package com.ycl.platform.service.impl;

import com.baomidou.mybatisplus.core.metadata.IPage;
import com.baomidou.mybatisplus.extension.conditions.query.LambdaQueryChainWrapper;
import com.github.pagehelper.Page;
import com.github.pagehelper.PageHelper;
import com.mongodb.client.AggregateIterable;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import com.ycl.platform.domain.entity.*;
import com.ycl.platform.domain.query.DataCenterQuery;
import com.ycl.platform.domain.result.HK.*;
import com.ycl.platform.domain.result.UY.*;
import com.ycl.platform.mapper.ImageResourceSecurityDetailMapper;
import com.ycl.platform.mapper.YwPointMapper;
import com.ycl.platform.service.*;
import com.ycl.system.Result;
import com.ycl.system.page.PageUtil;
import com.ycl.utils.DateUtils;
import com.ycl.utils.MongoUtil;
import constant.CheckConstants;
import lombok.RequiredArgsConstructor;
import org.apache.commons.collections.CollectionUtils;
import org.bson.Document;
import org.springframework.data.domain.Sort;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.query.Criteria;
import org.springframework.data.mongodb.core.query.Query;
import org.springframework.data.mongodb.core.query.TextCriteria;
import org.springframework.stereotype.Service;

import java.math.BigDecimal;
import java.math.RoundingMode;
import java.text.DecimalFormat;
import java.util.*;
import java.util.stream.Collectors;

/**
 * 数据中心接口
 *
 * @author：xp
 * @date：2024/8/2 11:07
 */
@Service
@RequiredArgsConstructor
public class DataCenterServiceImpl implements DataCenterService {

    private final MongoTemplate mongoTemplate;
    private final ImageResourceSecurityDetailMapper securityDetailMapper;
    private final YwPointMapper pointMapper;
    private final ICheckIndexVideoService checkIndexVideoService;
    private final ICheckIndexCarService checkIndexCarService;
    private final ICheckIndexFaceService checkIndexFaceService;


    private final static String TIME_FIELD = "mongoCreateTime";

    private static DecimalFormat DF = new DecimalFormat("#.####");

    /**
     * 视频：点位在线率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoPointOnlineRate(DataCenterQuery params) {
        // 生成查询
        List<String> likeFileds = Arrays.asList("arealayerName", "ipAddr", "deviceName", "deviceId");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        // 先查总数再分页
        long total = mongoTemplate.count(query, VideoOnlineResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<VideoOnlineResult> resultList = mongoTemplate.find(query, VideoOnlineResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_online");
        long distinctCount = collection.distinct("deviceId", String.class).into(new ArrayList<>()).size();
        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getSiteOnline)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getSiteOnline).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(distinctCount + "",this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：部级点位在线率
     *
     * @param params
     * @return
     */
    @Override
    public Result deptVideoPointOnlineRate(DataCenterQuery params) {

        List<String> likeFileds = Arrays.asList("arealayerName", "ipAddr", "deviceName", "deviceId");
        // 生成查询
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, 1);

        // 先查总数再分页
        long total = mongoTemplate.count(query, VideoOnlineResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<VideoOnlineResult> resultList = mongoTemplate.find(query, VideoOnlineResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_online");
        List<Document> dList = new ArrayList<>(2);
        dList.add(new Document("deptTag", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document filter = new Document("$and", dList);
        // 构建聚合管道
        List<Document> pipeline = Arrays.asList(
                // 只要部级的
                new Document("$match", filter),
                // $group 去重
                new Document("$group", new Document("_id", "$deviceId")),
                new Document("$count", "uniqueDeviceIds")
        );
        // 执行聚合查询并获取结果
        AggregateIterable<Document> result = collection.aggregate(pipeline);
        Integer uniqueDeviceIdCount = 0;
        for (Document doc : result) {
            uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
            break; // 不需要继续遍历，因为 $count 只会产生一个结果
        }
        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getMinistrySiteOnline)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getMinistrySiteOnline).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(uniqueDeviceIdCount + "", this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：重点点位在线率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoImportantPointOnlineRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("arealayerName", "ipAddr", "deviceName", "deviceId");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, 3);

        long total = mongoTemplate.count(query, VideoOnlineResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<VideoOnlineResult> resultList = mongoTemplate.find(query, VideoOnlineResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_online");

