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113 lines
3.1 KiB
TypeScript
113 lines
3.1 KiB
TypeScript
/**
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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import transformData from '../src/transformData';
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const t1 = 1704067200000;
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const t2 = 1704153600000;
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test('nests records per metric and group with null padding', () => {
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const data = transformData(
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[
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{ __timestamp: t1, gender: 'boy', sum__num: 10 },
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{ __timestamp: t2, gender: 'boy', sum__num: 20 },
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{ __timestamp: t1, gender: 'girl', sum__num: 30 },
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// girl is missing at t2 -> padded with null
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],
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['gender'],
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['sum__num'],
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);
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expect(Object.keys(data)).toEqual(['sum__num']);
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expect(data.sum__num).toEqual([
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{
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group: ['boy'],
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values: [
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{ x: t1, y: 10 },
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{ x: t2, y: 20 },
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],
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},
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{
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group: ['girl'],
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values: [
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{ x: t1, y: 30 },
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{ x: t2, y: null },
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],
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},
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]);
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});
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test('uses the All group when no groupby is set', () => {
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const data = transformData(
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[
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{ __timestamp: t1, sum__num: 1 },
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{ __timestamp: t2, sum__num: 2 },
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],
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[],
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['sum__num'],
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);
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expect(data.sum__num).toEqual([
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{
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group: 'All',
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values: [
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{ x: t1, y: 1 },
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{ x: t2, y: 2 },
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],
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},
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]);
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});
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test('handles multiple metrics and multi-column groups', () => {
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const data = transformData(
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[
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{ __timestamp: t1, gender: 'boy', state: 'CA', sum__num: 1, count: 5 },
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{ __timestamp: t1, gender: 'girl', state: 'NY', sum__num: 2, count: 6 },
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],
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['gender', 'state'],
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['sum__num', 'count'],
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);
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expect(Object.keys(data).sort()).toEqual(['count', 'sum__num']);
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expect(data.count).toEqual([
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{ group: ['boy', 'CA'], values: [{ x: t1, y: 5 }] },
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{ group: ['girl', 'NY'], values: [{ x: t1, y: 6 }] },
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]);
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});
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test('sorts numeric groups numerically like pandas pivot columns', () => {
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const data = transformData(
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[
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{ __timestamp: t1, decade: 10, sum__num: 1 },
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{ __timestamp: t1, decade: 2, sum__num: 2 },
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],
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['decade'],
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['sum__num'],
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);
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expect(data.sum__num.map(series => series.group)).toEqual([[2], [10]]);
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});
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test('sorts timestamps ascending like the pandas pivot index', () => {
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const data = transformData(
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[
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{ __timestamp: t2, sum__num: 2 },
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{ __timestamp: t1, sum__num: 1 },
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],
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[],
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['sum__num'],
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);
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expect(data.sum__num[0].values.map(v => v.x)).toEqual([t1, t2]);
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});
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