refactor(stage9): 后端业务域目录形状统一
- 每个域现在都是 src/server/routes/<domain>/ 目录：
vehicles/routes.ts（原 routes/vehicles.ts）、vehicle-heatmap/{routes,model}.ts、
hydrogen-heatmap/{routes,model}.ts、ele/routes.ts、feedback/routes.ts。
- 命名约定：index.ts 是聚合器（挂子路由），routes.ts 是叶子路由。mileage/energy/
scheduling 保持 index.ts 聚合，其余统一为 routes.ts。
- 纯移动与改名，未改动任何 SQL、参数顺序、路由挂载前缀或处理器逻辑。
import 改写由一次性 codemod 完成；vehicles/repository.test.ts 读取的源码路径同步更新。
- docs/ARCHITECTURE.md 补充"后端业务域形状"表，并如实标注 ele / feedback 尚未拆出
repository（这两个域缺 SQL 指纹测试，建议先补测试再拆）。
lint / test(139) / build 全绿，可达性 0 未引用文件。
This commit is contained in:
dsh-agent
@@ -0,0 +1,152 @@
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import assert from 'node:assert/strict';
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import test from 'node:test';
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import {
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buildVehicleGrid,
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buildVehicleRanking,
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daysInclusive,
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filterVehicleRecordsByRadius,
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haversineKm,
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parseNearbyQuery,
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parseVehicleHeatmapQuery,
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summarizeVehicleRecords,
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vehicleGridPrecision,
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type VehicleHeatmapRecord,
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} from './model.js';
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import { recentDayRange } from '../../../shared/date-range.js';
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// 默认区间是"近 30 天"滚动窗口，注入固定时钟让断言可复现。
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const NOW = new Date('2026-07-13T12:00:00');
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const FALLBACK = recentDayRange(30, NOW);
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function record(overrides: Partial<VehicleHeatmapRecord> = {}): VehicleHeatmapRecord {
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return {
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date: '2026-07-01',
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vin: 'VIN-A',
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plate: '粤A00001',
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time: '2026-07-01 08:00:00',
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longitude: 120,
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latitude: 30,
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source: 'test',
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sourceRecordId: '1',
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...overrides,
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};
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}
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test('车辆热力图查询默认使用近 30 天滚动窗口，并保留原有字符串处理规则', () => {
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assert.deepEqual(parseVehicleHeatmapQuery({}, NOW), {
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startDate: FALLBACK.start,
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endDate: FALLBACK.end,
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query: '',
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batchModel: '',
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metric: 'locations',
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});
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assert.deepEqual(parseVehicleHeatmapQuery({
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startDate: '2026-06-01',
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endDate: 'invalid',
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query: ' 粤A ',
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batchModel: ' 190台冷链 ',
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metric: 'vehicles',
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}, NOW), {
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startDate: '2026-06-01',
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endDate: FALLBACK.end,
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query: ' 粤A ',
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batchModel: '190台冷链',
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metric: 'vehicles',
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});
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});
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test('附近查询继续沿用经纬度 Number 语义和 5 至 200 公里半径限制', () => {
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assert.deepEqual(parseNearbyQuery({ lng: '', lat: '0', radiusKm: '0' }), {
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center: { lng: 0, lat: 0 },
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radiusKm: 50,
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});
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assert.deepEqual(parseNearbyQuery({ lng: '120', lat: '30', radiusKm: '-1' }), {
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center: { lng: 120, lat: 30 },
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radiusKm: 5,
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});
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assert.equal(parseNearbyQuery({ lng: '120', lat: '30', radiusKm: '500' }).radiusKm, 200);
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assert.equal(parseNearbyQuery({ lng: 'bad', lat: '30' }).center, null);
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});
