Transformations: Add Group to Nested Tables Transformation (#79952)

* Stub group to subframe transformation

* Get proper field grouping

* Mostly working but fields not displaying 😭

* Fix display processing in nested tables

* Modularize and start merging groupBy and groupToSubrame

* Get this working

* Prettier

* Typing things

* More types

* Add option for showing subframe table headers

* Prettier

* Get tests going

* Update tests

* Fix naming and add icons

* Betterer fix

* Prettier

* Fix CSS object syntax

* Prettier

* Stub alert for calcs with grouping, start renaming

* Add logic to show warning message for calculations

* Add calc warning

* Renaming and feature flag

* Rename images

* Prettier

* Fix tests

* Update feature toggle

* Fix error showing extra blank row

* minor code cleanup

---------

Co-authored-by: nmarrs <nathanielmarrs@gmail.com>
This commit is contained in:
Kyle Cunningham 2024-02-07 21:28:26 +07:00 committed by GitHub
parent 26bc87b60e
commit 756cd3c28b
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
17 changed files with 941 additions and 57 deletions

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@ -87,6 +87,7 @@ Some features are enabled by default. You can disable these feature by setting t
| `canvasPanelPanZoom` | Allow pan and zoom in canvas panel |
| `regressionTransformation` | Enables regression analysis transformation |
| `alertingPreviewUpgrade` | Show Unified Alerting preview and upgrade page in legacy alerting |
| `groupToNestedTableTransformation` | Enables the group to nested table transformation |
## Experimental feature toggles

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@ -206,6 +206,13 @@ export function applyFieldOverrides(options: ApplyFieldOverrideOptions): DataFra
for (const nestedFrames of field.values) {
for (let nfIndex = 0; nfIndex < nestedFrames.length; nfIndex++) {
for (const valueField of nestedFrames[nfIndex].fields) {
// Get display processor for nested fields
valueField.display = getDisplayProcessor({
field: valueField,
theme: options.theme,
timeZone: options.timeZone,
});
valueField.state = {
scopedVars: {
__dataContext: {

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@ -9,6 +9,7 @@ import { filterByValueTransformer } from './transformers/filterByValue';
import { formatStringTransformer } from './transformers/formatString';
import { formatTimeTransformer } from './transformers/formatTime';
import { groupByTransformer } from './transformers/groupBy';
import { groupToNestedTable } from './transformers/groupToNestedTable';
import { groupingToMatrixTransformer } from './transformers/groupingToMatrix';
import { histogramTransformer } from './transformers/histogram';
import { joinByFieldTransformer } from './transformers/joinByField';
@ -53,4 +54,5 @@ export const standardTransformers = {
convertFieldTypeTransformer,
groupingToMatrixTransformer,
limitTransformer,
groupToNestedTable,
};