        List<Document> dList = new ArrayList<>(2);
        dList.add(new Document("importantTag", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document filter = new Document("$and", dList);
        // 构建聚合管道
        List<Document> pipeline = Arrays.asList(
                new Document("$match", filter),
                // $group 去重
                new Document("$group", new Document("_id", "$deviceId")),
                new Document("$count", "uniqueDeviceIds")
        );
        // 执行聚合查询并获取结果
        AggregateIterable<Document> result = collection.aggregate(pipeline);
        Integer uniqueDeviceIdCount = 0;
        for (Document doc : result) {
            uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
            break; // 不需要继续遍历，因为 $count 只会产生一个结果
        }

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getKeySiteOnline)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getKeySiteOnline).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(uniqueDeviceIdCount + "", this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：重点指挥图像在线率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoImportantPointImageOnlineRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("arealayerName", "ipAddr", "deviceName", "deviceId");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, 4);

        long total = mongoTemplate.count(query, VideoOnlineResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<VideoOnlineResult> resultList = mongoTemplate.find(query, VideoOnlineResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_online");

        List<Document> dList = new ArrayList<>(2);
        dList.add(new Document("importantCommandImageTag", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document filter = new Document("$and", dList);
        // 构建聚合管道
        List<Document> pipeline = Arrays.asList(
                new Document("$match", filter),
                // $group 去重
                new Document("$group", new Document("_id", "$deviceId")),
                new Document("$count", "uniqueDeviceIds")
        );
        // 执行聚合查询并获取结果
        AggregateIterable<Document> result = collection.aggregate(pipeline);
        Integer uniqueDeviceIdCount = 0;
        for (Document doc : result) {
            uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
            break; // 不需要继续遍历，因为 $count 只会产生一个结果
        }

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getKeyCommandImageOnline)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getKeyCommandImageOnline).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(uniqueDeviceIdCount + "", this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：一机一档注册率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoOneMachineDocumentRegister(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("ip.showValue", "name.showValue", "serialNumber.showValue");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, MonitorQualifyResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<MonitorQualifyResult> resultList = mongoTemplate.find(query, MonitorQualifyResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_monitor_qualify");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("ip.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("macdz.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("latitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("longitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$serialNumber.showValue")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getMonitorRegistration)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getMonitorRegistration).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：一机一档合格率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoOneMachineDocumentQualified(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("ip.showValue", "name.showValue", "serialNumber.showValue");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, MonitorQualifyResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<MonitorQualifyResult> resultList = mongoTemplate.find(query, MonitorQualifyResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_monitor_qualify");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("ip.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("macdz.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("latitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("longitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$serialNumber.showValue")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getMonitorQualification)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getMonitorQualification).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：档案考核比
     *
     * @param params
     * @return
     */
    @Override
    public Result videoAssessmentFileRatio(DataCenterQuery params) {
        // TODO 新增一张表记录每次的档案考核
        List<String> likeFileds = Arrays.asList("ip.showValue", "name.showValue", "serialNumber.showValue");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, MonitorQualifyResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<MonitorQualifyResult> resultList = mongoTemplate.find(query, MonitorQualifyResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_monitor_qualify");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("ip.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("macdz.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("latitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("longitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$serialNumber.showValue")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        rList.add("0%");
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：录像可用率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoAvailabilityRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("deviceId", "deviceName");
        Query query = MongoUtil.getQuery(params,"createTime", likeFileds, null);