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test('网格精度继续按含首尾天数和筛选条件决定', () => {
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assert.equal(daysInclusive('2026-07-01', '2026-07-14'), 14);
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assert.equal(daysInclusive('2026-07-14', '2026-07-01'), 0);
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assert.equal(vehicleGridPrecision('2026-07-01', '2026-07-14', '', ''), 3);
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assert.equal(vehicleGridPrecision('2026-07-01', '2026-07-15', '', ''), 2);
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assert.equal(vehicleGridPrecision('2026-07-01', '2026-07-15', ' ', ''), 3);
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});
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test('车辆网格继续区分位置次数和去重车辆数并保留插入顺序', () => {
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const records = [
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record({ vin: 'VIN-A', longitude: 120.1231, latitude: 30.9878 }),
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record({ vin: 'VIN-A', longitude: 120.1232, latitude: 30.9879 }),
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record({ vin: 'VIN-B', longitude: 120.1233, latitude: 30.9877 }),
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record({ vin: 'VIN-C', longitude: 121, latitude: 31 }),
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];
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assert.deepEqual(buildVehicleGrid(records, 'locations', 3), {
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points: [
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{ lng: 120.123, lat: 30.988, count: 3 },
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{ lng: 121, lat: 31, count: 1 },
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],
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max: 3,
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});
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assert.deepEqual(buildVehicleGrid(records, 'vehicles', 3), {
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points: [
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{ lng: 120.123, lat: 30.988, count: 2 },
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{ lng: 121, lat: 31, count: 1 },
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],
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max: 2,
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});
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assert.deepEqual(buildVehicleGrid([], 'locations', 2), { points: [], max: 1 });
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});
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test('车辆排名继续按记录数、车牌排序并保留首末出现时间', () => {
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const records = [
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record({ vin: 'VIN-B', plate: '', time: '2026-07-02 10:00:00' }),
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record({ vin: 'VIN-A', plate: '粤A00001', time: '2026-07-02 09:00:00' }),
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record({ vin: 'VIN-B', plate: '粤B00001', time: '2026-07-01 08:00:00' }),
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record({ vin: 'VIN-A', plate: '粤A00001', time: '2026-07-03 11:00:00' }),
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];
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assert.deepEqual(buildVehicleRanking(records), [
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{
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vin: 'VIN-A',
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plateNumber: '粤A00001',
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locationCount: 2,
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firstSeen: '2026-07-02 09:00:00',
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lastSeen: '2026-07-03 11:00:00',
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},
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{
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vin: 'VIN-B',
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plateNumber: '粤B00001',
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locationCount: 2,
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firstSeen: '2026-07-01 08:00:00',
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lastSeen: '2026-07-02 10:00:00',
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},
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]);
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assert.equal(buildVehicleRanking(records, 1).length, 1);
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});
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test('车辆统计和附近筛选继续使用 VIN、自然日去重及 Haversine 距离', () => {
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const records = [
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record({ vin: 'VIN-A', date: '2026-07-01' }),
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record({ vin: 'VIN-A', date: '2026-07-02', longitude: 120.01 }),
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record({ vin: 'VIN-B', date: '2026-07-02', longitude: 121 }),
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];
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assert.deepEqual(summarizeVehicleRecords(records), {
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locationCount: 3,
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vehicleCount: 2,
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dayCount: 2,
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});
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assert.equal(haversineKm(120, 30, 120, 30), 0);
