53ea09078f
Co-authored-by: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>
265 lines
7.2 KiB
TypeScript
265 lines
7.2 KiB
TypeScript
/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License;
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* you may not use this file except in compliance with the Elastic License.
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*/
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import { Ast } from '@kbn/interpreter/common';
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import { i18n } from '@kbn/i18n';
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import {
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SuggestionRequest,
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Visualization,
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VisualizationSuggestion,
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Operation,
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DatasourcePublicAPI,
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} from '../types';
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import { LensIconChartDatatable } from '../assets/chart_datatable';
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export interface LayerState {
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layerId: string;
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columns: string[];
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}
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export interface DatatableVisualizationState {
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layers: LayerState[];
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}
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function newLayerState(layerId: string): LayerState {
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return {
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layerId,
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columns: [],
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};
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}
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export const datatableVisualization: Visualization<DatatableVisualizationState> = {
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id: 'lnsDatatable',
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visualizationTypes: [
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{
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id: 'lnsDatatable',
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icon: LensIconChartDatatable,
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label: i18n.translate('xpack.lens.datatable.label', {
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defaultMessage: 'Data table',
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}),
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},
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],
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getVisualizationTypeId() {
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return 'lnsDatatable';
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},
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getLayerIds(state) {
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return state.layers.map((l) => l.layerId);
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},
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clearLayer(state) {
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return {
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layers: state.layers.map((l) => newLayerState(l.layerId)),
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};
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},
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getDescription() {
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return {
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icon: LensIconChartDatatable,
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label: i18n.translate('xpack.lens.datatable.label', {
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defaultMessage: 'Data table',
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}),
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};
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},
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switchVisualizationType: (_, state) => state,
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initialize(frame, state) {
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return (
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state || {
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layers: [newLayerState(frame.addNewLayer())],
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}
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);
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},
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getSuggestions({
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table,
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state,
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keptLayerIds,
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}: SuggestionRequest<DatatableVisualizationState>): Array<
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VisualizationSuggestion<DatatableVisualizationState>
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> {
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if (
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keptLayerIds.length > 1 ||
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(keptLayerIds.length && table.layerId !== keptLayerIds[0]) ||
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(state && table.changeType === 'unchanged')
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) {
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return [];
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}
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const title =
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table.changeType === 'unchanged'
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? i18n.translate('xpack.lens.datatable.suggestionLabel', {
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defaultMessage: 'As table',
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})
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: i18n.translate('xpack.lens.datatable.visualizationOf', {
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defaultMessage: 'Table {operations}',
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values: {
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operations:
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table.label ||
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table.columns
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.map((col) => col.operation.label)
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.join(
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i18n.translate('xpack.lens.datatable.conjunctionSign', {
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defaultMessage: ' & ',
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description:
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'A character that can be used for conjunction of multiple enumarated items. Make sure to include spaces around it if needed.',
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})
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),
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},
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});
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return [
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{
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title,
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// table with >= 10 columns will have a score of 0.4, fewer columns reduce score
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score: (Math.min(table.columns.length, 10) / 10) * 0.4,
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state: {
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layers: [
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{
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layerId: table.layerId,
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columns: table.columns.map((col) => col.columnId),
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},
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],
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},
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previewIcon: LensIconChartDatatable,
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// tables are hidden from suggestion bar, but used for drag & drop and chart switching
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hide: true,
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},
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];
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},
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getConfiguration({ state, frame, layerId }) {
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const { sortedColumns, datasource } =
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getDataSourceAndSortedColumns(state, frame.datasourceLayers, layerId) || {};
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if (!sortedColumns) {
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return { groups: [] };
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}
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return {
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groups: [
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{
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groupId: 'columns',
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groupLabel: i18n.translate('xpack.lens.datatable.breakdown', {
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defaultMessage: 'Break down by',
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}),
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layerId: state.layers[0].layerId,
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accessors: sortedColumns.filter(
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(c) => datasource!.getOperationForColumnId(c)?.isBucketed
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),
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supportsMoreColumns: true,
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filterOperations: (op) => op.isBucketed,
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dataTestSubj: 'lnsDatatable_column',
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},
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{
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groupId: 'metrics',
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groupLabel: i18n.translate('xpack.lens.datatable.metrics', {
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defaultMessage: 'Metrics',
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}),
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layerId: state.layers[0].layerId,
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accessors: sortedColumns.filter(
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(c) => !datasource!.getOperationForColumnId(c)?.isBucketed
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),
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supportsMoreColumns: true,
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filterOperations: (op) => !op.isBucketed,
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required: true,
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dataTestSubj: 'lnsDatatable_metrics',
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},
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],
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};
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},
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setDimension({ prevState, layerId, columnId }) {
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return {
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...prevState,
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layers: prevState.layers.map((l) => {
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if (l.layerId !== layerId || l.columns.includes(columnId)) {
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return l;
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}
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return { ...l, columns: [...l.columns, columnId] };
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}),
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};
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},
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removeDimension({ prevState, layerId, columnId }) {
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return {
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...prevState,
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layers: prevState.layers.map((l) =>
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l.layerId === layerId
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? {
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...l,
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columns: l.columns.filter((c) => c !== columnId),
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}
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: l
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),
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};
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},
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toExpression(state, datasourceLayers, { title, description } = {}): Ast | null {
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const { sortedColumns, datasource } =
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getDataSourceAndSortedColumns(state, datasourceLayers, state.layers[0].layerId) || {};
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if (
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sortedColumns?.length &&
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sortedColumns.filter((c) => !datasource!.getOperationForColumnId(c)?.isBucketed).length === 0
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) {
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return null;
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}
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const operations = sortedColumns!
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.map((columnId) => ({ columnId, operation: datasource!.getOperationForColumnId(columnId) }))
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.filter((o): o is { columnId: string; operation: Operation } => !!o.operation);
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return {
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type: 'expression',
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chain: [
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{
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type: 'function',
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function: 'lens_datatable',
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arguments: {
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title: [title || ''],
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description: [description || ''],
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columns: [
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{
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type: 'expression',
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chain: [
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{
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type: 'function',
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function: 'lens_datatable_columns',
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arguments: {
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columnIds: operations.map((o) => o.columnId),
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},
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},
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],
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},
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],
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},
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},
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],
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};
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},
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getErrorMessages(state, frame) {
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return undefined;
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},
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};
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function getDataSourceAndSortedColumns(
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state: DatatableVisualizationState,
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datasourceLayers: Record<string, DatasourcePublicAPI>,
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layerId: string
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) {
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const layer = state.layers.find((l: LayerState) => l.layerId === layerId);
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if (!layer) {
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return undefined;
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}
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const datasource = datasourceLayers[layer.layerId];
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const originalOrder = datasource.getTableSpec().map(({ columnId }) => columnId);
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// When we add a column it could be empty, and therefore have no order
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const sortedColumns = Array.from(new Set(originalOrder.concat(layer.columns)));
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return { datasource, sortedColumns };
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}
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