        long total = mongoTemplate.count(query, RecordMetaDSumResult.class);
        MongoUtil.setPage(query, params, "createTime");
        List<RecordMetaDSumResult> resultList = mongoTemplate.find(query, RecordMetaDSumResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_record_meta_d_sum");
        List<Integer> status = Arrays.asList(1, 0, -1);
        List<String> resultCount = status.stream().map(item -> {
            List<Document> dList = new ArrayList<>(2);
            dList.add(new Document("recordStatus", new Document("$eq", item)));
            if (params.getDataType().equals(1)) {
                dList.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
            }
            Document filter = new Document("$and", dList);
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$deviceId")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getVideoAvailable)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getVideoAvailable).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        resultCount.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", resultCount);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：部级录像可用率
     *
     * @param params
     * @return
     */
    @Override
    public Result deptVideoAvailabilityRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("deviceId", "deviceName");
        Query query = MongoUtil.getQuery(params,"createTime", likeFileds, 1);

        long total = mongoTemplate.count(query, RecordMetaDSumResult.class);
        MongoUtil.setPage(query, params, "createTime");
        List<RecordMetaDSumResult> resultList = mongoTemplate.find(query, RecordMetaDSumResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_record_meta_d_sum");
        List<Integer> status = Arrays.asList(1, 0, -1);
        List<String> resultCount = status.stream().map(item -> {
            List<Document> dList = new ArrayList<>(4);
            dList.add(new Document("deptTag", new Document("$eq", Boolean.TRUE)));
            dList.add(new Document("recordStatus",  new Document("$eq", item)));
            if (params.getDataType().equals(1)) {
                dList.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
            }
            Document filter = new Document("$and", dList);
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$deviceId")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getMinistryVideoAvailable)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getMinistryVideoAvailable).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        resultCount.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", resultCount);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：重点点位录像可用率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoImportantPointAvailabilityRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("deviceId", "deviceName");
        Query query = MongoUtil.getQuery(params,"createTime", likeFileds, 3);

        long total = mongoTemplate.count(query, RecordMetaDSumResult.class);
        MongoUtil.setPage(query, params, "createTime");
        List<RecordMetaDSumResult> resultList = mongoTemplate.find(query, RecordMetaDSumResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_record_meta_d_sum");
        List<Integer> status = Arrays.asList(1, 0, -1);
        List<String> resultCount = status.stream().map(item -> {
            List<Document> dList = new ArrayList<>(4);
            dList.add(new Document("importantTag", new Document("$eq", Boolean.TRUE)));
            dList.add(new Document("recordStatus", new Document("$eq", item)));
            if (params.getDataType().equals(1)) {
                dList.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
            }
            Document filter = new Document("$and", dList);
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$deviceId")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "%";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getKeyVideoAvailable)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getKeyVideoAvailable).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        resultCount.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", resultCount);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：标注正确率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoLabelingAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("deviceId", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, RecordMetaDSumResult.class);
        List<RecordMetaDSumResult> resultList = mongoTemplate.find(query, RecordMetaDSumResult.class);
        // 统计数
        long nonNetwork = mongoTemplate.count(new Query().addCriteria(Criteria.where("LWSX").is("0")), RecordMetaDSumResult.class);
        long network = mongoTemplate.count(new Query().addCriteria(Criteria.where("LWSX").is("1")), RecordMetaDSumResult.class);
        long video = mongoTemplate.count(new Query().addCriteria(Criteria.where("SXJGNLX").regex(".*1.*")), RecordMetaDSumResult.class);
        long car = mongoTemplate.count(new Query().addCriteria(Criteria.where("SXJGNLX").regex(".*2.*")), RecordMetaDSumResult.class);
        long face = mongoTemplate.count(new Query().addCriteria(Criteria.where("SXJGNLX").regex(".*3.*")), RecordMetaDSumResult.class);
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(nonNetwork, network, video, car, face));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：重点点位标注正确率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoImportantPointLabelingAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("deviceNo", "osdName");
        Query query = MongoUtil.getQuery(params,"checkTime", likeFileds, 3);