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@ -22,6 +22,10 @@ export interface GroupByTransformerOptions {
fields: Record<string, GroupByFieldOptions>;
}
interface FieldMap {
[key: string]: Field;
}
export const groupByTransformer: DataTransformerInfo<GroupByTransformerOptions> = {
id: DataTransformerID.groupBy,
name: 'Group by',
@ -75,64 +79,19 @@ export const groupByTransformer: DataTransformerInfo<GroupByTransformerOptions>
const processed: DataFrame[] = [];
for (const frame of data) {
const groupByFields: Field[] = [];
for (const field of frame.fields) {
if (shouldGroupOnField(field, options)) {
groupByFields.push(field);
}
}
// Create a list of fields to group on
// If there are none we skip the rest
const groupByFields: Field[] = frame.fields.filter((field) => shouldGroupOnField(field, options));
if (groupByFields.length === 0) {
continue; // No group by field in this frame, ignore the frame
continue;
}
// Group the values by fields and groups so we can get all values for a
// group for a given field.
const valuesByGroupKey = new Map<string, Record<string, Field>>();
for (let rowIndex = 0; rowIndex < frame.length; rowIndex++) {
const groupKey = String(groupByFields.map((field) => field.values[rowIndex]));
const valuesByField = valuesByGroupKey.get(groupKey) ?? {};
const valuesByGroupKey = groupValuesByKey(frame, groupByFields);
if (!valuesByGroupKey.has(groupKey)) {
valuesByGroupKey.set(groupKey, valuesByField);
}
for (let field of frame.fields) {
const fieldName = getFieldDisplayName(field);
if (!valuesByField[fieldName]) {
valuesByField[fieldName] = {
name: fieldName,
type: field.type,
config: { ...field.config },
values: [],
};
}
valuesByField[fieldName].values.push(field.values[rowIndex]);
}
}
const fields: Field[] = [];
for (const field of groupByFields) {
const values: unknown[] = [];
const fieldName = getFieldDisplayName(field);
valuesByGroupKey.forEach((value) => {
values.push(value[fieldName].values[0]);
});
fields.push({
name: field.name,
type: field.type,
config: {
...field.config,
},
values: values,
});
}
// Add the grouped fields to the resulting fields of the transformation
const fields: Field[] = createGroupedFields(groupByFields, valuesByGroupKey);
// Then for each calculations configured, compute and add a new field (column)
for (const field of frame.fields) {
@ -197,7 +156,7 @@ const shouldCalculateField = (field: Field, options: GroupByTransformerOptions):
);
};
const detectFieldType = (aggregation: string, sourceField: Field, targetField: Field): FieldType => {
function detectFieldType(aggregation: string, sourceField: Field, targetField: Field): FieldType {
switch (aggregation) {
case ReducerID.allIsNull:
return FieldType.boolean;
@ -209,4 +168,75 @@ const detectFieldType = (aggregation: string, sourceField: Field, targetField: F
default:
return guessFieldTypeForField(targetField) ?? FieldType.string;
}
};
}
/**
* Groups values together by key. This will create a mapping of strings
* to _FieldMaps_ that will then be used to group values on.
*
* @param frame
* The dataframe containing the data to group.
* @param groupByFields
* An array of fields to group on.
*/
export function groupValuesByKey(frame: DataFrame, groupByFields: Field[]) {
const valuesByGroupKey = new Map<string, FieldMap>();
for (let rowIndex = 0; rowIndex < frame.length; rowIndex++) {
const groupKey = String(groupByFields.map((field) => field.values[rowIndex]));
const valuesByField = valuesByGroupKey.get(groupKey) ?? {};
if (!valuesByGroupKey.has(groupKey)) {
valuesByGroupKey.set(groupKey, valuesByField);
}
for (let field of frame.fields) {
const fieldName = getFieldDisplayName(field);
if (!valuesByField[fieldName]) {
valuesByField[fieldName] = {
name: fieldName,
type: field.type,
config: { ...field.config },
values: [],
};
}
valuesByField[fieldName].values.push(field.values[rowIndex]);
}
}
return valuesByGroupKey;
}
/**
* Create new fields which will be used to display grouped values.
*
* @param groupByFields
* @param valuesByGroupKey
* @returns
* Returns an array of fields that have been grouped.
*/
export function createGroupedFields(groupByFields: Field[], valuesByGroupKey: Map<string, FieldMap>): Field[] {
const fields: Field[] = [];
for (const field of groupByFields) {
const values: unknown[] = [];
const fieldName = getFieldDisplayName(field);
valuesByGroupKey.forEach((value) => {
values.push(value[fieldName].values[0]);
});
fields.push({
name: field.name,
type: field.type,
config: {
...field.config,
},
values,
});
}
return fields;
}