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assert.ok(Math.abs(haversineKm(0, 0, 0, 1) - 111.195) < 0.01);
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assert.deepEqual(
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filterVehicleRecordsByRadius(records, { lng: 120, lat: 30 }, 5).map(({ vin, date }) => ({ vin, date })),
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[
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{ vin: 'VIN-A', date: '2026-07-01' },
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{ vin: 'VIN-A', date: '2026-07-02' },
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],
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);
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});
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@@ -0,0 +1,171 @@
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import { recentDayRange } from '../../../shared/date-range.js';
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export type VehicleHeatmapMetric = 'locations' | 'vehicles';
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export type VehicleHeatmapRecord = {
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date: string;
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vin: string;
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plate: string;
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time: string;
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longitude: number;
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latitude: number;
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source: string;
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sourceRecordId: string;
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};
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export type VehicleRank = {
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vin: string;
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plateNumber: string;
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locationCount: number;
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firstSeen: string;
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lastSeen: string;
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};
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type VehicleHeatmapQueryInput = {
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startDate?: string;
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endDate?: string;
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query?: string;
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batchModel?: string;
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metric?: string;
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};
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type NearbyQueryInput = {
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lng?: string;
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lat?: string;
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radiusKm?: string;
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};
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/**
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* 未显式传日期时的兜底窗口。
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* 此前写死为 2026-01-01 ~ 2026-07-13，会让默认查询永久指向一段历史数据；
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* 现改为"近 N 天"滚动窗口。
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*/
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export const HEATMAP_DEFAULT_WINDOW_DAYS = 30;
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function isDate(value: string | undefined): value is string {
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return Boolean(value && /^\d{4}-\d{2}-\d{2}$/.test(value));
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}
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export function parseVehicleHeatmapQuery(input: VehicleHeatmapQueryInput, now: Date = new Date()) {
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const fallback = recentDayRange(HEATMAP_DEFAULT_WINDOW_DAYS, now);
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return {
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startDate: isDate(input.startDate) ? input.startDate : fallback.start,
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endDate: isDate(input.endDate) ? input.endDate : fallback.end,
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query: input.query || '',
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batchModel: (input.batchModel || '').trim(),
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metric: input.metric === 'vehicles' ? 'vehicles' as const : 'locations' as const,
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};
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}
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export function parseNearbyQuery(input: NearbyQueryInput) {
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const longitude = Number(input.lng);
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const latitude = Number(input.lat);
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return {
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center: Number.isFinite(longitude) && Number.isFinite(latitude)
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? { lng: longitude, lat: latitude }
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: null,
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radiusKm: Math.min(200, Math.max(5, Number(input.radiusKm) || 50)),
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};
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}
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export function daysInclusive(startDate: string, endDate: string): number {
