PivotEngine性能

PivotEngine 很快。 当与客户端数据一起使用时,它可以在几分之一秒内汇总具有数十万条记录的数据集(特别是在使用现代浏览器时)。

请注意,即使在慢速浏览器和大型数据集上,PivotEngine 也会异步生成摘要,因此永远不会阻止UI线程。

在大多数客户端方案中,数据集大小受下载或生成原始数据所需时间的限制,而不是总结它所需的时间。 (此示例异步生成数据,以避免在生成包含500l或100万个项目的数组时阻止应用程序。)

import 'bootstrap.css'; import '@grapecity/wijmo.styles/wijmo.css'; import './styles.css'; import * as wjOlap from '@grapecity/wijmo.olap'; import * as wjCore from '@grapecity/wijmo'; import { addData } from './data'; // document.readyState === 'complete' ? init() : window.onload = init; // function init() { // // initialize data sets var ds10 = addData([], 10e3), ds100 = [], ds500 = [], ds1M = [], result = document.getElementById('result'), start = 0; // // initialize pivot engine var ng = new wjOlap.PivotEngine({ autoGenerateFields: false, fields: [ { binding: 'date', header: 'Date', format: 'yyyy' }, { binding: 'buyer', header: 'Person' }, { binding: 'type', header: 'Category' }, { binding: 'amount', header: 'Amount', format: 'c0', aggregate: 'Sum' } ], itemsSource: ds10, showRowTotals: 'Subtotals', valueFields: ['Amount'], rowFields: ['Person', 'Category'], // // benchmark updatingView: function () { if (start == 0) { start = Date.now(); } }, updatedView: function (s) { var fmt = 'Summarized <b>{cnt:n0}</b> items in <b>{tm:n0}</b>ms'; result.innerHTML = wjCore.format(fmt, { cnt: s.itemsSource.length, tm: Date.now() - start }); start = 0; } }); // // show summary var pivotGrid = new wjOlap.PivotGrid('#pivotGrid', { itemsSource: ng }); // // handle click events to apply different data sources document.getElementById('buttons').addEventListener('click', function (e) { switch (e.target.id) { case '10k': ng.itemsSource = ds10; break; case '100k': ng.itemsSource = ds100; break; case '500k': ng.itemsSource = ds500; break; case '1M': ng.itemsSource = ds1M; break; } }); // // create large data asynchronously createDataAsync(100e3, function (result) { ds100 = result; enableButton('100k'); }); createDataAsync(500e3, function (result) { ds500 = result; enableButton('500k'); }); createDataAsync(1e6, function (result) { ds1M = result; enableButton('1M'); }); function enableButton(id) { document.getElementById(id).disabled = false; } // // // create data asynchronously function createDataAsync(cnt, callback) { var data = []; addDataAsync(data, cnt, function () { callback(data); }); } function addDataAsync(data, cnt, callback) { setTimeout(function () { addData(data, Math.min(cnt - data.length, 1000)); if (data.length == cnt) { callback(data); } else { addDataAsync(data, cnt, callback); } }); } } <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title>Grapecity Wijmo OLAP Pivot Engine</title> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <!-- SystemJS --> <script src="node_modules/systemjs/dist/system.src.js"></script> <script src="systemjs.config.js"></script> <script> System.import('./src/app'); </script> </head> <body> <div class="container-fluid"> <div id="buttons"> <button id="10k" class="btn btn-primary"> 10k items </button> <button id="100k" class="btn btn-primary" disabled> 100k items </button> <button id="500k" class="btn btn-primary" disabled> 500k items </button> <button id="1M" class="btn btn-primary" disabled> One Million items </button> </div> <p id="result"> </p> <div class="output"> <div id="pivotGrid"></div> </div> <p> If you deal with massive data sets, with millions of records, you should consider using server-side OLAP providers like SSAS cubes or ComponentOne Data Services. The <b>PivotEngine</b> can connect to either. </p> </div> </body> </html> function randomItem(arr) { return arr[Math.floor(Math.random() * arr.length)]; } export