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@ -0,0 +1,243 @@
import { toDataFrame } from '../../dataframe/processDataFrame';
import { DataTransformerConfig, Field, FieldType } from '../../types';
import { mockTransformationsRegistry } from '../../utils/tests/mockTransformationsRegistry';
import { ReducerID } from '../fieldReducer';
import { transformDataFrame } from '../transformDataFrame';
import { GroupByOperationID, GroupByTransformerOptions } from './groupBy';
import { groupToNestedTable, GroupToNestedTableTransformerOptions } from './groupToNestedTable';
import { DataTransformerID } from './ids';
describe('GroupToSubframe transformer', () => {
beforeAll(() => {
mockTransformationsRegistry([groupToNestedTable]);
});
it('should group values by message and place values in subframe', async () => {
const testSeries = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [3000, 4000, 5000, 6000, 7000, 8000] },
{ name: 'message', type: FieldType.string, values: ['one', 'two', 'two', 'three', 'three', 'three'] },
{ name: 'values', type: FieldType.string, values: [1, 2, 2, 3, 3, 3] },
],
});
const cfg: DataTransformerConfig<GroupToNestedTableTransformerOptions> = {
id: DataTransformerID.groupToNestedTable,
options: {
fields: {
message: {
operation: GroupByOperationID.groupBy,
aggregations: [],
},
},
},
};
await expect(transformDataFrame([cfg], [testSeries])).toEmitValuesWith((received) => {
const result = received[0];
const expected: Field[] = [
{
name: 'message',
type: FieldType.string,
config: {},
values: ['one', 'two', 'three'],
},
{
name: 'Nested frames',
type: FieldType.nestedFrames,
config: {},
values: [
[
{
meta: { custom: { noHeader: false } },
length: 1,
fields: [
{ name: 'time', type: 'time', config: {}, values: [3000] },
{ name: 'values', type: 'string', config: {}, values: [1] },
],
},
],
[
{
meta: { custom: { noHeader: false } },
length: 2,
fields: [
{
name: 'time',
type: 'time',
config: {},
values: [4000, 5000],
},
{
name: 'values',
type: 'string',
config: {},
values: [2, 2],
},
],
},
],
[
{
meta: { custom: { noHeader: false } },
length: 3,
fields: [
{
name: 'time',
type: 'time',
config: {},
values: [6000, 7000, 8000],
},
{
name: 'values',
type: 'string',
config: {},
values: [3, 3, 3],
},
],
},
],
],
},
];
expect(result[0].fields).toEqual(expected);
});
});
it('should group by message, compute a few calculations for each group of values, and place other values in a subframe', async () => {
const testSeries = toDataFrame({
name: 'A',
fields: [
{ name: 'time', type: FieldType.time, values: [3000, 4000, 5000, 6000, 7000, 8000] },
{ name: 'message', type: FieldType.string, values: ['one', 'two', 'two', 'three', 'three', 'three'] },
{ name: 'values', type: FieldType.number, values: [1, 2, 2, 3, 3, 3] },
{ name: 'intVal', type: FieldType.number, values: [1, 2, 3, 4, 5, 6] },
{ name: 'floatVal', type: FieldType.number, values: [1.1, 2.3, 3.6, 4.8, 5.7, 6.9] },
],
});
const cfg: DataTransformerConfig<GroupByTransformerOptions> = {
id: DataTransformerID.groupToNestedTable,
options: {
fields: {
message: {
operation: GroupByOperationID.groupBy,
aggregations: [],
},
values: {
operation: GroupByOperationID.aggregate,
aggregations: [ReducerID.sum],
},
},
},
};
await expect(transformDataFrame([cfg], [testSeries])).toEmitValuesWith((received) => {
const result = received[0];
const expected: Field[] = [
{
name: 'message',
type: FieldType.string,
config: {},
values: ['one', 'two', 'three'],
},
{
name: 'values (sum)',
values: [1, 4, 9],
type: FieldType.number,
config: {},
},
{
config: {},
name: 'Nested frames',
type: FieldType.nestedFrames,
values: [
[
{
meta: { custom: { noHeader: false } },
length: 1,
fields: [
{
name: 'time',
type: 'time',
config: {},
values: [3000],
},
{
name: 'intVal',
type: 'number',
config: {},
values: [1],
},
{
name: 'floatVal',
type: 'number',
config: {},
values: [1.1],
},
],
},
],
[
{
meta: { custom: { noHeader: false } },
length: 2,
fields: [
{
name: 'time',
type: 'time',
config: {},
values: [4000, 5000],
},
{
name: 'intVal',
type: 'number',
config: {},
values: [2, 3],
},
{
name: 'floatVal',
type: 'number',
config: {},
values: [2.3, 3.6],
},
],
},
],
[
{
meta: { custom: { noHeader: false } },
length: 3,
fields: [
{
name: 'time',
type: 'time',
config: {},
values: [6000, 7000, 8000],
},
{
name: 'intVal',
type: 'number',
config: {},
values: [4, 5, 6],
},
{
name: 'floatVal',
type: 'number',
config: {},
values: [4.8, 5.7, 6.9],
},
],
},
],
],
},
];
expect(result[0].fields).toEqual(expected);
});
});
});