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const start = Date.parse(`${startDate}T00:00:00+08:00`);
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const end = Date.parse(`${endDate}T00:00:00+08:00`);
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return Math.max(0, Math.floor((end - start) / 86_400_000) + 1);
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}
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export function vehicleGridPrecision(
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startDate: string,
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endDate: string,
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query: string,
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batchModel: string,
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): number {
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return daysInclusive(startDate, endDate) <= 14 || Boolean(query || batchModel) ? 3 : 2;
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}
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export function buildVehicleGrid(
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records: VehicleHeatmapRecord[],
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metric: VehicleHeatmapMetric,
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precision: number,
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) {
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const grid = new Map<string, { lng: number; lat: number; count: number; vins?: Set<string> }>();
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for (const record of records) {
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const lng = Number(record.longitude.toFixed(precision));
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const lat = Number(record.latitude.toFixed(precision));
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const key = `${lng},${lat}`;
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let point = grid.get(key);
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if (!point) {
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point = { lng, lat, count: 0, vins: metric === 'vehicles' ? new Set<string>() : undefined };
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grid.set(key, point);
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}
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if (point.vins) {
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point.vins.add(record.vin);
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point.count = point.vins.size;
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} else {
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point.count += 1;
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}
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}
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const points = [...grid.values()].map(({ lng, lat, count }) => ({ lng, lat, count }));
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let max = 1;
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for (const point of points) max = Math.max(max, point.count);
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return { points, max };
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}
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export function buildVehicleRanking(records: VehicleHeatmapRecord[], limit = 10): VehicleRank[] {
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const vehicles = new Map<string, VehicleRank>();
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for (const record of records) {
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const current = vehicles.get(record.vin);
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if (!current) {
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vehicles.set(record.vin, {
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vin: record.vin,
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plateNumber: record.plate,
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locationCount: 1,
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firstSeen: record.time,
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lastSeen: record.time,
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});
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continue;
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}
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current.locationCount += 1;
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if (record.time < current.firstSeen) current.firstSeen = record.time;
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if (record.time > current.lastSeen) current.lastSeen = record.time;
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if (!current.plateNumber && record.plate) current.plateNumber = record.plate;
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}
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return [...vehicles.values()]
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.sort((left, right) => right.locationCount - left.locationCount
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|| left.plateNumber.localeCompare(right.plateNumber, 'zh-CN'))
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.slice(0, limit);
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}
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export function summarizeVehicleRecords(records: VehicleHeatmapRecord[]) {
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return {
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locationCount: records.length,
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vehicleCount: new Set(records.map((record) => record.vin)).size,