function addData(data, cnt) { var today = Date.now(), buyers = 'Mom,Dad,Kelly,Sheldon'.split(','), types = 'Food,Clothes,Fuel,Books,Sports,Music'.split(','); for (var i = 0; i < cnt; i++) { data.push({ date: today - Math.random() * 365 * 3, buyer: randomItem(buyers), type: randomItem(types), amount: 20 + Math.random() * 1000 }); } return data; } #buttons { display: flex; margin-bottom: 6px; } #buttons .btn { margin: 6px; white-space: normal; } .output { display: flex; justify-content: center; margin: 6px; } .wj-pivotgrid { width: auto; max-height: 300px; } body { margin-bottom: 36pt; } import 'bootstrap.css'; import '@grapecity/wijmo.styles/wijmo.css'; import './styles.css'; import * as wjCore from '@grapecity/wijmo'; import * as wjOlap from '@grapecity/wijmo.olap'; // import { Component, Inject, enableProdMode, NgModule, AfterViewInit } from '@angular/core'; import { platformBrowserDynamic } from '@angular/platform-browser-dynamic'; import { BrowserModule } from '@angular/platform-browser'; import { WjOlapModule } from '@grapecity/wijmo.angular2.olap'; import { DataService, DataItem } from './app.data'; // @Component({ selector: 'app-component', templateUrl: 'src/app.component.html' }) export class AppComponent implements AfterViewInit { ng: wjOlap.PivotEngine; ds10: DataItem[]; ds100: DataItem[]; ds500: DataItem[]; ds1M: DataItem[]; start: number = 0; enable100K: boolean = true; enable500K: boolean = true; enable1M: boolean = true; result: string; // constructor(@Inject(DataService) private dataService: DataService) { var self = this; self.ds10 = dataService.addData([], 10e3); self.ng = new wjOlap.PivotEngine({ autoGenerateFields: false, fields: [ // specify the fields we want { binding: 'date', header: 'Date', format: 'yyyy' }, { binding: 'buyer', header: 'Person' }, { binding: 'type', header: 'Category' }, { binding: 'amount', header: 'Amount', format: 'c0', aggregate: 'Sum' } ], itemsSource: self.ds10, showRowTotals: 'Subtotals', valueFields: ['Amount'], rowFields: ['Person', 'Category'], updatingView: function () { if (self.start == 0) { self.start = Date.now(); } }, updatedView: function (s: wjOlap.PivotEngine) { var fmt = 'Summarized <b>{cnt:n0}</b> items in <b>{tm:n0}</b>ms'; self.result = wjCore.format(fmt, { cnt: s.itemsSource.length, tm: Date.now() - self.start }); self.start = 0; } }); } // ngAfterViewInit() { var self = this; self._createDataAsync(100e3, function (result: DataItem[]) { self.ds100 = result; self.enable100K = false; }); self._createDataAsync(500e3, function (result: DataItem[]) { self.ds500 = result; self.enable500K = false; }); self._createDataAsync(1e6, function (result: DataItem[]) { self.ds1M = result; self.enable1M = false; }); } // onButtonClick(e: MouseEvent) { switch ((e.target as HTMLElement).id) { case '10k': this.ng.itemsSource = this.ds10; break; case '100k': this.ng.itemsSource = this.ds100; break; case '500k': this.ng.itemsSource = this.ds500; break; case '1M': this.ng.itemsSource = this.ds1M; break; } } // _createDataAsync(cnt: number, callback: (result: DataItem[]) => void) { var data: DataItem[] = []; this._addDataAsync(data, cnt, function () { callback(data); }); } _addDataAsync(data: DataItem[], cnt: number, callback: (result: DataItem[]) => void) { var self = this; setTimeout(function () { self.dataService.addData(data, Math.min(cnt - data.length, 1000)); if (data.length == cnt) { callback(data); } else { self._addDataAsync(data, cnt, callback); } }); } _enableButton(id: string) { (document.getElementById(id) as HTMLButtonElement).disabled = false; } } // @NgModule({ imports: [WjOlapModule, BrowserModule], declarations: [AppComponent], providers: [DataService], bootstrap: [AppComponent] }) export class AppModule { } // enableProdMode(); // Bootstrap application with hash style navigation and global services. platformBrowserDynamic().bootstrapModule(AppModule); <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title>Grapecity Wijmo OLAP Pivot Engine Performance</title> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <!-- Polyfills --> <script src="node_modules/core-js/client/shim.min.js"></script> <script src="node_modules/zone.js/dist/zone.min.js"></script> <!-- SystemJS --> <script src="node_modules/systemjs/dist/system.js"></script> <script src="systemjs.config.js"></script> <script> // workaround to load 'rxjs/operators' from the rxjs bundle System.import('rxjs').then(function (m) { System.set(SystemJS.resolveSync('rxjs/operators'), System.newModule(m.operators)); System.import('./src/app.component'); }); </script> </head> <body> <app-component></app-component> </body> </html> <div class="container-fluid"> <div id="buttons" (click)="onButtonClick($event)"> <button id="10k" class="btn btn-primary"> 10k items </button> <button id="100k" class="btn btn-primary" [disabled]="enable100K"> 100k items </button> <button id="500k" class="btn btn-primary" [disabled]="enable500K"> 500k items </button> <button id="1M" class="btn btn-primary" [disabled]="enable1M"> One Million items </button> </div> <p id="result" [innerHtml]="result"> </p> <div class="output"> <wj-pivot-grid [itemsSource]="ng"></wj-pivot-grid> </div> <p> If you deal with massive data sets, with millions of records, you should consider using server-side OLAP providers like SSAS cubes or ComponentOne Data Services. The <b>PivotEngine</b> can connect to either. </p> </div> import { Injectable } from '@angular/core'; export interface DataItem { date: number; buyer: string; type: string; amount: number; } function randomItem(arr: string[]): string { return arr[Math.floor(Math.random() * arr.length)]; } @Injectable() export class DataService { addData(data: DataItem[], cnt: number): DataItem[] { var today = Date.now(), buyers = 'Mom,Dad,Kelly,Sheldon'.split(','), types = 'Food,Clothes,Fuel,Books,Sports,Music'.split(','); for (var i = 0; i < cnt; i++) { data.push({ date: today - Math.random() * 365 * 3, buyer: randomItem(buyers), type: randomItem(types), amount: 20 + Math.random() * 1000 }); } return data; } } #buttons { display: flex; margin-bottom: 6px; } #buttons .btn { margin: 6px; white-space: normal; } .output { display: flex; justify-content: center; margin: 6px; } .wj-pivotgrid { width: auto; max-height: 300px; } body { margin-bottom: 36pt; } <template> <div class="container-fluid"> <div id="buttons" v-on:click="onButtonClick"> <button id="10k" class="btn btn-primary"> 10k items </button> <button id="100k" class="btn btn-primary" :disabled="enable100K"> 100k items </button> <button id="500k" class="btn btn-primary" :disabled="enable500K"> 500k items </button> <button id="1M" class="btn btn-primary" :disabled="enable1M"> One Million items </button> </div> <p id="result" v-html="result"> </p> <div class="output"> <wj-pivot-grid id="pivotGrid" :items-source="ng"></wj-pivot-grid> </div> <p> If you deal with massive data sets, with millions of records, you should consider using server-side OLAP providers like SSAS cubes or ComponentOne Data Services. The <b>PivotEngine</b> can connect to either. </p> </div> </template> <script> import '@grapecity/wijmo.styles/wijmo.css'; import 'bootstrap.css'; import Vue from 'vue'; import '@grapecity/wijmo.vue2.olap'; import * as wjcCore from '@grapecity/wijmo'; import * as