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@ -0,0 +1,235 @@
import { map } from 'rxjs/operators';
import { guessFieldTypeForField } from '../../dataframe/processDataFrame';
import { getFieldDisplayName } from '../../field/fieldState';
import { DataFrame, Field, FieldType } from '../../types/dataFrame';
import { DataTransformerInfo } from '../../types/transformations';
import { ReducerID, reduceField } from '../fieldReducer';
import { GroupByFieldOptions, createGroupedFields, groupValuesByKey } from './groupBy';
import { DataTransformerID } from './ids';
export const SHOW_NESTED_HEADERS_DEFAULT = true;
export enum GroupByOperationID {
aggregate = 'aggregate',
groupBy = 'groupby',
}
export interface GroupToNestedTableTransformerOptions {
showSubframeHeaders?: boolean;
fields: Record<string, GroupByFieldOptions>;
}
interface FieldMap {
[key: string]: Field;
}
export const groupToNestedTable: DataTransformerInfo<GroupToNestedTableTransformerOptions> = {
id: DataTransformerID.groupToNestedTable,
name: 'Group to nested tables',
description: 'Group data by a field value and create nested tables with the grouped data',
defaultOptions: {
showSubframeHeaders: SHOW_NESTED_HEADERS_DEFAULT,
fields: {},
},
/**
* Return a modified copy of the series. If the transform is not or should not
* be applied, just return the input series
*/
operator: (options) => (source) =>
source.pipe(
map((data) => {
const hasValidConfig = Object.keys(options.fields).find(
(name) => options.fields[name].operation === GroupByOperationID.groupBy
);
if (!hasValidConfig) {
return data;
}
const processed: DataFrame[] = [];
for (const frame of data) {
// Create a list of fields to group on
// If there are none we skip the rest
const groupByFields: Field[] = frame.fields.filter((field) => shouldGroupOnField(field, options));
if (groupByFields.length === 0) {
continue;
}
// Group the values by fields and groups so we can get all values for a
// group for a given field.
const valuesByGroupKey = groupValuesByKey(frame, groupByFields);
// Add the grouped fields to the resulting fields of the transformation
const fields: Field[] = createGroupedFields(groupByFields, valuesByGroupKey);
// Group data into sub frames so they will display as tables
const subFrames: DataFrame[][] = groupToSubframes(valuesByGroupKey, options);
// Then for each calculations configured, compute and add a new field (column)
for (let i = 0; i < frame.fields.length; i++) {
const field = frame.fields[i];
if (!shouldCalculateField(field, options)) {
continue;
}
const fieldName = getFieldDisplayName(field);
const aggregations = options.fields[fieldName].aggregations;
const valuesByAggregation: Record<string, unknown[]> = {};
valuesByGroupKey.forEach((value) => {
const fieldWithValuesForGroup = value[fieldName];
const results = reduceField({
field: fieldWithValuesForGroup,
reducers: aggregations,
});
for (const aggregation of aggregations) {
if (!Array.isArray(valuesByAggregation[aggregation])) {
valuesByAggregation[aggregation] = [];
}
valuesByAggregation[aggregation].push(results[aggregation]);
}
});
for (const aggregation of aggregations) {
const aggregationField: Field = {
name: `${fieldName} (${aggregation})`,
values: valuesByAggregation[aggregation],
type: FieldType.other,
config: {},
};
aggregationField.type = detectFieldType(aggregation, field, aggregationField);
fields.push(aggregationField);
}
}
fields.push({
config: {},
name: 'Nested frames',
type: FieldType.nestedFrames,
values: subFrames,
});
processed.push({
fields,
length: valuesByGroupKey.size,
});
}
return processed;
})
),
};
/**
* Given the appropriate data, create a sub-frame
* which can then be displayed in a sub-table.
*/
function createSubframe(fields: Field[], frameLength: number, options: GroupToNestedTableTransformerOptions) {
const showHeaders =
options.showSubframeHeaders === undefined ? SHOW_NESTED_HEADERS_DEFAULT : options.showSubframeHeaders;
return {
meta: { custom: { noHeader: !showHeaders } },
length: frameLength,
fields,
};
}
/**
* Determines whether a field should be grouped on.
*
* @returns boolean
* This will return _true_ if a field should be grouped on and _false_ if it should not.
*/
const shouldGroupOnField = (field: Field, options: GroupToNestedTableTransformerOptions): boolean => {
const fieldName = getFieldDisplayName(field);
return options?.fields[fieldName]?.operation === GroupByOperationID.groupBy;
};
/**
* Determines whether field aggregations should be calculated
* @returns boolean
* This will return _true_ if a field should be calculated and _false_ if it should not.
*/
const shouldCalculateField = (field: Field, options: GroupToNestedTableTransformerOptions): boolean => {
const fieldName = getFieldDisplayName(field);
return (
options?.fields[fieldName]?.operation === GroupByOperationID.aggregate &&
Array.isArray(options?.fields[fieldName].aggregations) &&
options?.fields[fieldName].aggregations.length > 0
);
};
/**
* Detect the type of field given the relevant aggregation.
*/
const detectFieldType = (aggregation: string, sourceField: Field, targetField: Field): FieldType => {
switch (aggregation) {
case ReducerID.allIsNull:
return FieldType.boolean;
case ReducerID.last:
case ReducerID.lastNotNull:
case ReducerID.first:
case ReducerID.firstNotNull:
return sourceField.type;
default:
return guessFieldTypeForField(targetField) ?? FieldType.string;
}
};
/**
* Group values into subframes so that they'll be displayed
* inside of a subtable.
*
* @param valuesByGroupKey
* A mapping of group keys to their respective grouped values.
* @param options
* Transformation options, which are used to find ungrouped/unaggregated fields.
* @returns
*/
function groupToSubframes(
valuesByGroupKey: Map<string, FieldMap>,
options: GroupToNestedTableTransformerOptions
): DataFrame[][] {
const subFrames: DataFrame[][] = [];
// Construct a subframe of any fields
// that aren't being group on or reduced
for (const [, value] of valuesByGroupKey) {
const nestedFields: Field[] = [];
for (const [fieldName, field] of Object.entries(value)) {
const fieldOpts = options.fields[fieldName];
if (fieldOpts === undefined) {
nestedFields.push(field);
}
// Depending on the configuration form state all of the following are possible
else if (
fieldOpts.aggregations === undefined ||
(fieldOpts.operation === GroupByOperationID.aggregate && fieldOpts.aggregations.length === 0) ||
fieldOpts.operation === null ||
fieldOpts.operation === undefined
) {
nestedFields.push(field);
}
}
// If there are any values in the subfields
// push a new subframe with the fields
// otherwise push an empty frame
if (nestedFields.length > 0) {
subFrames.push([createSubframe(nestedFields, nestedFields[0].values.length, options)]);
} else {
subFrames.push([createSubframe([], 0, options)]);
}
}
return subFrames;
}

