优化架次

liusuyi

2025-12-24 18f6032658828ceaff5a61ca1f495f74a1092f57

 ard-work/src/main/java/com/ard/work/service/impl/ArdFlightTaskPartServiceImpl.java

@@ -1,7 +1,10 @@
package com.ard.work.service.impl;

import cn.hutool.core.util.SerializeUtil;
import com.ard.work.domain.cache.UavStateCache;
import com.ard.work.domain.cache.UavTelemetryDataCache;
import com.ard.work.domain.dto.UavFlightStateDTO;
import com.ard.work.domain.dto.state.UavState;
import com.ard.work.domain.dto.telemetry.TelemetryData;
import com.ard.work.domain.entity.ArdFlightTaskPart;
import com.ard.work.mapper.ArdFlightTaskPartMapper;
@@ -11,12 +14,13 @@
import org.springframework.scheduling.annotation.Async;
import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.stereotype.Service;
import java.time.LocalDateTime;
import java.time.temporal.ChronoUnit;

import java.util.ArrayList;
import java.util.Comparator;
import java.util.Date;
import java.util.List;
import java.util.concurrent.ConcurrentHashMap;

/**
 * 轨迹分片处理业务
 */
@@ -26,11 +30,12 @@
public class ArdFlightTaskPartServiceImpl implements IArdFlightTaskPartService {

    private final ArdFlightTaskPartMapper ardflightTaskPartMapper;

    // 上一次飞行状态缓存
    private final ConcurrentHashMap<String, Integer> lastFlightStatusMap = new ConcurrentHashMap<>();
    /**
     * 缓存：boxSn -> 当前分片数据
     */
    private final ConcurrentHashMap<String, List<TelemetryData>> cacheMap = new ConcurrentHashMap<>();
    private final ConcurrentHashMap<String, List<UavFlightStateDTO>> cacheMap = new ConcurrentHashMap<>();

    /**
     * 分片保存阈值条数
@@ -43,8 +48,41 @@
     */
    @Scheduled(fixedRate = 1000)
    public void readTelemetryTask() {
        long now = System.currentTimeMillis();
        UavTelemetryDataCache.forEach((boxSn, telemetryData) -> {
            addTelemetryData(telemetryData);

            // 1️⃣ 从状态缓存里取当前状态
            UavState uavState = UavStateCache.get(boxSn);
            if (uavState == null) {
                return; // 状态不存在，不记录
            }

            // 2️⃣ 使用遥测自身时间戳判断是否还活着
            long dataTs = telemetryData.getTimestamp(); // 设备时间 / 服务器接收时间
            if (now - dataTs > 3000) {
                return; // 超过 3 秒没有新遥测 → 认为已离线或冻结，不记录
            }

            int currentStatus = uavState.getFlightControllerState().getFlightStatus();
            Integer lastStatus = lastFlightStatusMap.get(boxSn);

            // 仅在“飞行中 → 非飞行中”状态变化时 flush
            if (lastStatus != null && lastStatus == 2 && currentStatus != 2) {
                flushRemaining(boxSn);
            }
            lastFlightStatusMap.put(boxSn, currentStatus);

            // 只有飞行中才添加缓存
            if (currentStatus == 2) {
                UavFlightStateDTO dto = new UavFlightStateDTO(uavState, telemetryData, dataTs);
                addTelemetryData(dto);
            }
            UavFlightStateDTO dto = new UavFlightStateDTO(
                    uavState,
                    telemetryData,
                    dataTs
            );
            addTelemetryData(dto);
        });
    }

@@ -52,10 +90,10 @@
     * 添加一条遥测数据到缓存
     */
    @Override
    public void addTelemetryData(TelemetryData telemetryData) {
        String boxSn = telemetryData.getBoxSn();
        List<TelemetryData> list = cacheMap.computeIfAbsent(boxSn, k -> new ArrayList<>());
        list.add(telemetryData);
    public void addTelemetryData(UavFlightStateDTO uavFlightStateDTO) {
        String boxSn = uavFlightStateDTO.getTelemetryData().getBoxSn();
        List<UavFlightStateDTO> list = cacheMap.computeIfAbsent(boxSn, k -> new ArrayList<>());
        list.add(uavFlightStateDTO);

        // 当缓存条数达到阈值 或 时间间隔超过 CHUNK_INTERVAL 时，分片保存
        if (list.size() >= CHUNK_SIZE) {
@@ -68,18 +106,22 @@
     */
    @Async
    public void saveChunk(String boxSn) {
        List<TelemetryData> dataList = cacheMap.getOrDefault(boxSn, new ArrayList<>());
        List<UavFlightStateDTO> dataList = cacheMap.getOrDefault(boxSn, new ArrayList<>());
        if (dataList.isEmpty()) {
            return;
        }

        try {
            byte[] blobData = SerializeUtil.serialize(dataList);

            // 取第一个和最后一个状态时间
            long startTs = dataList.get(0).getTimestamp();
            long endTs = dataList.get(dataList.size() - 1).getTimestamp();
            ArdFlightTaskPart part = ArdFlightTaskPart.builder()
                    .boxSn(boxSn)
                    .count(dataList.size())
                    .dataPart(blobData)
                    .startTime(new Date(startTs))
                    .endTime(new Date(endTs))
                    .build();
            part.setCreateTime(new Date());
            ardflightTaskPartMapper.insert(part);
@@ -100,7 +142,7 @@
     */
    @Override
    public void flushRemaining(String boxSn) {
        List<TelemetryData> dataList = cacheMap.getOrDefault(boxSn, new ArrayList<>());
        List<UavFlightStateDTO> dataList = cacheMap.getOrDefault(boxSn, new ArrayList<>());
        if (!dataList.isEmpty()) {
            saveChunk(boxSn);
        }
@@ -110,18 +152,21 @@
     * 获取完整航线轨迹（合并所有分片）
     */
    @Override
    public List<TelemetryData> getCompleteFlightData(ArdFlightTaskPart ardFlightTaskPart) {
        List<TelemetryData> allData = new ArrayList<>();
    public List<UavFlightStateDTO> getCompleteFlightData(ArdFlightTaskPart ardFlightTaskPart) {
        List<UavFlightStateDTO> allData = new ArrayList<>();
        String boxSn = ardFlightTaskPart.getBoxSn();
        List<ArdFlightTaskPart> parts = ardflightTaskPartMapper.selectByTaskStartTime(ardFlightTaskPart);
        List<ArdFlightTaskPart> parts = ardflightTaskPartMapper.selectByTimeRange(ardFlightTaskPart);
        for (ArdFlightTaskPart part : parts) {
            try {
                List<TelemetryData> partData = SerializeUtil.deserialize(part.getDataPart());
                List<UavFlightStateDTO> partData = SerializeUtil.deserialize(part.getDataPart());
                allData.addAll(partData);
            } catch (Exception e) {
                log.error("反序列化 boxSn={} 分片数据失败", boxSn, e);
            }
        }
        // 按 telemetryData.timestamp 升序排序
        allData.sort(Comparator.comparingLong(dto -> dto.getTelemetryData().getTimestamp()));

        return allData;
    }
}