if (!query) { + this.data = []; + return this; + } + + const comparator = this.buildComparator(query); + this.data = this.data.filter(pt => !comparator(pt)); + return this; + } + + /** + * Runs a query against the time series. + * @example + * + * db.series('bandwidth').query({ + * metrics: { + * mean: db.mean('bits'), + * }, + * where: { + * time: { is: '>', than: Date.now() - 5 * 60 * 100 } + * }, + * group: db.interval(30 * 1000, true), + * }); + * + * // returns: + * + * [{ + * group: { start: 1459513952592, end: 1459513982592 }, + * metrics: { + * mean: 3511 + * } + * }, { + * // ... + * }] + */ + public query(options: { + metrics: { [col: string]: () => Aggregate }; + where?: { [col: string]: Comparator | Comparator[] }; + group?: Group; + }): BinResult[] { + options.where = options.where || {}; + options.group = options.group || new AnyGrouper(); + + const data = this.data.filter(this.buildComparator(options.where)); + + return options.group + .where(options.where) + .binify(data, options.metrics) + .map(bin => bin.toObject()); + } + + /** + * Frees resources associated with the time series. Subsequent attempted + * usages of the series will throw an error. + */ + public destroy() { + clearInterval(this.interval); + } +} + +export interface Aggregate { + /** + * Adds a new point to the aggregate. + */ + push(point: Point): void; + + /** + * Returns the aggregate's result for returning in the query results. + */ + serialize(): any; +} + +class Mapper implements Aggregate { + private data = new Array(); + + /** + * Mapper returns the results of a mapping function on the points. + */ + constructor(private fn: (pt: Point) => any) {} + + public push(pt: Point) { + this.data.push(this.fn(pt)); + } + + public serialize() { + return this.data; + } +} + +class Reducer implements Aggregate { + private result: T; + + /** + * Mapper returns the results of a mapping function on the points. + */ + constructor(private fn: (current: T, pt: Point) => T, initial: T) { + this.result = initial; + } + + public push(pt: Point) { + this.result = this.fn(this.result, pt); + } + + public serialize() { + return this.result; + } +} + +class Average implements Aggregate { + private sum = 0; + private count = 0; + + /** + * Average computes the arithmetic mean of the specified column. + */ + constructor(private column: string) {} + + public push(pt: Point) { + if (pt.has(this.column)) { + this.sum += pt.get(this.column, 0); + this.count += 1; + } + } + + public serialize() { + return this.count === 0 ? 0 : this.sum / this.count; + } +} + +class Derivative implements Aggregate { + private lastChange = 0; + private lastValue?: number; + private lastTime?: number; + private leadingTime?: number; + + private points = new Array(); + + /** + * Derivative plots changes in a column's value. + */ + constructor(private column: string, private interval: number) {} + + public push(pt: Point) { + const value = pt.get(this.column); + if (!value) { + return; + } + + const time = pt.getTime(); + if (this.lastTime === undefined || this.lastValue === undefined) { + this.lastTime = time; + this.lastValue = value; + } + + while (this.lastTime + this.interval < time) { + this.pushPoint(this.lastTime + this.interval); + } + + this.lastChange += value - this.lastValue; + this.lastValue = value; + this.leadingTime = time; + } + + private pushPoint(time: number) { + this.points.push(new Point({ [this.column]: this.lastChange }, time)); + + this.lastChange = 0; + this.lastTime = time; + } + + public serialize() { + if (this.leadingTime !== undefined) { + this.pushPoint(this.leadingTime); + } + + return this.points; + } +} + +/** + * TSDB is a miniature time-series database in plain Js. It functions as follows: + * - The database has many Series, identified by their name as strings. + * - You can push data to each Series. + * - Later, you can query for data in the Series. Data is always passed + * through a grouper when you query if (even if it groups all points + * together) and you can also attach aggregators to it. + * - Each group creates a bunch of "bins", and pushed each data point + * in the query to one or more bins. + * - Each bin stores one or more aggregators, like "mean", which analyze + * data in that bin + * - At the end of the query, the grouper returns the bins it created + * which are then serialized and passed back to the caller. + */ +export class TSDB { + private _series: { [name: string]: Series } = {}; + private _defaultRetention = 0; + + /** + * Sets the default series retention time in milliseconds. + */ + public defaultRetention(ttl: number) { + this._defaultRetention = ttl; + } + + /** + * Returns a new Series, creating one if it did not already exist. + * @param {String} name + * @return {Series} + */ + public series(name: string): Series { + if (!this._series.hasOwnProperty(name)) { + this._series[name] = new Series(); + this._series[name].setRetention(this._defaultRetention); + } + + return this._series[name]; + } + + /** + * Tears down the database. + */ + public destroy() { + Object.keys(this._series).forEach(s => this._series[s].destroy()); + this._series = {}; + } + + /** + * Creates an analysis which runs a custom mapping function on points, + * returning the mapping results. If the `mapper` is a string, it'll + * extract the specified column from the results, lodash style. + */ + public static map(mapper: string | ((pt: Point) => any)): () => Aggregate { + let fn: (pt: Point) => any; + if (typeof mapper === 'function') { + fn = mapper; + } else { + fn = pt => pt.get(mapper); + } + + return () => new Mapper(fn); + } + + /** + * Creates an analysis which runs a custom mapping function on points, + * returning the mapping results. If the `mapper` is a string, it'll + * extract the specified column from the results, lodash style. + */ + public static reduce(fn: (current: T, pt: Point) => T, initial: T): () => Aggregate { + return () => new Reducer(fn, initial); + } + + /** + * Creates a mean metric analysis passed into Series.Query + */ + public static mean(column: string): () => Aggregate { + return () => new Average(column); + } + + /** + * Creates a max metric analysis passed into Series.Query + */ + public static max(column: string): () => Aggregate { + return this.reduce((max, pt) => Math.max(pt.get(column, -Infinity), max), 0); + } + + /** + * Creates a min metric analysis passed into Series.Query + */ + public static min(column: string): () => Aggregate { + return this.reduce((min, pt) => Math.min(pt.get(column, Infinity), min), 0); + } + + /** + * Creates an analysis which returns points that plot changes in a column, + * within a specified interval. + */ + public static derivative(column: string, interval: number): () => Aggregate { + return () => new Derivative(column, interval); + } + + /** + * Creates an analysis that gets the most recent + * value of the specified column. + */ + public static last(column: string): () => Aggregate { + return this.reduce((x, pt) => pt.get(column, null), null); + } + + /** + * Creates a sum metric analysis passed into Series.Query + */ + public static sum(column: string): () => Aggregate { + return this.reduce((sum, pt) => sum + pt.get(column, 0), 0); + } + + /** + * Creates a count analysis passed into Series.Query. By default, counts + * all columns, or you can pass a column to only count points that have + * that column. + */ + public static count(column = '*'): () => Aggregate { + return this.reduce((sum, pt) => { + if (column === '*' || pt.get(column) !== undefined) { + return sum + 1; + } + return sum; + }, 0); + } + + /** + * Creates a new grouper based on time intervals. + */ + public static interval(interval: number, fill = true, now: number = Date.now()): Group { + return new IntervalGrouper(interval, fill, now); + } +} diff --git a/test.js b/test.js deleted file mode 100644 index d221ef2..0000000 --- a/test.js +++ /dev/null @@ -1,313 +0,0 @@ -'use strict' - -/* eslint-env mocha */ - -const TSDB = require('./').TSDB -const sinon = require('sinon') -const chai = require('chai') -const expect = chai.expect - -describe('querying', () => { - let tsdb - let clock - let now - beforeEach(() => { - clock = sinon.useFakeTimers(1000) - tsdb = new TSDB() - - now = Date.now() - for (let i = 0; i < 5; i++) { - tsdb.series('a').insert({ - my_col1: i, - my_col2: i * 2 - }, now - (4 - i) * 100) - } - for (let i = 0; i < 5; i++) { - tsdb.series('b').insert({ - my_col1: Math.pow(i, 2) - }, now - (4 - i) * 100) - } - }) - - afterEach(() => clock.restore()) - - it('runs map() aggregations', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') } - }) - ).to.deep.equal([ - { - results: { - data: [0, 1, 2, 3, 4] - } - } - ]) - - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map(pt => pt.get('my_col2')) } - }) - ).to.deep.equal([ - { - results: { - data: [0, 2, 4, 6, 8] - } - } - ]) - }) - - it('runs mean() aggregations', () => { - expect( - tsdb.series('a').query({ - metrics: { mean: TSDB.mean('my_col1') } - }) - ).to.deep.equal([ - { - results: { mean: 2 } - } - ]) - }) - - it('runs max() aggregations', () => { - expect( - tsdb.series('a').query({ - metrics: { max: TSDB.max('my_col1') } - }) - ).to.deep.equal([ - { - results: { max: 4 } - } - ]) - }) - - it('runs min() aggregations', () => { - expect( - tsdb.series('a').query({ - metrics: { min: TSDB.min('my_col1') } - }) - ).to.deep.equal([ - { - results: { min: 0 } - } - ]) - }) - - it('runs derivative() aggregations #1', () => { - expect( - tsdb.series('b').query({ - metrics: { der: TSDB.derivative('my_col1', 100) } - })[0].results.der.map(pt => pt.toObject()) - ).to.deep.equal([ - { time: now - 300, my_col1: 1 }, - { time: now - 200, my_col1: 3 }, - { time: now - 100, my_col1: 5 }, - { time: now, my_col1: 7 } - ]) - }) - - it('runs derivative() aggregations #2', () => { - expect( - tsdb.series('b').query({ - metrics: { der: TSDB.derivative('my_col1', 200) } - })[0].results.der.map(pt => pt.toObject()) - ).to.deep.equal([ - { time: now - 200, my_col1: 4 }, - { time: now, my_col1: 12 } - ]) - }) - - it('runs derivative() aggregations #4', () => { - expect( - tsdb.series('b').query({ - metrics: { der: TSDB.derivative('my_col1', 500) } - })[0].results.der.map(pt => pt.toObject()) - ).to.deep.equal([ - { time: now, my_col1: 16 } - ]) - }) - - it('runs derivative() aggregations #5', () => { - expect( - tsdb.series('q').query({ - metrics: { der: TSDB.derivative('my_col1', 500) } - })[0].results.der.map(pt => pt.toObject()) - ).to.deep.equal([]) - }) - - it('runs last() aggregations', () => { - expect( - tsdb.series('a').query({ - metrics: { last: TSDB.last('my_col1') }, - group: TSDB.interval(250, false) - }) - ).to.deep.equal([ - { - results: { last: 4 }, - group: { start: now - 250, width: 250 } - }, - { - results: { last: 1 }, - group: { start: now - 500, width: 250 } - } - ]) - }) - - it('runs last() aggregations', () => { - expect( - tsdb.series('a').query({ - metrics: { last: TSDB.last('my_col1') }, - group: TSDB.interval(250, false) - }) - ).to.deep.equal([ - { - results: { last: 4 }, - group: { start: now - 250, width: 250 } - }, - { - results: { last: 1 }, - group: { start: now - 500, width: 250 } - } - ]) - }) - - it('time shifts the interval grouper', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') }, - group: TSDB.interval(250, false, now - 100) - }) - ).to.deep.equal([ - { - results: { data: [1, 2, 3] }, - group: { start: now - 350, width: 250 } - }, - { - results: { data: [0] }, - group: { start: now - 600, width: 250 } - } - ]) - }) - - it('runs grouped() aggregations #1', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') }, - group: TSDB.interval(250, false) - }) - ).to.deep.equal([ - { - results: { data: [2, 3, 4] }, - group: { start: now - 250, width: 250 } - }, - { - results: { data: [0, 1] }, - group: { start: now - 500, width: 250 } - } - ]) - }) - - it('runs grouped() aggregations #2', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') }, - group: TSDB.interval(100, false), - where: { time: { is: '>', than: now - 300 } } - }) - ).to.deep.equal([ - { - results: { data: [4] }, - group: { start: now - 100, width: 100 } - }, - { - results: { data: [3] }, - group: { start: now - 200, width: 100 } - }, - { - results: { data: [2] }, - group: { start: now - 300, width: 100 } - } - ]) - }) - - it('runs grouped() aggregations #3', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') }, - group: TSDB.interval(100, false), - where: { time: { is: '>', than: now } } - }) - ).to.deep.equal([]) - }) - - it('respects single where clauses', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') }, - where: { time: { is: '>', than: now - 300 } } - }) - ).to.deep.equal([ - { - results: { - data: [2, 3, 4] - } - } - ]) - }) - - it('respects multiple where clauses', () => { - expect( - tsdb.series('a').query({ - metrics: { data: TSDB.map('my_col1') }, - where: { - time: [ - { is: '>', than: now - 300 }, - { is: '<', than: now } - ] - } - }) - ).to.deep.equal([ - { - results: { - data: [2, 3] - } - } - ]) - }) - - it('drops all data', () => { - tsdb.series('a').remove() - expect( - tsdb.series('a').query({ - metrics: { total: TSDB.count() } - }) - ).to.deep.equal([ - { - results: { - total: 0 - } - } - ]) - }) - - it('drops data matching a clause', () => { - tsdb.series('a').remove({ - time: [ - { is: '>', than: now - 300 }, - { is: '<', than: now } - ] - }) - - expect( - tsdb.series('a').query({ - metrics: { time: TSDB.map('time') } - }) - ).to.deep.equal([ - { - results: { - time: [600, 700, 1000] - } - } - ]) - }) -}) diff --git a/tsconfig.json b/tsconfig.json index 859587b..0efdc79 100644 --- a/tsconfig.json +++ b/tsconfig.json @@ -1,15 +1,20 @@ - { "compilerOptions": { - "module": "commonjs", - "noImplicitAny": true, - "target": "es5", - "lib": [ - "dom", - "es6" - ] + "module": "commonjs", + "target": "es2017", + "lib": ["es2017", "dom"], + "declaration": true, + "noImplicitAny": true, + "noImplicitThis": true, + "sourceMap": true, + "outDir": "./dist", + "strict": true, + "noUnusedLocals": true, + "experimentalDecorators": true, + "alwaysStrict": true, + "resolveJsonModule": true, + "esModuleInterop": true, + "types": ["mocha"] }, - "exclude": [ - "node_modules" - ] -} + "include": ["src"] + } diff --git a/uts.ts b/uts.ts deleted file mode 100644 index 8b22d44..0000000 --- a/uts.ts +++ /dev/null @@ -1,649 +0,0 @@ -/** - * The Bin is used internally in the query system and holds analysis for - * a group. - */ -export class Bin { - - private columns: string[]; - private metrics: { [column: string]: Aggregate } = {}; - private _size: number = 0; - - - /** - * The bin holds data for a group of time series metrics. - * @param {Object} metrics - * @param {Object} group arbitrary object describing the grouping of - * the contained metrics. - */ - constructor(metrics: { [column: string]: () => Aggregate }, private group?: any) { - this.columns = Object.keys(metrics); - this.columns.forEach(col => { - this.metrics[col] = metrics[col](); - }); - } - - /** - * Returns the number of points in this bin. - * @return {Number} - */ - size(): number { - return this._size; - } - - /** - * Adds new data to the bin. - * @param {Point} point - * @return {Bin} - */ - push(point: Point): this { - this._size++; - - for (let i = 0; i < this.columns.length; i++) { - const col = this.columns[i]; - this.metrics[col].push(point); - } - - return this; - } - - /** - * Serializes the bin to a results object. - * @return {Object} - */ - toObject(): BinResult { - const out: BinResult = { results: {} }; - - if (this.group) { - out.group = this.group; - } - - this.columns.forEach(col => { - out.results[col] = this.metrics[col].serialize(); - }); - - return out; - } -} - -/** - * Parent class of groupers. - */ -export abstract class Group { - - protected _where: { [col: string]: Comparator | Comparator[] }; - - /** - * Sets the `where` object this query is being called with. - * @param {Object} where - * @return {Group} - */ - public where(where: any): this { - this._where = where; - return this; - } - - protected getWhere(column: string): Comparator[] { - const clause = this._where[column]; - if (!clause) { - return []; - } - - return (Array.isArray(clause) ? clause : [clause]); - } - - /** - * Returns a list of bins with points added to them. - */ - abstract binify(data: Point[], metrics: { [column: string]: () => Aggregate }): Bin[]; -} - -/** - * The IntervalGrouper groups data based on time. - */ -class IntervalGrouper extends Group { - /** - * @param {Number} interval the size, in milliseconds, of each group bin - * @param {Boolean} fill whether to zero-fill bins that don't have data - */ - constructor(private interval: number, private fill: boolean, private now: number) { - super(); - } - - binify(data: Point[], metrics: { [column: string]: () => Aggregate }): Bin[] { - let start: number; - const timeBound = this.getWhere('time').find(time => time.is === '>'); - if (timeBound) { - start = timeBound.than; - } else { - start = data[0].getTime(); - } - - const { interval, now } = this; - const count = Math.floor((now - start) / interval) + 1; - - let bins = new Array(); - for (let i = 0; i < count; i++) { - bins.push(new Bin(metrics, { - start: now - (i + 1) * interval, - width: interval - })); - } - - for (let i = 0; i < data.length; i++) { - const time = data[i].getTime(); - if (time > now) { - break; - } - - bins[Math.floor((now - time) / interval)].push(data[i]); - } - - if (!this.fill) { - bins = bins.filter((b) => b.size() > 0); - } - - return bins; - } -} - -/** - * The AnyGrouper is the "base" grouper that just shoves all the data into - * a single bin. - */ -class AnyGrouper extends Group { - binify(data: Point[], metrics: { [column: string]: () => Aggregate }): Bin[] { - const bin = new Bin(metrics); - for (let i = 0; i < data.length; i++) { - bin.push(data[i]); - } - - return [bin]; - } -} - -export type PointData = { - [column: string]: any, -}; - -/** - * A Point is the minimal item of data within a Series. It stores one or more - * properties that can be analyzed, as well as the time it was inserted. - */ -export class Point { - - /** - * Creates a new point for insertion into a time series. - * @param {Object} data - * @param {[Number]} time insertion time in milliseconds - */ - constructor(private data: PointData, time = Date.now()) { - this.data["time"] = time; - } - - /** - * Gets a property from the point, returning the default value if - * it doens't exist. - */ - public get(prop: string, defaultValue: any = undefined): any { - return this.has(prop) ? this.data[prop] : defaultValue; - } - - /** - * Returns true if this point contains the provided property. - - */ - public has(prop: string) { - return this.data.hasOwnProperty(prop); - } - - /** - * Returns the time this point was inserted at. - * @return {Number} milliseconds timestamp - */ - public getTime(): number { - return this.data["time"]; - } - - /** - * Clones and converts the point to a plain object. - */ - public toObject(): PointData { - const out: PointData = {}; - Object.keys(this.data).forEach(key => out[key] = this.data[key]); - return out; - } -} - -export type BinaryOperator = ">" | "<" | "="; - -/** - * The Comparator can be passed into the series query to compare values - * to each other. - */ -export interface Comparator { - is: BinaryOperator, - than: any, -} - -/** - * BinResults are returned from time series queries. - */ -export interface BinResult { - group?: any, - results: { [column: string]: any }, -} - -/** - * Series contains a logical grouping of results that can be aggregated. - */ -export class Series { - - private retention = 0; - private interval = 0; - private data = new Array(); - - /** - * Sets how long data will be stored in the provided series. - * @param {Number} ttl duration in milliseconds - * If zero, all data will be kept - */ - public setRetention(ttl: number) { - clearInterval(this.interval); - - if (ttl === 0) { - return; - } - - this.interval = setInterval(() => { - const threshold = Date.now() - ttl; - - let i = 0; - while (this.data[i] && this.data[i].getTime() < threshold) { - i++; - } - - if (i > 0) { - this.data = this.data.slice(i); - } - }, 1000); - } - - /** - * Inserts new data into the series at the specified time, - * defaulting to the current time if not provided. - */ - public insert(data: any, time?: number) { - this.data.push(data instanceof Point ? data : new Point(data, time)); - return this; - } - - /** - * Coverts a comparator `where` from a query into a predicate function. - * @param {Object} cmp - * @return {Function} - */ - private buildComparator(cmp: { [col: string]: Comparator | Comparator[] }): (pt: Point) => boolean { - const fns = Object.keys(cmp).reduce((allFns, col) => { - let comparators = cmp[col]; - if (!Array.isArray(cmp[col])) { - comparators = [ comparators]; - } - - const cmpFns = ( comparators).map(comp => { - const comparator = comp.is; - const value = comp.than; - - return (pt: Point): boolean => { - if (!pt.has(col)) return