mirror of
https://github.com/apache/superset.git
synced 2026-07-27 17:12:36 +00:00
101 lines
2.8 KiB
TypeScript
101 lines
2.8 KiB
TypeScript
/**
|
|
* Licensed to the Apache Software Foundation (ASF) under one
|
|
* or more contributor license agreements. See the NOTICE file
|
|
* distributed with this work for additional information
|
|
* regarding copyright ownership. The ASF licenses this file
|
|
* to you under the Apache License, Version 2.0 (the
|
|
* "License"); you may not use this file except in compliance
|
|
* with the License. You may obtain a copy of the License at
|
|
*
|
|
* http://www.apache.org/licenses/LICENSE-2.0
|
|
*
|
|
* Unless required by applicable law or agreed to in writing,
|
|
* software distributed under the License is distributed on an
|
|
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
|
* KIND, either express or implied. See the License for the
|
|
* specific language governing permissions and limitations
|
|
* under the License.
|
|
*/
|
|
import transformData from '../src/transformData';
|
|
|
|
const t1 = 1704067200000;
|
|
const t2 = 1704153600000;
|
|
|
|
test('builds one series per group, dropping the single metric from the key', () => {
|
|
const data = transformData(
|
|
[
|
|
{ __timestamp: t1, gender: 'boy', sum__num: 10 },
|
|
{ __timestamp: t2, gender: 'boy', sum__num: 20 },
|
|
{ __timestamp: t1, gender: 'girl', sum__num: 30 },
|
|
],
|
|
['gender'],
|
|
['sum__num'],
|
|
);
|
|
expect(data).toEqual([
|
|
{
|
|
key: ['boy'],
|
|
values: [
|
|
{ x: t1, y: 10 },
|
|
{ x: t2, y: 20 },
|
|
],
|
|
},
|
|
{
|
|
key: ['girl'],
|
|
values: [
|
|
{ x: t1, y: 30 },
|
|
{ x: t2, y: null },
|
|
],
|
|
},
|
|
]);
|
|
});
|
|
|
|
test('keys ungrouped series by the metric name', () => {
|
|
const data = transformData(
|
|
[
|
|
{ __timestamp: t1, sum__num: 1, count: 2 },
|
|
{ __timestamp: t2, sum__num: 3, count: 4 },
|
|
],
|
|
[],
|
|
['sum__num', 'count'],
|
|
);
|
|
expect(data.map(series => series.key)).toEqual(['count', 'sum__num']);
|
|
});
|
|
|
|
test('keeps the metric in multi-metric grouped keys', () => {
|
|
const data = transformData(
|
|
[{ __timestamp: t1, gender: 'boy', sum__num: 1, count: 2 }],
|
|
['gender'],
|
|
['sum__num', 'count'],
|
|
);
|
|
expect(data.map(series => series.key)).toEqual([
|
|
['count', 'boy'],
|
|
['sum__num', 'boy'],
|
|
]);
|
|
});
|
|
|
|
test('normalizes rows when contribution is on', () => {
|
|
const data = transformData(
|
|
[
|
|
{ __timestamp: t1, gender: 'boy', sum__num: 30 },
|
|
{ __timestamp: t1, gender: 'girl', sum__num: 10 },
|
|
],
|
|
['gender'],
|
|
['sum__num'],
|
|
true,
|
|
);
|
|
expect(data[0].values[0].y).toBeCloseTo(0.75);
|
|
expect(data[1].values[0].y).toBeCloseTo(0.25);
|
|
});
|
|
|
|
test('drops series whose values are all null', () => {
|
|
const data = transformData(
|
|
[
|
|
{ __timestamp: t1, gender: 'boy', sum__num: 5 },
|
|
{ __timestamp: t1, gender: 'girl', sum__num: null },
|
|
],
|
|
['gender'],
|
|
['sum__num'],
|
|
);
|
|
expect(data.map(series => series.key)).toEqual([['boy']]);
|
|
});
|