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@ -40,4 +40,5 @@ export enum DataTransformerID {
formatTime = 'formatTime',
formatString = 'formatString',
regression = 'regression',
groupToNestedTable = 'groupToNestedTable',
}

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@ -173,4 +173,5 @@ export interface FeatureToggles {
alertingSaveStatePeriodic?: boolean;
promQLScope?: boolean;
nodeGraphDotLayout?: boolean;
groupToNestedTableTransformation?: boolean;
}

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@ -1310,5 +1310,13 @@ var (
Owner: grafanaObservabilityTracesAndProfilingSquad,
Created: time.Date(2024, time.January, 2, 12, 0, 0, 0, time.UTC),
},
{
Name: "groupToNestedTableTransformation",
Description: "Enables the group to nested table transformation",
Stage: FeatureStagePublicPreview,
FrontendOnly: true,
Owner: grafanaDatavizSquad,
Created: time.Date(2024, time.February, 5, 12, 0, 0, 0, time.UTC),
},
}
)

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@ -154,3 +154,4 @@ onPremToCloudMigrations,experimental,@grafana/grafana-operator-experience-squad,
alertingSaveStatePeriodic,privatePreview,@grafana/alerting-squad,2024-01-22,false,false,false
promQLScope,experimental,@grafana/observability-metrics,2024-01-29,false,false,false
nodeGraphDotLayout,experimental,@grafana/observability-traces-and-profiling,2024-01-02,false,false,true
groupToNestedTableTransformation,preview,@grafana/dataviz-squad,2024-02-05,false,false,true

1 Name Stage Owner Created requiresDevMode RequiresRestart FrontendOnly
154 alertingSaveStatePeriodic privatePreview @grafana/alerting-squad 2024-01-22 false false false
155 promQLScope experimental @grafana/observability-metrics 2024-01-29 false false false
156 nodeGraphDotLayout experimental @grafana/observability-traces-and-profiling 2024-01-02 false false true
157 groupToNestedTableTransformation preview @grafana/dataviz-squad 2024-02-05 false false true