false; - - switch (comparator) { - case '>': return pt.get(col) > value; - case '<': return pt.get(col) < value; - case '=': return pt.get(col) === value; - default: throw new Error(`Unknown comparator '${comparator}'`); - } - }; - }); - - return [...allFns, ...cmpFns]; - }, []); - - return (pt) => { - for (let i = 0; i < fns.length; i++) { - if (!fns[i](pt)) { - return false; - } - } - - return true; - }; - } - - /** - * deleteBy removes series data that matches the comparison. If no - * comparator is given, then all data is removed. - */ - public remove(query?: { [col: string]: Comparator | Comparator[] }): this { - if (!query) { - this.data = []; - return; - } - - const comparator = this.buildComparator(query); - this.data = this.data.filter(pt => !comparator(pt)); - return this; - } - - /** - * Runs a query against the time series. - * @example - * - * db.series('bandwidth').query({ - * metrics: { - * mean: db.mean('bits'), - * }, - * where: { - * time: { is: '>', than: Date.now() - 5 * 60 * 100 } - * }, - * group: db.interval(30 * 1000, true), - * }); - * - * // returns: - * - * [{ - * group: { start: 1459513952592, end: 1459513982592 }, - * metrics: { - * mean: 3511 - * } - * }, { - * // ... - * }] - */ - public query(options: { - metrics: { [col: string]: () => Aggregate }, - where?: { [col: string]: Comparator | Comparator[] }, - group?: Group, - }): BinResult[] { - options.where = options.where || {}; - options.group = options.group || new AnyGrouper(); - - const data = this.data.filter(this.buildComparator(options.where)); - - return options.group.where(options.where) - .binify(data, options.metrics) - .map((bin) => bin.toObject()); - } - - /** - * Frees resources associated with the time series. Subsequent attempted - * usages of the series will throw an error. - */ - public destroy() { - clearInterval(this.interval); - } -} - -export interface Aggregate { - /** - * Adds a new point to the aggregate. - */ - push(point: Point): void; - - /** - * Returns the aggregate's result for returning in the query results. - */ - serialize(): any; -} - -class Mapper implements Aggregate { - - private data = new Array(); - - /** - * Mapper returns the results of a mapping function on the points. - */ - constructor(private fn: (pt: Point) => any) {} - - public push(pt: Point) { - this.data.push(this.fn(pt)); - } - - public serialize() { - return this.data; - } -} - -class Reducer implements Aggregate { - - private result: T; - - /** - * Mapper returns the results of a mapping function on the points. - */ - constructor(private fn: (current: T, pt: Point) => T, initial: T) { - this.result = initial; - } - - public push(pt: Point) { - this.result = this.fn(this.result, pt); - } - - public serialize() { - return this.result; - } -} - -class Average implements Aggregate { - - private sum = 0; - private count = 0; - - /** - * Average computes the arithmetic mean of the specified column. - */ - constructor(private column: string) {} - - public push(pt: Point) { - if (pt.has(this.column)) { - this.sum += pt.get(this.column); - this.count += 1; - } - } - - public serialize() { - return this.count === 0 ? 0 : this.sum / this.count; - } -} - -class Derivative implements Aggregate { - - private lastChange: number = 0; - private nextValues: number[] = []; - private lastValue: number; - private lastTime: number; - private leadingTime: number; - - private points = new Array(); - - /** - * Derivative plots changes in a column's value. - */ - constructor(private column: string, private interval: number) {} - - public push(pt: Point) { - const value = pt.get(this.column); - const time = pt.getTime(); - if (this.lastTime === undefined) { - this.lastTime = time; - this.lastValue = value; - } - - while (this.lastTime + this.interval < time) { - this.pushPoint(this.lastTime + this.interval); - } - - this.lastChange += value - this.lastValue; - this.lastValue = value; - this.leadingTime = time; - } - - private pushPoint(time: number) { - this.points.push(new Point( - { [this.column]: this.lastChange }, - time - )); - - this.lastChange = 0; - this.lastTime = time; - } - - public serialize() { - if (this.leadingTime !