1、内存利用率图标增加内存已用字段。

2、ping丢包率虚拟网卡模式累加。
2026-02-03 18:46:51 +08:00
parent 180c522ca3
commit f8e0ab1b2a
8 changed files with 159 additions and 89 deletions
@@ -90,8 +90,15 @@ public class EchartsDataUtils {

            // 计算稀疏间隔
            long totalTimeRange = endDate.getTime() - startDate.getTime();
-            long sparseInterval = totalTimeRange > 12L * 30 * 24 * 60 * 60 * 1000 ?
-                    30L * 24 * 60 * 60 * 1000 : 2L * 24 * 60 * 60 * 1000;
+
+            long sparseInterval;
+            if (totalTimeRange > 12L * 30 * 24 * 60 * 60 * 1000) {  // 大于12个月
+                sparseInterval = 30L * 24 * 60 * 60 * 1000;         // 30天间隔
+            } else if (totalTimeRange <= 24L * 60 * 60 * 1000) {    // 小于等于24小时
+                sparseInterval = 5L * 60 * 1000;                    // 5分钟间隔
+            } else {                                                // 其他情况（大于24小时，小于等于12个月）
+                sparseInterval = 2L * 24 * 60 * 60 * 1000;          // 2天间隔
+            }

            // 核心修改：生成X轴时间序列
            List<Date> xAxisTimes = generateXAxisTimeSeries(
@@ -323,6 +330,16 @@ public class EchartsDataUtils {
            if (normalizedStart < startMillis) {
                calendar.add(Calendar.MILLISECOND, (int)interval);
            }
+        } else {
+            // 对齐到下一分钟的0秒
+            // 先将秒和毫秒清零
+            calendar.set(Calendar.SECOND, 0);
+            calendar.set(Calendar.MILLISECOND, 0);
+
+            // 如果当前时间不是整分钟，就跳到下一分钟
+            if (calendar.getTime().before(start)) {
+                calendar.add(Calendar.MINUTE, 1);
+            }
        }

        // 包含开始时间
@@ -182,9 +182,15 @@ public class EchartsMoreDataUtils {

        // 计算稀疏间隔
        long totalTimeRange = endDate.getTime() - startDate.getTime();
-        long sparseInterval = totalTimeRange > 12L * 30 * 24 * 60 * 60 * 1000 ?
-                30L * 24 * 60 * 60 * 1000 : 2L * 24 * 60 * 60 * 1000;

+        long sparseInterval;
+        if (totalTimeRange > 12L * 30 * 24 * 60 * 60 * 1000) {  // 大于12个月
+            sparseInterval = 30L * 24 * 60 * 60 * 1000;         // 30天间隔
+        } else if (totalTimeRange <= 24L * 60 * 60 * 1000) {    // 小于等于24小时
+            sparseInterval = 5L * 60 * 1000;                    // 5分钟间隔
+        } else {                                                // 其他情况（大于24小时，小于等于12个月）
+            sparseInterval = 2L * 24 * 60 * 60 * 1000;          // 2天间隔
+        }
        // 使用默认的5分钟作为数据期间间隔
        long dataInterval = 300000L;

@@ -421,7 +427,7 @@ public class EchartsMoreDataUtils {
     */
    private static long normalizeTime(Date time, long interval) {
        long timeMillis = time.getTime();
-        return (timeMillis / interval) * interval;
+        return ((timeMillis + interval - 1) / interval) * interval;
    }
    public static Map<String, String> sortInterfaceMap(Map<String, String> interfaceMap, String mainName, boolean hasSub) {
        List<Map.Entry<String, String>> list = new ArrayList<>(interfaceMap.entrySet());
@@ -35,4 +35,6 @@ public class InitialSystemOtherCollectData extends BaseEntity
    private String endTime;
    /** 表名 */
    private String tableName;
+    /** 已用内存 */
+    private String memUsed;
 }
@@ -45,6 +45,7 @@ import java.math.BigDecimal;
 import java.math.RoundingMode;
 import java.text.SimpleDateFormat;
 import java.util.*;
+import java.util.concurrent.ConcurrentHashMap;
 import java.util.concurrent.TimeUnit;
 import java.util.function.Consumer;
 import java.util.function.Function;
@@ -192,12 +193,14 @@ public class MessageHandler {
                    localIsp = networkInfoChild.getIsp();
                }
            }
+            // 在计算百分比之前，先并行查询所有IP归属地
+            Map<String, Map<String, String>> ipLocationCache = new ConcurrentHashMap<>();

+            tcpdumpVoList.parallelStream().forEach(vo -> {
+                ipLocationCache.computeIfAbsent(vo.getIp(), ip -> queryIpLocation(ip));
+            });
            // 计算总数量
            Double totalCount = 0.0;
-            for (TcpdumpVo tcpdumpVo : tcpdumpVoList) {
-                totalCount += tcpdumpVo.getCount();
-            }

            // 分别统计IPv4和IPv6
            Map<String, List<TcpdumpVo>> ipTypeMap = new HashMap<>();
@@ -206,6 +209,7 @@ public class MessageHandler {