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dayCount: new Set(records.map((record) => record.date)).size,
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};
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}
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export function haversineKm(
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leftLng: number,
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leftLat: number,
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rightLng: number,
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rightLat: number,
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): number {
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const radians = (degrees: number) => degrees * Math.PI / 180;
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const earthRadius = 6371;
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const dLat = radians(rightLat - leftLat);
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const dLng = radians(rightLng - leftLng);
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const a = Math.sin(dLat / 2) ** 2
|
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+ Math.cos(radians(leftLat)) * Math.cos(radians(rightLat)) * Math.sin(dLng / 2) ** 2;
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return earthRadius * 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));
|
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}
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|
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export function filterVehicleRecordsByRadius(
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records: VehicleHeatmapRecord[],
|
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center: { lng: number; lat: number },
|
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radiusKm: number,
|
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): VehicleHeatmapRecord[] {
|
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return records.filter((record) => (
|
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haversineKm(center.lng, center.lat, record.longitude, record.latitude) <= radiusKm
|
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));
|
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}
|
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@@ -0,0 +1,234 @@
|
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import { Hono } from 'hono';
|
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import pool from '../../db/mysql.js';
|
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import heatmapPool from '../../db/heatmap.js';
|
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import { getCache } from '../mileage/cache.js';
|
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import {
|
||||
buildVehicleGrid,
|
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buildVehicleRanking,
|
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filterVehicleRecordsByRadius,
|
||||
parseNearbyQuery,
|
||||
parseVehicleHeatmapQuery,
|
||||
summarizeVehicleRecords,
|
||||
vehicleGridPrecision,
|
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type VehicleHeatmapRecord,
|
||||
} from './model.js';
|
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|
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type MetaRow = {
|
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start_date: string;
|
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end_date: string;
|
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location_count: string;
|
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vehicle_count: string;
|
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day_count: string;
|
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total_location_count: string;
|
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excluded_location_count: string;
|
||||
outside_mainland_count: string;
|
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tibet_count: string;
|
||||
};
|
||||
|
||||
type VehicleOptionRow = {
|
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vin: string;
|
||||
plate_number: string;
|
||||
};
|
||||
|
||||
type RecordRow = {
|
||||
date: string;
|
||||
vin: string;
|
||||
plate: string;
|
||||
time: string;
|
||||
longitude: number;
|
||||
latitude: number;
|
||||
source: string;
|
||||
source_record_id: string;
|
||||
};
|
||||
|
||||
type BatchModelRow = {
|
||||
target_name: string;
|
||||
plate_number: string;
|
||||
};
|
||||
|
||||
async function loadBatchModelPlates(): Promise<Map<string, Set<string>>> {
|
||||
const cached = getCache()?.targetPlatesMap;
|
||||
if (cached?.size) return cached;
|
||||
|
||||
try {
|
||||
const [rows] = await pool.execute(`
|
||||
select t.target_name, v.plate_number
|
||||
from lingniu_prod.tab_mileage_assessment_target t
|
||||
join lingniu_prod.tab_mileage_assessment_vehicle v
|
||||
on v.target_id = t.id and v.is_deleted = 0
|
||||
where t.is_deleted = 0
|
||||
`) as [BatchModelRow[], unknown];
|
||||
const result = new Map<string, Set<string>>();
|
||||
for (const row of rows) {
|
||||
const plates = result.get(row.target_name) || new Set<string>();
|
||||
plates.add(row.plate_number);
|
||||
result.set(row.target_name, plates);
|
||||
}
|
||||
return result;
|
||||
} catch (error) {
|
||||
console.error('[vehicle-heatmap] batch model lookup failed', error);
|
||||
return new Map();
|
||||
}
|
||||
}
|
||||
|
||||
async function loadRecords(
|
||||
startDate: string,
|
||||
endDate: string,
|
||||
query: string,
|
||||
batchModel: string,
|
||||
): Promise<VehicleHeatmapRecord[]> {
|
||||
let batchPlates: string[] = [];
|
||||
if (batchModel) {
|
||||
const modelPlates = await loadBatchModelPlates();
|
||||
batchPlates = [...(modelPlates.get(batchModel) || [])];