wjcOlap from '@grapecity/wijmo.olap'; import { addData } from './data'; let App = Vue.extend({ name: "app", data: function() { return { ds10: addData([], 10e3), ds100: null, ds500: null, ds1M: null, start: 0, enable100K: true, enable500K: true, enable1M: true, result: '', ng: new wjcOlap.PivotEngine({ autoGenerateFields: false, fields: [ // specify the fields we want { binding: 'date', header: 'Date', format: 'yyyy' }, { binding: 'buyer', header: 'Person' }, { binding: 'type', header: 'Category' }, { binding: 'amount', header: 'Amount', format: 'c0', aggregate: 'Sum' } ], itemsSource: addData([], 10e3), showRowTotals: 'Subtotals', valueFields: ['Amount'], rowFields: ['Person', 'Category'], updatingView: () => { if (this.start == 0) { this.start = Date.now(); } }, updatedView: (s) => { let fmt = 'Summarized <b>{cnt:n0}</b> items in <b>{tm:n0}</b>ms'; this.result = wjcCore.format(fmt, { cnt: s.itemsSource.length, tm: Date.now() - this.start }); this.start = 0; } }) }; }, mounted: function() { this._createDataAsync(100e3, (result) => { this.ds100 = result; this.enable100K = false; }); this._createDataAsync(500e3, (result) => { this.ds500 = result; this.enable500K = false; }); /*this._createDataAsync(1e6, (result) => { this.ds1M = result; this.enable1M = false; });*/ }, methods: { onButtonClick(e) { switch (e.target.id) { case '10k': this.ng.itemsSource = this.ds10; break; case '100k': this.ng.itemsSource = this.ds100; break; case '500k': this.ng.itemsSource = this.ds500; break; case '1M': this.ng.itemsSource = this.ds1M; break; } }, _createDataAsync(cnt, callback) { let data = []; this._addDataAsync(data, cnt, () => { callback(data); }); }, _addDataAsync (data, cnt, callback) { setTimeout(() => { addData(data, Math.min(cnt - data.length, 1000)); if (data.length == cnt) { callback(data); } else { this._addDataAsync(data, cnt, callback); } }); } } }); new Vue({ render: h => h(App) }).$mount("#app"); </script> <style> #buttons { display: flex; margin-bottom: 6px; } #buttons .btn { margin: 6px; white-space: normal; } .output { display: flex; justify-content: center; margin: 6px; } #pivotGrid { width: auto; max-height: 300px; } body { margin-bottom: 36pt; } </style> <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title>Grapecity Wijmo OLAP Pivot Engine Performance</title> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <!-- SystemJS --> <script src="node_modules/systemjs/dist/system.src.js"></script> <script src="systemjs.config.js"></script> <script> System.import('./src/app.vue'); </script> </head> <body> <div id="app"> </div> </body> </html> export function addData(data, cnt) { var today = Date.now(), buyers = 'Mom,Dad,Kelly,Sheldon'.split(','), types = 'Food,Clothes,Fuel,Books,Sports,Music'.split(','); for (var i = 0; i < cnt; i++) { data.push({ date: today - Math.random() * 365 * 3, buyer: randomItem(buyers), type: randomItem(types), amount: 20 + Math.random() * 1000 }); } return data; } function randomItem(arr) { return arr[Math.floor(Math.random() * arr.length)]; } import './app.css'; import 'bootstrap.css'; import '@grapecity/wijmo.styles/wijmo.css'; // import * as React from 'react'; import * as ReactDOM from 'react-dom'; // import * as Olap from '@grapecity/wijmo.react.olap'; import * as wjcCore from '@grapecity/wijmo'; import * as wjcOlap from '@grapecity/wijmo.olap'; import { addData } from './data'; class App extends React.Component { constructor(props) { super(props); this._start = 0; this.state = { ds10: addData([], 10e3), ds100: null, ds500: null, ds1M: null, enable100K: true, enable500K: true, enable1M: true, ng: new wjcOlap.PivotEngine({ autoGenerateFields: false, fields: [ { binding: 'date', header: 'Date', format: 'yyyy' }, { binding: 'buyer', header: 'Person' }, { binding: 'type', header: 'Category' }, { binding: 'amount', header: 'Amount', format: 'c0', aggregate: 'Sum' } ], itemsSource: addData([], 10e3), showRowTotals: 'Subtotals', valueFields: ['Amount'], rowFields: ['Person', 'Category'], updatingView: () => { if (this._start == 0) { this._start = Date.now(); } }, updatedView: (s) => { let fmt = 'Summarized <b>{cnt:n0}</b> items in <b>{tm:n0}</b>ms'; let tm = Date.now() - this._start; let result = wjcCore.format(fmt, { cnt: s.itemsSource.length, tm }); this._result.innerHTML = result; this._start = 0; } }) }; } onButtonClick(e) { switch (e.target.id) { case '10k': this.state.ng.itemsSource = this.state.ds10; break; case '100k': this.state.ng.itemsSource = this.state.ds100; break; case '500k': this.state.ng.itemsSource = this.state.ds500; break; case '1M': this.state.ng.itemsSource = this.state.ds1M; break; } this.setState({ ng: this.state.ng }); } _createDataAsync(cnt, callback) { let data = []; this._addDataAsync(data, cnt, () => { callback(data); }); } _addDataAsync(data, cnt, callback) { setTimeout(() => { addData(data, Math.min(cnt - data.length, 1000)); if (data.length == cnt) { callback(data); } else { this._addDataAsync(data, cnt, callback); } }); } componentDidMount() { this._createDataAsync(100e3, (result) => { this.setState({ ds100: result, enable100K: false }); }); this._createDataAsync(500e3, (result) => { this.setState({ ds500: result, enable500K: false }); }); /*this._createDataAsync(1e6, (result) => { this.setState({ ds1M: result, enable1M: false }); });*/ } render() { return (<div className="container-fluid"> <div id="buttons" onClick={this.onButtonClick.bind(this)}> <button id="10k" className="btn btn-primary"> 10k items </button> <button id="100k" className="btn btn-primary" disabled={this.state.enable100K}> 100k items </button> <button id="500k" className="btn btn-primary" disabled={this.state.enable500K}> 500k items </button> <button id="1M" className="btn btn-primary" disabled={this.state.enable1M}> One Million items </button> </div> <p ref={el => this._result = el} id="result"> </p> <div className="output"> <Olap.PivotGrid id="pivotGrid" itemsSource={this.state.ng}></Olap.PivotGrid> </div> <p> If you deal with massive data sets, with millions of records, you should consider using server-side OLAP providers like SSAS cubes or ComponentOne Data Services. The <b>PivotEngine</b> can connect to either. </p> </div>); } } ReactDOM.render(<App />, document.getElementById('app')); <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title>AutoComplete</title> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <!-- SystemJS --> <script src="node_modules/systemjs/dist/system.src.js"></script> <script src="systemjs.config.js"></script> <script> System.import('./src/app'); </script> </head> <body> <div id="app"></div> </body> </html> #buttons { display: flex; margin-bottom: 6px; } #buttons .btn { margin: 6px; white-space: normal; } .output { display: flex; justify-content: center; margin: 6px; } #pivotGrid { width: auto; max-height: 300px; } body { margin-bottom: 36pt; } export function addData(data, cnt) { var today = Date.now(), buyers = 'Mom,Dad,Kelly,Sheldon'.split(','), types = 'Food,Clothes,Fuel,Books,Sports,Music'.split(','); for (var i = 0; i < cnt; i++) { data.push({ date: today - Math.random() * 365 * 3, buyer: randomItem(buyers), type: randomItem(types), amount: 20 + Math.random() * 1000 }); } return data; } function randomItem(arr) { return arr[Math.floor(Math.random() * arr.length)]; }