        long total = mongoTemplate.count(query, OsdCheckResult.class);
        MongoUtil.setPage(query, params, "checkTime");
        List<OsdCheckResult> resultList = mongoTemplate.find(query, OsdCheckResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("osd_check_result");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("importantTag", Boolean.TRUE));
        dList1.add(new Document("osdNameCorrect", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("importantTag", Boolean.TRUE));
        dList2.add(new Document("osdNameCorrect", new Document("$eq", -1)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("importantTag", Boolean.TRUE));
        dList3.add(new Document("osdTimeCorrect", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("importantTag", Boolean.TRUE));
        dList4.add(new Document("osdTimeCorrect", new Document("$eq", -1)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document osdNameFilter = new Document("$and", dList1);
        Document osdNameErrFilter = new Document("$and", dList2);
        Document osdTimeFilter = new Document("$and", dList3);
        Document osdTimeErrFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(osdNameFilter, osdNameErrFilter, osdTimeFilter, osdTimeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$deviceNo")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getKeyAnnotationAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getKeyAnnotationAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：校时正确率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoCheckTimeAccuracy(DataCenterQuery params) {

        List<String> likeFileds = Arrays.asList("deviceId");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, OneMachineFileResult.class);
        List<OneMachineFileResult> resultList = mongoTemplate.find(query, OneMachineFileResult.class);
        // 统计数
        long nonNetwork = mongoTemplate.count(new Query().addCriteria(Criteria.where("LWSX").is("0")), OneMachineFileResult.class);
        long network = mongoTemplate.count(new Query().addCriteria(Criteria.where("LWSX").is("1")), OneMachineFileResult.class);
        long video = mongoTemplate.count(new Query().addCriteria(Criteria.where("SXJGNLX").regex(".*1.*")), OneMachineFileResult.class);
        long car = mongoTemplate.count(new Query().addCriteria(Criteria.where("SXJGNLX").regex(".*2.*")), OneMachineFileResult.class);
        long face = mongoTemplate.count(new Query().addCriteria(Criteria.where("SXJGNLX").regex(".*3.*")), OneMachineFileResult.class);
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(nonNetwork, network, video, car, face));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 视频：重点点位校时正确率
     *
     * @param params
     * @return
     */
    @Override
    public Result videoImportantPointCheckTimeAccuracy(DataCenterQuery params) {

        List<String> likeFileds = Arrays.asList("deviceNo", "osdName");
        Query query = MongoUtil.getQuery(params,"checkTime", likeFileds, 3);

        long total = mongoTemplate.count(query, OsdCheckResult.class);
        MongoUtil.setPage(query, params, "checkTime");
        List<OsdCheckResult> resultList = mongoTemplate.find(query, OsdCheckResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("osd_check_result");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("importantTag", Boolean.TRUE));
        dList1.add(new Document("osdTimeCorrect", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("importantTag", Boolean.TRUE));
        dList2.add(new Document("osdTimeCorrect", new Document("$eq", -1)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document osdTimeFilter = new Document("$and", dList1);
        Document osdTimeErrFilter = new Document("$and", dList2);
        List<Document> lists = Arrays.asList(osdTimeFilter, osdTimeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$deviceNo")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
                .select(CheckIndexVideo::getKeyTimingAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getKeyTimingAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }


    /**
     * 车辆：视图库对接稳定性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleViewDockStable(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, SnapshotDataMonitorResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<SnapshotDataMonitorResult> resultList = mongoTemplate.find(query, SnapshotDataMonitorResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_snapshot_data_monitor");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("importantTag", Boolean.TRUE));
        dList1.add(new Document("resultType", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("importantTag", Boolean.TRUE));
        dList2.add(new Document("resultType", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("importantTag", Boolean.TRUE));
        dList3.add(new Document("resultType", new Document("$eq", 3)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("importantTag", Boolean.TRUE));
        dList4.add(new Document("resultType", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document normalFilter = new Document("$and", dList1);
        Document noDataFilter = new Document("$and", dList2);
        Document trFilter = new Document("$and", dList3);
        Document littleFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(normalFilter, noDataFilter, trFilter, littleFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getViewConnectStability)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getViewConnectStability).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：点位在线率
     *
     * @param params
     * @return
     */
    @Override
    public Result vehiclePointOnlineRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, SnapshotDataMonitorResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<SnapshotDataMonitorResult> resultList = mongoTemplate.find(query, SnapshotDataMonitorResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_snapshot_data_monitor");
        long distinctCount = collection.distinct("externalIndexCode", String.class).into(new ArrayList<>()).size();

