Transformers: adds labels as columns transformer (#23703)

* Transformers: adds labels as columns transformer

* Refactor: adds support for same timestamps with different labels

* Refactor: adds basic transform ui

* Refactor: adds sorted result

* Refactor: renames transformer
This commit is contained in:
Hugo Häggmark 2020-04-22 12:21:34 +02:00 committed by GitHub
parent 0a8ce714cb
commit bcf5d4b25c
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6 changed files with 391 additions and 0 deletions

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@ -9,6 +9,7 @@ import { orderFieldsTransformer } from './transformers/order';
import { organizeFieldsTransformer } from './transformers/organize';
import { seriesToColumnsTransformer } from './transformers/seriesToColumns';
import { renameFieldsTransformer } from './transformers/rename';
import { labelsToFieldsTransformer } from './transformers/labelsToFields';
export const standardTransformers = {
noopTransformer,
@ -23,4 +24,5 @@ export const standardTransformers = {
calculateFieldTransformer,
seriesToColumnsTransformer,
renameFieldsTransformer,
labelsToFieldsTransformer,
};

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@ -9,6 +9,7 @@ export enum DataTransformerID {
calculateField = 'calculateField', // Run a reducer on the row
seriesToColumns = 'seriesToColumns', // former table transform timeseries_to_columns
labelsToFields = 'labelsToFields', // former table transform table
filterFields = 'filterFields', // Pick some fields (keep all frames)
filterFieldsByName = 'filterFieldsByName', // Pick fields with name matching regex (keep all frames)
filterFrames = 'filterFrames', // Pick some frames (keep all fields)