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@ -626,4 +626,8 @@ const (
// FlagNodeGraphDotLayout
// Changed the layout algorithm for the node graph
FlagNodeGraphDotLayout = "nodeGraphDotLayout"
// FlagGroupToNestedTableTransformation
// Enables the group to nested table transformation
FlagGroupToNestedTableTransformation = "groupToNestedTableTransformation"
)

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@ -16,7 +16,7 @@ import {
GroupByOperationID,
GroupByTransformerOptions,
} from '@grafana/data/src/transformations/transformers/groupBy';
import { useTheme2, Select, StatsPicker, InlineField, Stack } from '@grafana/ui';
import { useTheme2, Select, StatsPicker, InlineField, Stack, Alert } from '@grafana/ui';
import { getTransformationContent } from '../docs/getTransformationContent';
import { useAllFieldNamesFromDataFrames } from '../utils';
@ -49,8 +49,28 @@ export const GroupByTransformerEditor = ({
[onChange]
);
// See if there's both an aggregation and grouping field configured
// for calculations. If not we display a warning because there
// needs to be a grouping for the calculation to have effect
let hasGrouping,
hasAggregation = false;
for (const field of Object.values(options.fields)) {
if (field.aggregations.length > 0 && field.operation !== null) {
hasAggregation = true;
}
if (field.operation === GroupByOperationID.groupBy) {
hasGrouping = true;
}
}
const showCalcAlert = hasAggregation && !hasGrouping;
return (
<div>
<Stack direction="column">
{showCalcAlert && (
<Alert title="Calculations will not have an effect if no fields are being grouped on." severity="warning" />
)}
{fieldNames.map((key) => (
<GroupByFieldConfiguration
onConfigChange={onConfigChange(key)}
@ -59,7 +79,7 @@ export const GroupByTransformerEditor = ({
key={key}
/>
))}
</div>
</Stack>
);
};