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getSiteOnline)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getSiteOnline).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(distinctCount + "", this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：互联网卡口设备目录一致性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleNetDeviceDirectoryConsistency(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("ip.showValue", "name.showValue", "serialNumber.showValue");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, MonitorQualifyResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<MonitorQualifyResult> resultList = mongoTemplate.find(query, MonitorQualifyResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_monitor_qualify");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("ip.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("macdz.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("latitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("longitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$serialNumber.showValue")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getDeviceDirectoryConsistent)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getDeviceDirectoryConsistent).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口信息采集准确率
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleCollectionConsistency(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "crossName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, CrossDetailResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<CrossDetailResult> resultList = mongoTemplate.find(query, CrossDetailResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_cross_detail");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("lalType", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("lalType", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("lalType", new Document("$eq", 3)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("lalType", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehicleInformationCollectionAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehicleInformationCollectionAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口设备抓拍数据完整性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleCollectionDataIntegrity(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, DataIntegrityMonitoringResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<DataIntegrityMonitoringResult> resultList = mongoTemplate.find(query, DataIntegrityMonitoringResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_data_integrity_monitoring");

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehicleCaptureIntegrity)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehicleCaptureIntegrity).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }

        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口设备抓拍数据准确性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleCollectionDataCaptured(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, AttrRecognitionMonitorResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<AttrRecognitionMonitorResult> resultList = mongoTemplate.find(query, AttrRecognitionMonitorResult.class);

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehicleCaptureAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehicleCaptureAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口设备时钟准确性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleClockAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, VehicleDeviceInspectionResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<VehicleDeviceInspectionResult> resultList = mongoTemplate.find(query, VehicleDeviceInspectionResult.class);


        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_vehicle_device_inspection");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("snapResult", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("snapResult", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("snapResult", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document longitudeErrFilter = new Document("$and", dList3);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehicleTimingAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehicleTimingAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口设备抓拍数据上传及时性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleTimelyUploadAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, SnapshotDelayMonitorResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<SnapshotDelayMonitorResult> resultList = mongoTemplate.find(query, SnapshotDelayMonitorResult.class);

        // 统计数
        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehicleUploadTimeliness)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehicleUploadTimeliness).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口设备url可用性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleUrlAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, PicAccessResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<PicAccessResult> resultList = mongoTemplate.find(query, PicAccessResult.class);

        // 统计数
        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehicleUrlAvailability)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehicleUrlAvailability).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 车辆：车辆卡口设备抓拍数据大图可用性
     *
     * @param params
     * @return
     */
    @Override
    public Result vehicleBigImgAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, VehicleDeviceSamplingResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<VehicleDeviceSamplingResult> resultList = mongoTemplate.find(query, VehicleDeviceSamplingResult.class);