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@ -0,0 +1,232 @@
import { mockTransformationsRegistry } from '../../utils/tests/mockTransformationsRegistry';
import { LabelsToFieldsOptions, labelsToFieldsTransformer } from './labelsToFields';
import { DataTransformerConfig, Field, FieldType } from '../../types';
import { DataTransformerID } from './ids';
import { toDataFrame } from '../../dataframe';
import { transformDataFrame } from '../transformDataFrame';
import { ArrayVector } from '../../vector';
describe('Labels as Columns', () => {
beforeAll(() => {
mockTransformationsRegistry([labelsToFieldsTransformer]);
});
it('data frame with 1 value and 1 label', () => {
const cfg: DataTransformerConfig<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
options: {},
};
const oneValueOneLabelA = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [1000] },
{ name: 'temp', type: FieldType.number, values: [1], labels: { location: 'inside' } },
],
});
const oneValueOneLabelB = toDataFrame({
name: 'B',
fields: [
{ name: 'time', type: FieldType.time, values: [2000] },
{ name: 'temp', type: FieldType.number, values: [-1], labels: { location: 'outside' } },
],
});
const result = transformDataFrame([cfg], [oneValueOneLabelA, oneValueOneLabelB]);
const expected: Field[] = [
{ name: 'time', type: FieldType.time, values: new ArrayVector([1000, 2000]), config: {} },
{ name: 'location', type: FieldType.string, values: new ArrayVector(['inside', 'outside']), config: {} },
{ name: 'temp', type: FieldType.number, values: new ArrayVector([1, -1]), config: {} },
];
expect(result[0].fields).toEqual(expected);
});
it('data frame with 2 values and 1 label', () => {
const cfg: DataTransformerConfig<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
options: {},
};
const twoValuesOneLabelA = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [1000] },
{ name: 'temp', type: FieldType.number, values: [1], labels: { location: 'inside' } },
{ name: 'humidity', type: FieldType.number, values: [10000], labels: { location: 'inside' } },
],
});
const twoValuesOneLabelB = toDataFrame({
name: 'B',
fields: [
{ name: 'time', type: FieldType.time, values: [2000] },
{ name: 'temp', type: FieldType.number, values: [-1], labels: { location: 'outside' } },
{ name: 'humidity', type: FieldType.number, values: [11000], labels: { location: 'outside' } },
],
});
const result = transformDataFrame([cfg], [twoValuesOneLabelA, twoValuesOneLabelB]);
const expected: Field[] = [
{ name: 'time', type: FieldType.time, values: new ArrayVector([1000, 2000]), config: {} },
{ name: 'location', type: FieldType.string, values: new ArrayVector(['inside', 'outside']), config: {} },
{ name: 'temp', type: FieldType.number, values: new ArrayVector([1, -1]), config: {} },
{ name: 'humidity', type: FieldType.number, values: new ArrayVector([10000, 11000]), config: {} },
];
expect(result[0].fields).toEqual(expected);
});
it('data frame with 1 value and 2 labels', () => {
const cfg: DataTransformerConfig<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
options: {},
};
const oneValueTwoLabelsA = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [1000] },
{ name: 'temp', type: FieldType.number, values: [1], labels: { location: 'inside', area: 'living room' } },
],
});
const oneValueTwoLabelsB = toDataFrame({
name: 'B',
fields: [
{ name: 'time', type: FieldType.time, values: [2000] },
{ name: 'temp', type: FieldType.number, values: [-1], labels: { location: 'outside', area: 'backyard' } },
],
});
const result = transformDataFrame([cfg], [oneValueTwoLabelsA, oneValueTwoLabelsB]);
const expected: Field[] = [
{ name: 'time', type: FieldType.time, values: new ArrayVector([1000, 2000]), config: {} },
{ name: 'location', type: FieldType.string, values: new ArrayVector(['inside', 'outside']), config: {} },
{ name: 'area', type: FieldType.string, values: new ArrayVector(['living room', 'backyard']), config: {} },
{ name: 'temp', type: FieldType.number, values: new ArrayVector([1, -1]), config: {} },
];
expect(result[0].fields).toEqual(expected);
});
it('data frame with 2 values and 2 labels', () => {
const cfg: DataTransformerConfig<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
options: {},
};
const twoValuesTwoLabelsA = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [1000] },
{ name: 'temp', type: FieldType.number, values: [1], labels: { location: 'inside', area: 'living room' } },
{
name: 'humidity',
type: FieldType.number,
values: [10000],
labels: { location: 'inside', area: 'living room' },
},
],
});
const twoValuesTwoLabelsB = toDataFrame({
name: 'B',
fields: [
{ name: 'time', type: FieldType.time, values: [2000] },
{ name: 'temp', type: FieldType.number, values: [-1], labels: { location: 'outside', area: 'backyard' } },
{
name: 'humidity',
type: FieldType.number,
values: [11000],
labels: { location: 'outside', area: 'backyard' },
},
],
});
const result = transformDataFrame([cfg], [twoValuesTwoLabelsA, twoValuesTwoLabelsB]);
const expected: Field[] = [
{ name: 'time', type: FieldType.time, values: new ArrayVector([1000, 2000]), config: {} },
{ name: 'location', type: FieldType.string, values: new ArrayVector(['inside', 'outside']), config: {} },
{ name: 'area', type: FieldType.string, values: new ArrayVector(['living room', 'backyard']), config: {} },
{ name: 'temp', type: FieldType.number, values: new ArrayVector([1, -1]), config: {} },
{ name: 'humidity', type: FieldType.number, values: new ArrayVector([10000, 11000]), config: {} },
];
expect(result[0].fields).toEqual(expected);
});
it('data frames with different labels', () => {
const cfg: DataTransformerConfig<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
options: {},
};
const oneValueDifferentLabelsA = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [1000] },
{ name: 'temp', type: FieldType.number, values: [1], labels: { location: 'inside', feelsLike: 'ok' } },
],
});
const oneValueDifferentLabelsB = toDataFrame({
name: 'B',
fields: [
{ name: 'time', type: FieldType.time, values: [2000] },
{ name: 'temp', type: FieldType.number, values: [-1], labels: { location: 'outside', sky: 'cloudy' } },
],
});
const result = transformDataFrame([cfg], [oneValueDifferentLabelsA, oneValueDifferentLabelsB]);
const expected: Field[] = [
{ name: 'time', type: FieldType.time, values: new ArrayVector([1000, 2000]), config: {} },
{ name: 'location', type: FieldType.string, values: new ArrayVector(['inside', 'outside']), config: {} },
{ name: 'feelsLike', type: FieldType.string, values: new ArrayVector(['ok', null]), config: {} },
{ name: 'sky', type: FieldType.string, values: new ArrayVector([null, 'cloudy']), config: {} },
{ name: 'temp', type: FieldType.number, values: new ArrayVector([1, -1]), config: {} },
];
expect(result[0].fields).toEqual(expected);
});
it('data frames with same timestamp and different labels', () => {
const cfg: DataTransformerConfig<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
options: {},
};
const oneValueDifferentLabelsA = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [1000, 2000] },
{ name: 'temp', type: FieldType.number, values: [1, 2], labels: { location: 'inside', feelsLike: 'ok' } },
],
});
const oneValueDifferentLabelsB = toDataFrame({
name: 'B',
fields: [
{ name: 'time', type: FieldType.time, values: [1000, 2000] },
{ name: 'temp', type: FieldType.number, values: [-1, -2], labels: { location: 'outside', sky: 'cloudy' } },
],
});
const result = transformDataFrame([cfg], [oneValueDifferentLabelsA, oneValueDifferentLabelsB]);
const expected: Field[] = [
{ name: 'time', type: FieldType.time, values: new ArrayVector([1000, 1000, 2000, 2000]), config: {} },
{
name: 'location',
type: FieldType.string,
values: new ArrayVector(['inside', 'outside', 'inside', 'outside']),
config: {},
},
{ name: 'feelsLike', type: FieldType.string, values: new ArrayVector(['ok', null, 'ok', null]), config: {} },
{ name: 'sky', type: FieldType.string, values: new ArrayVector([null, 'cloudy', null, 'cloudy']), config: {} },
{ name: 'temp', type: FieldType.number, values: new ArrayVector([1, -1, 2, -2]), config: {} },
];
expect(result[0].fields).toEqual(expected);
});
});

