ピボットエンジン:パフォーマンス

PivotEngineは非常に大きなデータセットを要約することができます。データがクライアント側から連結されている場合、要約データは非常に高速に生成できます。要約データは非同期に生成され、ユーザーとの対話を改善します。

以下のサンプルは、さまざまなサイズのデータセット(最大100万個)を読み込むのにかかる時間を示すことによってパフォーマンスを示しています。

何百万ものレコードを含む大量のデータセットを扱う場合は、SSASキューブやComponentOne Data Servicesなどのサーバー側OLAPプロバイダーの使用を検討する必要があります。PivotEngineはどちらにも接続できます。

import 'bootstrap.css'; import '@grapecity/wijmo.styles/wijmo.css'; import './styles.css'; import '@grapecity/wijmo.touch'; // support drag/drop on touch devices 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 = [], result = document.getElementById('result'), start = 0; // // initialize pivot engine var ng = new wjOlap.PivotEngine({ autoGenerateFields: false, fields: [ { binding: 'date', header: '日付', format: 'yyyy' }, { binding: 'buyer', header: '担当者' }, { binding: 'type', header: '分類' }, { binding: 'amount', header: '金額', format: 'c0', aggregate: 'Sum' } ], itemsSource: ds10, showRowTotals: 'Subtotals', valueFields: ['金額'], rowFields: ['担当者', '分類'], // // benchmark updatingView: function () { if (start == 0) { start = Date.now(); } }, updatedView: function (s) { var fmt = '<b>{cnt:n0}</b>個の項目を<b>{tm:n0}</b>msで処理しました。'; 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; } }); // // create large data asynchronously createDataAsync(100e3, function (result) { ds100 = result; enableButton('100k'); }); createDataAsync(500e3, function (result) { ds500 = result; enableButton('500k'); }); 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 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'); </script> </head> <body> <div class="container-fluid"> <div id="buttons"> <button id="10k" class="btn btn-primary"> 1万個の項目 </button> <button id="100k" class="btn btn-primary" disabled> 10万個の項目 </button> <button id="500k" class="btn btn-primary" disabled> 50万個の項目 </button> </div> <p id="result"> </p> <div class="output"> <div id="pivotGrid"></div> </div> </div> </body> </html>
import { DateTime } from '@grapecity/wijmo'; function randomItem(arr) { return arr[Math.floor(Math.random() * arr.length)]; } export function addData(data, cnt) { var today = new Date(), buyers = '成宮 真紀,山本 雅治,加藤 泰江,川村 匡'.split(','), types = '音楽,ビデオ,本,家電,パソコン,食品'.split(','); for (var i = 0; i < cnt; i++) { data.push({ date: DateTime.addYears(today, -Math.random() * 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; }
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