ln-bi/src/server/routes/vehicle-heatmap.ts

import { Hono } from 'hono';
import pool from '../db.js';
import heatmapPool from '../heatmap-db.js';
import { getCache } from './mileage/cache.js';
import {
  buildVehicleGrid,
  buildVehicleRanking,
  filterVehicleRecordsByRadius,
  parseNearbyQuery,
  parseVehicleHeatmapQuery,
  summarizeVehicleRecords,
  vehicleGridPrecision,
  type VehicleHeatmapRecord,
} from './vehicle-heatmap-model.js';

type MetaRow = {
  start_date: string;
  end_date: string;
  location_count: string;
  vehicle_count: string;
  day_count: string;
  total_location_count: string;
  excluded_location_count: string;
  outside_mainland_count: string;
  tibet_count: string;
};

type VehicleOptionRow = {
  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;