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174 lines
5.2 KiB
TypeScript
174 lines
5.2 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 { buildQueryContext } from '@superset-ui/core';
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import * as queryModule from '../../src/query/normalizeTimeColumn';
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describe('buildQueryContext', () => {
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it('should build datasource for table sources and apply defaults', () => {
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const queryContext = buildQueryContext({
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datasource: '5__table',
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granularity_sqla: 'ds',
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viz_type: 'table',
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});
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expect(queryContext.datasource.id).toBe(5);
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expect(queryContext.datasource.type).toBe('table');
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expect(queryContext.force).toBe(false);
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expect(queryContext.result_format).toBe('json');
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expect(queryContext.result_type).toBe('full');
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});
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it('should build datasource for table sources with columns', () => {
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const queryContext = buildQueryContext(
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{
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datasource: '5__table',
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granularity_sqla: 'ds',
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viz_type: 'table',
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source: 'source_column',
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source_category: 'source_category_column',
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target: 'target_column',
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target_category: 'target_category_column',
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},
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{
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queryFields: {
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source: 'columns',
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source_category: 'columns',
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target: 'columns',
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target_category: 'columns',
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},
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},
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);
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expect(queryContext.datasource.id).toBe(5);
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expect(queryContext.datasource.type).toBe('table');
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expect(queryContext.force).toBe(false);
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expect(queryContext.result_format).toBe('json');
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expect(queryContext.result_type).toBe('full');
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expect(queryContext.queries).toEqual(
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expect.arrayContaining([
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expect.objectContaining({
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columns: [
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'source_column',
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'source_category_column',
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'target_column',
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'target_category_column',
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],
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}),
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]),
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);
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});
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it('should build datasource for table sources and process with custom function', () => {
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const queryContext = buildQueryContext(
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{
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datasource: '5__table',
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granularity_sqla: 'ds',
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viz_type: 'table',
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source: 'source_column',
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source_category: 'source_category_column',
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target: 'target_column',
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target_category: 'target_category_column',
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},
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function addExtraColumn(queryObject) {
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return [{ ...queryObject, columns: ['dummy_column'] }];
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},
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);
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expect(queryContext.datasource.id).toBe(5);
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expect(queryContext.datasource.type).toBe('table');
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expect(queryContext.force).toBe(false);
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expect(queryContext.result_format).toBe('json');
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expect(queryContext.result_type).toBe('full');
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expect(queryContext.queries).toEqual(
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expect.arrayContaining([
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expect.objectContaining({
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columns: ['dummy_column'],
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}),
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]),
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);
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});
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it('should remove undefined value in post_processing', () => {
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const queryContext = buildQueryContext(
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{
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datasource: '5__table',
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viz_type: 'table',
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},
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() => [
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{
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post_processing: [
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undefined,
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undefined,
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{
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operation: 'flatten',
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},
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undefined,
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],
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},
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],
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);
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expect(queryContext.queries[0].post_processing).toEqual([
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{
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operation: 'flatten',
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},
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]);
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});
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it('should call normalizeTimeColumn if GENERIC_CHART_AXES is enabled and has x_axis', () => {
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// @ts-ignore
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const spy = jest.spyOn(window, 'window', 'get').mockImplementation(() => ({
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featureFlags: {
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GENERIC_CHART_AXES: true,
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},
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}));
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const spyNormalizeTimeColumn = jest.spyOn(
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queryModule,
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'normalizeTimeColumn',
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);
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buildQueryContext(
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{
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datasource: '5__table',
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viz_type: 'table',
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x_axis: 'axis',
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},
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() => [{}],
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);
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expect(spyNormalizeTimeColumn).toBeCalled();
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spy.mockRestore();
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spyNormalizeTimeColumn.mockRestore();
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});
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it("shouldn't call normalizeTimeColumn if GENERIC_CHART_AXES is disabled", () => {
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// @ts-ignore
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const spy = jest.spyOn(window, 'window', 'get').mockImplementation(() => ({
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featureFlags: {
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GENERIC_CHART_AXES: false,
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},
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}));
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const spyNormalizeTimeColumn = jest.spyOn(
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queryModule,
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'normalizeTimeColumn',
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);
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buildQueryContext(
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{
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datasource: '5__table',
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viz_type: 'table',
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},
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() => [{}],
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);
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expect(spyNormalizeTimeColumn).not.toBeCalled();
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spy.mockRestore();
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spyNormalizeTimeColumn.mockRestore();
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});
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});
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