== undefined) { - this.pushPoint(this.leadingTime); - } - - return this.points; - } -} - -/** - * TSDB is a miniature time-series database in plain Js. It functions as follows: - * - The database has many Series, identified by their name as strings. - * - You can push data to each Series. - * - Later, you can query for data in the Series. Data is always passed - * through a grouper when you query if (even if it groups all points - * together) and you can also attach aggregators to it. - * - Each group creates a bunch of "bins", and pushed each data point - * in the query to one or more bins. - * - Each bin stores one or more aggregators, like "mean", which analyze - * data in that bin - * - At the end of the query, the grouper returns the bins it created - * which are then serialized and passed back to the caller. - */ -export class TSDB { - - private _series: { [name: string]: Series } = {}; - private _defaultRetention: number = 0; - - /** - * Sets the default series retention time in milliseconds. - */ - public defaultRetention(ttl: number) { - this._defaultRetention = ttl; - } - - /** - * Returns a new Series, creating one if it did not already exist. - * @param {String} name - * @return {Series} - */ - public series(name: string): Series { - if (!this._series.hasOwnProperty(name)) { - this._series[name] = new Series(); - this._series[name].setRetention(this._defaultRetention); - } - - return this._series[name]; - } - - /** - * Tears down the database. - */ - public destroy() { - Object.keys(this._series).forEach(s => this._series[s].destroy()); - this._series = {}; - } - - /** - * Creates an analysis which runs a custom mapping function on points, - * returning the mapping results. If the `mapper` is a string, it'll - * extract the specified column from the results, lodash style. - */ - public static map(mapper: string | ((pt: Point) => any)): () => Aggregate { - let fn: (pt: Point) => any; - if (typeof mapper === 'function') { - fn = mapper; - } else { - fn = (pt) => pt.get(mapper); - } - - return () => new Mapper(fn); - } - - /** - * Creates an analysis which runs a custom mapping function on points, - * returning the mapping results. If the `mapper` is a string, it'll - * extract the specified column from the results, lodash style. - */ - public static reduce(fn: (current: T, pt: Point) => T, initial: T): () => Aggregate { - return () => new Reducer(fn, initial); - } - - /** - * Creates a mean metric analysis passed into Series.Query - */ - public static mean(column: string): () => Aggregate { - return () => new Average(column); - } - - /** - * Creates a max metric analysis passed into Series.Query - */ - public static max(column: string): () => Aggregate { - return this.reduce((max, pt) => Math.max(pt.get(column), max), 0); - } - - /** - * Creates a min metric analysis passed into Series.Query - */ - public static min(column: string): () => Aggregate { - return this.reduce((min, pt) => Math.min(pt.get(column), min), 0); - } - - /** - * Creates an analysis which returns points that plot changes in a column, - * within a specified interval. - */ - public static derivative(column: string, interval: number): () => Aggregate { - return () => new Derivative(column, interval); - } - - /** - * Creates an analysis that gets the most recent - * value of the specified column. - */ - public static last(column: string): () => Aggregate { - return this.reduce((x, pt) => pt.get(column), null); - } - - /** - * Creates a sum metric analysis passed into Series.Query - */ - public static sum(column: string): () => Aggregate { - return this.reduce((sum, pt) => sum + pt.get(column), 0); - } - - /** - * Creates a count analysis passed into Series.Query. By default, counts - * all columns, or you can pass a column to only count points that have - * that column. - */ - public static count(column: string = '*'): () => Aggregate { - return this.reduce( - (sum, pt) => { - if (column === '*' || pt.get(column) !== undefined) { - return sum + 1; - } - return sum; - }, - 0, - ); - } - - /** - * Creates a new grouper based on time intervals. - */ - public static interval(interval: number, fill: boolean = true, now: number = Date.now()): Group { - return new IntervalGrouper(interval, fill, now); - } -}