        // 统计数
        Date now = new Date();
        List<CheckIndexCar> videoList = new LambdaQueryChainWrapper<>(checkIndexCarService.getBaseMapper())
                .select(CheckIndexCar::getVehiclePictureAvailability)
                .eq(params.getDataType().equals(1), CheckIndexCar::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexCar::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexCar::getVehiclePictureAvailability).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：视图库对接稳定性
     *
     * @param params
     * @return
     */
    @Override
    public Result faceViewDockStable(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, SnapshotDataMonitorResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<SnapshotDataMonitorResult> resultList = mongoTemplate.find(query, SnapshotDataMonitorResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_snapshot_data_monitor");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("resultType", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("resultType", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("resultType", new Document("$eq", 3)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("resultType", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document normalFilter = new Document("$and", dList1);
        Document noDataFilter = new Document("$and", dList2);
        Document trFilter = new Document("$and", dList3);
        Document littleFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(normalFilter, noDataFilter, trFilter, littleFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getViewConnectStability)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getViewConnectStability).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：点位在线率
     *
     * @param params
     * @return
     */
    @Override
    public Result facePointOnlineRate(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, SnapshotDataMonitorResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<SnapshotDataMonitorResult> resultList = mongoTemplate.find(query, SnapshotDataMonitorResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_snapshot_data_monitor");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("resultType", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("resultType", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("resultType", new Document("$eq", 3)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("resultType", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document normalFilter = new Document("$and", dList1);
        Document noDataFilter = new Document("$and", dList2);
        Document trFilter = new Document("$and", dList3);
        Document littleFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(normalFilter, noDataFilter, trFilter, littleFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getSiteOnline)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getSiteOnline).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：目录一致率
     *
     * @param params
     * @return
     */
    @Override
    public Result faceDirectoryConsistency(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("serialNumber.showValue", "ip.showValue", "name.showValue");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, MonitorQualifyResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<MonitorQualifyResult> resultList = mongoTemplate.find(query, MonitorQualifyResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_monitor_qualify");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("ip.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("macdz.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("latitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("longitude.error", new Document("$eq", Boolean.TRUE)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$serialNumber.showValue")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getDeviceDirectoryConsistent)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getDeviceDirectoryConsistent).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：人脸卡口信息采集准确率
     *
     * @param params
     * @return
     */
    @Override
    public Result faceCollectionConsistency(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "crossName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, CrossDetailResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<CrossDetailResult> resultList = mongoTemplate.find(query, CrossDetailResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_cross_detail");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("lalType", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("lalType", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("lalType", new Document("$eq", 3)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("lalType", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);
        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getFaceInformationCollectionAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getFaceInformationCollectionAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：设备抓拍图片合格性
     *
     * @param params
     * @return
     */
    @Override
    public Result faceImgQualification(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "cameraName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, MonitoringDetailResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<MonitoringDetailResult> resultList = mongoTemplate.find(query, MonitoringDetailResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_monitoring_detail");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("lalType", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("lalType", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("lalType", new Document("$eq", 3)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList4 = new ArrayList<>(2);
        dList4.add(new Document("lalType", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList4.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document latitudeErrFilter = new Document("$and", dList3);
        Document longitudeErrFilter = new Document("$and", dList4);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, latitudeErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getFacePictureQualification)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getFacePictureQualification).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：设备抓拍图片时钟准确性
     *
     * @param params
     * @return
     */
    @Override
    public Result faceCapturesImagesAccuracy(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, FaceDeviceInspectionResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<FaceDeviceInspectionResult> resultList = mongoTemplate.find(query, FaceDeviceInspectionResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_vehicle_device_inspection");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("snapResult", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("snapResult", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("snapResult", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document longitudeErrFilter = new Document("$and", dList3);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getFaceTimingAccuracy)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getFaceTimingAccuracy).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：抓拍人脸数据上传及时性
     *
     * @param params
     * @return
     */
    @Override
    public Result faceTimelyUpload(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, FaceDeviceInspectionResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<FaceDeviceInspectionResult> resultList = mongoTemplate.find(query, FaceDeviceInspectionResult.class);

        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("hk_vehicle_device_inspection");