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@ -0,0 +1,135 @@
import { DataFrame, DataTransformerInfo, FieldType } from '../../types';
import { DataTransformerID } from './ids';
import { MutableDataFrame } from '../../dataframe';
import { ArrayVector } from '../../vector';
import { filterFieldsTransformer } from './filter';
import { FieldMatcherID } from '..';
export interface LabelsToFieldsOptions {}
type MapItem = { type: FieldType; values: Record<string, any>; isValue: boolean };
type SeriesMapItem = Record<string, MapItem>;
type Map = Record<string, SeriesMapItem>;
export const labelsToFieldsTransformer: DataTransformerInfo<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
name: 'Labels to fields',
description: 'Groups series by time and return labels as columns',
defaultOptions: {},
transformer: options => (data: DataFrame[]) => {
const framesWithTimeField = filterFieldsTransformer.transformer({ include: { id: FieldMatcherID.time } })(data);
if (!framesWithTimeField.length || !framesWithTimeField[0].fields.length) {
return data;
}
const framesWithoutTimeField = filterFieldsTransformer.transformer({ exclude: { id: FieldMatcherID.time } })(data);
if (!framesWithoutTimeField.length || !framesWithoutTimeField[0].fields.length) {
return data;
}
const columnsMap = createColumnsMap(framesWithTimeField, framesWithoutTimeField);
const processed = createFields(columnsMap);
const values: Record<string, any[]> = {};
const timeColumnItem = columnsMap[processed.fields[0].name];
const seriesIndexStrings = Object.keys(timeColumnItem);
for (const seriesIndexString of seriesIndexStrings) {
const seriesItem = timeColumnItem[seriesIndexString];
const timeValueStrings = Object.keys(seriesItem.values);
for (const timeValueString of timeValueStrings) {
if (!values[timeValueString]) {
values[timeValueString] = [];
}
let row = new Array(processed.fields.length);
for (let index = 0; index < processed.fields.length; index++) {
const field = processed.fields[index];
const valueItem = columnsMap[field.name][seriesIndexString];
const value = valueItem ? valueItem.values[timeValueString] ?? null : null;
row[index] = value;
}
values[timeValueString].push(row);
}
}
const timestamps = Object.values(values);
for (const timestamp of timestamps) {
for (const row of timestamp) {
for (let fieldIndex = 0; fieldIndex < processed.fields.length; fieldIndex++) {
processed.fields[fieldIndex].values.add(row[fieldIndex]);
}
}
}
return [processed];
},
};
function addOrAppendMapItem(args: { map: Map; series: number; column: string; type: FieldType; isValue?: boolean }) {
const { map, column, type, series, isValue = false } = args;
// we're using the fact that the series (number) will automatically become a string prop on the object
const seriesMapItem: SeriesMapItem = { [series]: { type, values: {}, isValue } };
if (!map[column]) {
map[column] = seriesMapItem;
}
if (!map[column][series]) {
map[column] = { ...map[column], ...seriesMapItem };
}
}
// this is a naive implementation that does the job, not optimized for performance or speed
function createColumnsMap(framesWithTimeField: DataFrame[], framesWithoutTimeField: DataFrame[]) {
const map: Map = {};
for (let frameIndex = 0; frameIndex < framesWithTimeField.length; frameIndex++) {
const timeFrame = framesWithTimeField[frameIndex];
const otherFrame = framesWithoutTimeField[frameIndex];
const timeField = timeFrame.fields[0];
addOrAppendMapItem({ map, column: timeField.name, series: frameIndex, type: timeField.type });
for (let valueIndex = 0; valueIndex < timeFrame.length; valueIndex++) {
const timeFieldValue = timeField.values.get(valueIndex);
map[timeField.name][frameIndex].values[timeFieldValue] = timeFieldValue;
for (const field of otherFrame.fields) {
if (field.labels) {
const labels = Object.keys(field.labels);
for (const label of labels) {
addOrAppendMapItem({ map, column: label, series: frameIndex, type: FieldType.string });
map[label][frameIndex].values[timeFieldValue] = field.labels[label];
}
}
const otherFieldValue = field.values.get(valueIndex);
addOrAppendMapItem({ map, column: field.name, series: frameIndex, type: field.type, isValue: true });
map[field.name][frameIndex].values[timeFieldValue] = otherFieldValue;
}
}
}
return map;
}
function createFields(columnsMap: Map) {
const columns = Object.keys(columnsMap);
const processed = new MutableDataFrame();
const valueColumns: string[] = [];
for (const column of columns) {
const columnItem = Object.values<MapItem>(columnsMap[column])[0];
if (columnItem.isValue) {
valueColumns.push(column);
continue;
}
processed.addField({ type: columnItem.type, values: new ArrayVector(), name: column });
}
for (const column of valueColumns) {
const columnItem = Object.values<MapItem>(columnsMap[column])[0];
processed.addField({ type: columnItem.type, values: new ArrayVector(), name: column });
}
return processed;
}