|
||||
if (batchPlates.length === 0) return [];
|
||||
}
|
||||
|
||||
const result = await heatmapPool.query<RecordRow>(`
|
||||
select
|
||||
to_char(stat_date, 'YYYY-MM-DD') as date,
|
||||
vin,
|
||||
plate_number as plate,
|
||||
to_char(first_event_time at time zone 'Asia/Shanghai',
|
||||
'YYYY-MM-DD HH24:MI:SS') as time,
|
||||
longitude,
|
||||
latitude,
|
||||
source_name as source,
|
||||
coalesce(source_record_id::text, '') as source_record_id
|
||||
from analytics.vehicle_daily_first_location
|
||||
where stat_date between $1::date and $2::date
|
||||
and is_heatmap_eligible
|
||||
and ($4::boolean = false or plate_number = any($5::text[]))
|
||||
and (
|
||||
$3 = ''
|
||||
or upper(vin) like '%' || upper($3) || '%'
|
||||
or upper(plate_number) like '%' || upper($3) || '%'
|
||||
)
|
||||
order by stat_date, vin
|
||||
`, [startDate, endDate, query.trim(), Boolean(batchModel), batchPlates]);
|
||||
|
||||
return result.rows.map((row) => ({
|
||||
...row,
|
||||
longitude: Number(row.longitude),
|
||||
latitude: Number(row.latitude),
|
||||
sourceRecordId: row.source_record_id,
|
||||
}));
|
||||
}
|
||||
|
||||
const router = new Hono();
|
||||
|
||||
router.get('/config', (c) => {
|
||||
const key = process.env.AMAP_WEB_KEY;
|
||||
const securityCode = process.env.AMAP_SECURITY_JS_CODE;
|
||||
if (!key || !securityCode) {
|
||||
return c.json({ error: '高德地图配置缺失' }, 503);
|
||||
}
|
||||
return c.json({ key, securityCode });
|
||||
});
|
||||
|
||||
router.get('/meta', async (c) => {
|
||||
const [metaResult, vehiclesResult, batchModelPlates] = await Promise.all([
|
||||
heatmapPool.query<MetaRow>(`
|
||||
select
|
||||
to_char(min(stat_date) filter (where is_heatmap_eligible), 'YYYY-MM-DD') as start_date,
|
||||
to_char(max(stat_date) filter (where is_heatmap_eligible), 'YYYY-MM-DD') as end_date,
|
||||
count(*) filter (where is_heatmap_eligible)::text as location_count,
|
||||
count(distinct vin) filter (where is_heatmap_eligible)::text as vehicle_count,
|
||||
count(distinct stat_date) filter (where is_heatmap_eligible)::text as day_count,
|
||||
count(*)::text as total_location_count,
|
||||
count(*) filter (where not is_heatmap_eligible)::text as excluded_location_count,
|
||||
count(*) filter (where exclusion_reason = 'outside_mainland_china')::text as outside_mainland_count,
|
||||
count(*) filter (where exclusion_reason = 'tibet')::text as tibet_count
|
||||
from analytics.vehicle_daily_first_location
|
||||
`),
|
||||
heatmapPool.query<VehicleOptionRow>(`
|
||||
select distinct on (vin) vin, plate_number
|
||||
from analytics.vehicle_daily_first_location
|
||||
where is_heatmap_eligible
|
||||
order by vin, stat_date desc
|
||||
`),
|
||||
loadBatchModelPlates(),
|
||||
]);
|
||||
const meta = metaResult.rows[0];
|
||||
const vehicles = vehiclesResult.rows
|
||||
.map(({ vin, plate_number: plateNumber }) => ({ vin, plateNumber }))
|
||||
.sort((left, right) => left.plateNumber.localeCompare(right.plateNumber, 'zh-CN'));
|
||||
return c.json({
|
||||
startDate: meta.start_date,
|
||||
endDate: meta.end_date,
|
||||
locationCount: Number(meta.location_count),
|
||||
vehicleCount: Number(meta.vehicle_count),
|
||||
dayCount: Number(meta.day_count),
|
||||
totalLocationCount: Number(meta.total_location_count),
|
||||
excludedLocationCount: Number(meta.excluded_location_count),
|
||||
outsideMainlandCount: Number(meta.outside_mainland_count),
|
||||
tibetCount: Number(meta.tibet_count),
|
||||
batchModels: [...batchModelPlates.keys()].sort((left, right) => left.localeCompare(right, 'zh-CN')),
|
||||
vehicles,
|
||||
});
|
||||
});
|
||||
|
||||
router.get('/points', async (c) => {
|
||||
const {
|
||||
startDate,
|
||||
endDate,
|
||||
query,
|
||||
batchModel,
|
||||
metric,
|
||||
} = parseVehicleHeatmapQuery({
|
||||
startDate: c.req.query('startDate'),
|
||||
endDate: c.req.query('endDate'),
|
||||
query: c.req.query('query'),
|
||||
batchModel: c.req.query('batchModel'),
|
||||
metric: c.req.query('metric'),
|
||||
});
|
||||
if (startDate > endDate) return c.json({ error: '开始日期不能晚于结束日期' }, 400);
|
||||
|
||||
const records = await loadRecords(startDate, endDate, query, batchModel);
|
||||
const precision = vehicleGridPrecision(startDate, endDate, query, batchModel);
|
||||
const { points, max } = buildVehicleGrid(records, metric, precision);
|
||||
const summary = summarizeVehicleRecords(records);
|
||||
|
||||
return c.json({
|
||||
startDate,
|
||||
endDate,
|
||||
metric,
|
||||
locationCount: summary.locationCount,
|
||||
vehicleCount: summary.vehicleCount,
|
||||
dayCount: summary.dayCount,
|
||||
points,
|
||||
max,
|
||||
topVehicles: buildVehicleRanking(records),
|
||||
});
|
||||
});
|
||||
|
||||
router.get('/nearby', async (c) => {
|
||||
const { center, radiusKm } = parseNearbyQuery({
|
||||
lng: c.req.query('lng'),
|
||||
lat: c.req.query('lat'),
|
||||
radiusKm: c.req.query('radiusKm'),
|
||||
});
|
||||
if (!center) {
|
||||
return c.json({ error: '经纬度参数无效' }, 400);
|
||||
}
|
||||
|
||||
const { startDate, endDate, query, batchModel } = parseVehicleHeatmapQuery({
|
||||
startDate: c.req.query('startDate'),
|
||||
endDate: c.req.query('endDate'),
|
||||
query: c.req.query('query'),
|
||||
batchModel: c.req.query('batchModel'),
|
||||
});
|
||||
const records = await loadRecords(startDate, endDate, query, batchModel);
|
||||
const nearby = filterVehicleRecordsByRadius(records, center, radiusKm);
|
||||
const summary = summarizeVehicleRecords(nearby);
|
||||
|
||||
return c.json({
|
||||
center,
|
||||
radiusKm,
|
||||
locationCount: summary.locationCount,
|
||||
vehicleCount: summary.vehicleCount,
|
||||
topVehicles: buildVehicleRanking(nearby),
|
||||
});
|
||||
});
|
||||
|
||||
export default router;
|
||||
Reference in New Issue
Block a user