        List<Document> dList1 = new ArrayList<>(2);
        dList1.add(new Document("snapResult", new Document("$eq", 1)));
        if (params.getDataType().equals(1)) {
            dList1.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList2 = new ArrayList<>(2);
        dList2.add(new Document("snapResult", new Document("$eq", 2)));
        if (params.getDataType().equals(1)) {
            dList2.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        List<Document> dList3 = new ArrayList<>(2);
        dList3.add(new Document("snapResult", new Document("$eq", 4)));
        if (params.getDataType().equals(1)) {
            dList3.add(new Document("provinceTag", new Document("$eq", Boolean.TRUE)));
        }
        Document ipErrFilter = new Document("$and", dList1);
        Document macdzErrFilter = new Document("$and", dList2);
        Document longitudeErrFilter = new Document("$and", dList3);

        List<Document> lists = Arrays.asList(ipErrFilter, macdzErrFilter, longitudeErrFilter);
        List<String> rList = lists.stream().map(filter -> {
            // 构建聚合管道
            List<Document> pipeline = Arrays.asList(
                    new Document("$match", filter),
                    // $group 去重
                    new Document("$group", new Document("_id", "$externalIndexCode")),
                    new Document("$count", "uniqueDeviceIds")
            );
            // 执行聚合查询并获取结果
            AggregateIterable<Document> result = collection.aggregate(pipeline);
            Integer uniqueDeviceIdCount = 0;
            for (Document doc : result) {
                uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
                break; // 不需要继续遍历，因为 $count 只会产生一个结果
            }
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());

        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getFaceUploadTimeliness)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getFaceUploadTimeliness).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }
        rList.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", rList);
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }

    /**
     * 人脸：人脸卡口设备抓拍数据大图可用性
     *
     * @param params
     * @return
     */
    @Override
    public Result faceAvailabilityOfLargeImg(DataCenterQuery params) {
        List<String> likeFileds = Arrays.asList("externalIndexCode", "deviceName");
        Query query = MongoUtil.getQuery(params, TIME_FIELD, likeFileds, null);

        long total = mongoTemplate.count(query, FaceDeviceSamplingResult.class);
        MongoUtil.setPage(query, params, TIME_FIELD);
        List<FaceDeviceSamplingResult> resultList = mongoTemplate.find(query, FaceDeviceSamplingResult.class);

        // 统计数
        Date now = new Date();
        List<CheckIndexFace> videoList = new LambdaQueryChainWrapper<>(checkIndexFaceService.getBaseMapper())
                .select(CheckIndexFace::getFacePictureAvailability)
                .eq(params.getDataType().equals(1), CheckIndexFace::getExamineTag, CheckConstants.Examine_Tag_Province)
                .between(CheckIndexFace::getCreateTime, DateUtils.getDayStart(now), DateUtils.getDayEnd(now))
                .list();
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (CollectionUtils.isNotEmpty(videoList)) {
            BigDecimal sum = videoList.stream().map(CheckIndexFace::getFacePictureAvailability).reduce(BigDecimal.ZERO, BigDecimal::add);
            BigDecimal count = BigDecimal.valueOf(videoList.size());
            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
        }

        HashMap<String, Object> map = new HashMap<>();
        map.put("count", Arrays.asList(this.remove0(onlineRate)));
        map.put("list", resultList);
        return Result.ok().data(map).total(total);
    }
    /**
     * 视频：视频图像资源安全管理
     *
     * @param query
     * @return
     */
    @Override
    public Result videoImageResourceSecurity(DataCenterQuery query) {
        Page<ImageResourceSecurityDetail> page = PageHelper.startPage(query.getPageNum(), query.getPageSize());
        securityDetailMapper.selectImageResourceSecurityDetailList(query);

        // 统计数
        HashMap<String, Object> map = new HashMap<>();
        map.put("count", CollectionUtils.EMPTY_COLLECTION);
        map.put("list", page);
        return Result.ok().data(map).total(page.getTotal());

    }

    /**
     * 删除尾部的0
     * @param rate
     * @return
     */
    private String remove0(BigDecimal rate) {
        DF.setDecimalSeparatorAlwaysShown(false);
        return DF.format(rate) + "%";
    }
}