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@ -0,0 +1,19 @@
import React from 'react';
import { DataTransformerID, standardTransformers, TransformerRegistyItem, TransformerUIProps } from '@grafana/data';
import { LabelsToFieldsOptions } from '@grafana/data/src/transformations/transformers/labelsToFields';
export const LabelsAsFieldsTransformerEditor: React.FC<TransformerUIProps<LabelsToFieldsOptions>> = ({
input,
options,
onChange,
}) => {
return null;
};
export const labelsAsFieldsTransformerRegistryItem: TransformerRegistyItem<LabelsToFieldsOptions> = {
id: DataTransformerID.labelsToFields,
editor: LabelsAsFieldsTransformerEditor,
transformation: standardTransformers.labelsToFieldsTransformer,
name: 'Labels as fields',
description: 'Groups series by time and return labels as fields',
};

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@ -5,6 +5,7 @@ import { filterFramesByRefIdTransformRegistryItem } from '../components/Transfor
import { organizeFieldsTransformRegistryItem } from '../components/TransformersUI/OrganizeFieldsTransformerEditor';
import { seriesToFieldsTransformerRegistryItem } from '../components/TransformersUI/SeriesToFieldsTransformerEditor';
import { calculateFieldTransformRegistryItem } from '../components/TransformersUI/CalculateFieldTransformerEditor';
import { labelsAsFieldsTransformerRegistryItem } from '../components/TransformersUI/LabelsAsFieldsTransformerEditor';
export const getStandardTransformers = (): Array<TransformerRegistyItem<any>> => {
return [
@ -14,5 +15,6 @@ export const getStandardTransformers = (): Array<TransformerRegistyItem<any>> =>
organizeFieldsTransformRegistryItem,
seriesToFieldsTransformerRegistryItem,
calculateFieldTransformRegistryItem,
labelsAsFieldsTransformerRegistryItem,
];
};