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@ -0,0 +1,185 @@
import { css } from '@emotion/css';
import React, { useCallback } from 'react';
import {
DataTransformerID,
ReducerID,
SelectableValue,
standardTransformers,
TransformerRegistryItem,
TransformerUIProps,
TransformerCategory,
GrafanaTheme2,
} from '@grafana/data';
import {
GroupByFieldOptions,
GroupByOperationID,
GroupByTransformerOptions,
} from '@grafana/data/src/transformations/transformers/groupBy';
import {
GroupToNestedTableTransformerOptions,
SHOW_NESTED_HEADERS_DEFAULT,
} from '@grafana/data/src/transformations/transformers/groupToNestedTable';
import { Stack } from '@grafana/experimental';
import { useTheme2, Select, StatsPicker, InlineField, Field, Switch, Alert } from '@grafana/ui';
import { useAllFieldNamesFromDataFrames } from '../utils';
interface FieldProps {
fieldName: string;
config?: GroupByFieldOptions;
onConfigChange: (config: GroupByFieldOptions) => void;
}
export const GroupToNestedTableTransformerEditor = ({
input,
options,
onChange,
}: TransformerUIProps<GroupToNestedTableTransformerOptions>) => {
const fieldNames = useAllFieldNamesFromDataFrames(input);
const showHeaders =
options.showSubframeHeaders === undefined ? SHOW_NESTED_HEADERS_DEFAULT : options.showSubframeHeaders;
const onConfigChange = useCallback(
(fieldName: string) => (config: GroupByFieldOptions) => {
onChange({
...options,
fields: {
...options.fields,
[fieldName]: config,
},
});
},
// Adding options to the dependency array causes infinite loop here.
// eslint-disable-next-line react-hooks/exhaustive-deps
[onChange]
);
const onShowFieldNamesChange = useCallback(
() => {
const showSubframeHeaders =
options.showSubframeHeaders === undefined ? !SHOW_NESTED_HEADERS_DEFAULT : !options.showSubframeHeaders;
onChange({
showSubframeHeaders,
fields: {
...options.fields,
},
});
},
// Adding options to the dependency array causes infinite loop here.
// eslint-disable-next-line react-hooks/exhaustive-deps
[onChange]
);
// See if there's both an aggregation and grouping field configured
// for calculations. If not we display a warning because there
// needs to be a grouping for the calculation to have effect
let hasGrouping,
hasAggregation = false;
for (const field of Object.values(options.fields)) {
if (field.aggregations.length > 0 && field.operation !== null) {
hasAggregation = true;
}
if (field.operation === GroupByOperationID.groupBy) {
hasGrouping = true;
}
}
const showCalcAlert = hasAggregation && !hasGrouping;
return (
<Stack direction="column">
{showCalcAlert && (
<Alert title="Calculations will not have an effect if no fields are being grouped on." severity="warning" />
)}
<div>
{fieldNames.map((key) => (
<GroupByFieldConfiguration
onConfigChange={onConfigChange(key)}
fieldName={key}
config={options.fields[key]}
key={key}
/>
))}
</div>
<Field
label="Show field names in nested tables"
description="If enabled nested tables will show field names as a table header"
>
<Switch value={showHeaders} onChange={onShowFieldNamesChange} />
</Field>
</Stack>
);
};
const options = [
{ label: 'Group by', value: GroupByOperationID.groupBy },
{ label: 'Calculate', value: GroupByOperationID.aggregate },
];
export const GroupByFieldConfiguration = ({ fieldName, config, onConfigChange }: FieldProps) => {
const theme = useTheme2();
const styles = getStyles(theme);
const onChange = useCallback(
(value: SelectableValue<GroupByOperationID | null>) => {
onConfigChange({
aggregations: config?.aggregations ?? [],
operation: value?.value ?? null,
});
},
[config, onConfigChange]
);
return (
<InlineField className={styles.label} label={fieldName} grow shrink>
<Stack gap={0.5} direction="row" wrap={false}>
<div className={styles.operation}>
<Select options={options} value={config?.operation} placeholder="Ignored" onChange={onChange} isClearable />
</div>
{config?.operation === GroupByOperationID.aggregate && (
<StatsPicker
className={styles.aggregations}
placeholder="Select Stats"
allowMultiple
stats={config.aggregations}
onChange={(stats) => {
// eslint-disable-next-line
onConfigChange({ ...config, aggregations: stats as ReducerID[] });
}}
/>
)}
</Stack>
</InlineField>
);
};
const getStyles = (theme: GrafanaTheme2) => {
return {
label: css({
minWidth: theme.spacing(32),
}),
operation: css({
flexShrink: 0,
height: '100%',
width: theme.spacing(24),
}),
aggregations: css({
flexGrow: 1,
}),
};
};
export const groupToNestedTableTransformRegistryItem: TransformerRegistryItem<GroupByTransformerOptions> = {
id: DataTransformerID.groupToNestedTable,
editor: GroupToNestedTableTransformerEditor,
transformation: standardTransformers.groupToNestedTable,
name: standardTransformers.groupToNestedTable.name,
description: standardTransformers.groupToNestedTable.description,
categories: new Set([
TransformerCategory.Combine,
TransformerCategory.CalculateNewFields,
TransformerCategory.Reformat,
]),
};

View File

@ -12,6 +12,7 @@ import { filterFramesByRefIdTransformRegistryItem } from './editors/FilterByRefI
import { formatStringTransformerRegistryItem } from './editors/FormatStringTransformerEditor';
import { formatTimeTransformerRegistryItem } from './editors/FormatTimeTransformerEditor';
import { groupByTransformRegistryItem } from './editors/GroupByTransformerEditor';
import { groupToNestedTableTransformRegistryItem } from './editors/GroupToNestedTableTransformerEditor';
import { groupingToMatrixTransformRegistryItem } from './editors/GroupingToMatrixTransformerEditor';
import { histogramTransformRegistryItem } from './editors/HistogramTransformerEditor';
import { joinByFieldTransformerRegistryItem } from './editors/JoinByFieldTransformerEditor';
@ -64,6 +65,7 @@ export const getStandardTransformers = (): Array<TransformerRegistryItem<any>> =
partitionByValuesTransformRegistryItem,
...(config.featureToggles.formatString ? [formatStringTransformerRegistryItem] : []),
...(config.featureToggles.regressionTransformation ? [regressionTransformerRegistryItem] : []),
...(config.featureToggles.groupToNestedTableTransformation ? [groupToNestedTableTransformRegistryItem] : []),
formatTimeTransformerRegistryItem,
timeSeriesTableTransformRegistryItem,
];

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