            // 按类型分类
            for (TcpdumpVo tcpdumpVo : tcpdumpVoList) {
+                totalCount += tcpdumpVo.getCount();
                String ip = tcpdumpVo.getIp();
                String type = checkIPVersion(ip);
                if ("IPv4".equals(type)) {
@@ -232,7 +236,7 @@ public class MessageHandler {
                // 按省份运营商分组统计（过滤本地省份）
                Map<String, Double> v4StatMap = new HashMap<>();
                for (TcpdumpVo tcpdumpVo : ipTypeMap.get("IPv4")) {
-                    Map<String, String> locationInfo = queryIpLocation(tcpdumpVo.getIp());
+                    Map<String, String> locationInfo = ipLocationCache.get(tcpdumpVo.getIp());
                    if (locationInfo != null) {
                        String operator = locationInfo.get("operator");
                        String province = locationInfo.get("province");
@@ -277,7 +281,7 @@ public class MessageHandler {
                // 按省份运营商分组统计（过滤本地省份）
                Map<String, Double> v6StatMap = new HashMap<>();
                for (TcpdumpVo tcpdumpVo : ipTypeMap.get("IPv6")) {
-                    Map<String, String> locationInfo = queryIpLocation(tcpdumpVo.getIp());
+                    Map<String, String> locationInfo = ipLocationCache.get(tcpdumpVo.getIp());
                    if (locationInfo != null) {
                        String operator = locationInfo.get("operator");
                        String province = locationInfo.get("province");
@@ -80,4 +80,6 @@ public interface InitialSystemOtherCollectDataMapper
     * @return
     */
    String getMemTotalSize(InitialSystemOtherCollectData otherCollectData);
+
+    String getMemTotalSizeNoConvert(InitialSystemOtherCollectData otherCollectData);
 }
@@ -704,94 +704,72 @@ public class InitialBandwidthTrafficServiceImpl implements IInitialBandwidthTraf
        return resultMap;
    }

+//    @Override
+//    public Map<String, Object> pingDroppedEcharts(InitialBandwidthTraffic initialBandwidthTraffic) {
+//        // 流量信息
+//        List<InitialBandwidthTraffic> list = getListByTableName(initialBandwidthTraffic);
+//        Map<String, Function<InitialBandwidthTraffic, ?>> extractors = new LinkedHashMap<>();
+//        extractors.put("pingDropped", info -> info.getPingDropped());
+//
+//        return EchartsDataUtils.buildEchartsDataAutoPadding(
+//                list, InitialBandwidthTraffic::getCreateTime, extractors,
+//                initialBandwidthTraffic.getStartTime(), initialBandwidthTraffic.getEndTime()
+//        );
+//    }
    @Override
    public Map<String, Object> pingDroppedEcharts(InitialBandwidthTraffic initialBandwidthTraffic) {
-        // 流量信息
+        // 主网卡流量信息
        List<InitialBandwidthTraffic> list = getListByTableName(initialBandwidthTraffic);
+        String originalName = initialBandwidthTraffic.getName();
+        String name = originalName;
+        if (originalName != null && originalName.contains("(")) {
+            int index = originalName.indexOf("(");
+            name = originalName.substring(0, index);
+        }
+        // 如果是Ethernet类型，查询子网卡
+        if(isEthernetInterface(name)){
+            RmNetworkInterfaceChild query = new RmNetworkInterfaceChild();
+            query.setClientId(initialBandwidthTraffic.getClientId());
+            query.setParentInterface(name);
+            List<RmNetworkInterfaceChild> children = rmNetworkInterfaceChildMapper.selectRmNetworkInterfaceChildList(query);
+            if(children != null && !children.isEmpty()){
+                // 按时间分组的主网卡数据
+                Map<String, InitialBandwidthTraffic> timeGroupMap = new HashMap<>();
+                for (InitialBandwidthTraffic item : list) {
+                    if (item.getCreateTime() != null) {
+                        timeGroupMap.put(DateUtils.parseDateToStr("yyyy-MM-dd HH:mm:ss", item.getCreateTime()), item);
+                    }
+                }
+                for (RmNetworkInterfaceChild child : children) {
+                    InitialBandwidthTraffic childTraffic = new InitialBandwidthTraffic();
+                    BeanUtils.copyProperties(initialBandwidthTraffic, childTraffic);
+                    childTraffic.setName(child.getInterfaceName());
+                    List<InitialBandwidthTraffic> childTrafficList = getListByTableName(childTraffic);
+                    if(childTrafficList != null && !childTrafficList.isEmpty()){
+                        // 将子网卡数据累加到对应时间点的主网卡数据中
+                        for (InitialBandwidthTraffic childItem : childTrafficList) {
+                            if (childItem.getCreateTime() != null && childItem.getPingDropped() != null) {
+                                InitialBandwidthTraffic mainItem = timeGroupMap.get(DateUtils.parseDateToStr("yyyy-MM-dd HH:mm:ss", childItem.getCreateTime()));
+                                if (mainItem != null) {
+                                    // 累加pingDropped值
+                                    Double mainValue = mainItem.getPingDropped() != null ? mainItem.getPingDropped() : 0;
+                                    Double childValue = childItem.getPingDropped() != null ? childItem.getPingDropped() : 0;
+                                    // 修改原list中pingDropped的值
+                                    mainItem.setPingDropped(mainValue + childValue);
+                                }
+                            }
+                        }
+                    }
+                }
+            }
+        }
        Map<String, Function<InitialBandwidthTraffic, ?>> extractors = new LinkedHashMap<>();
        extractors.put("pingDropped", info -> info.getPingDropped());
-
        return EchartsDataUtils.buildEchartsDataAutoPadding(
                list, InitialBandwidthTraffic::getCreateTime, extractors,
                initialBandwidthTraffic.getStartTime(), initialBandwidthTraffic.getEndTime()
        );
    }
-//    @Override
-//    public Map<String, Object> pingDroppedEcharts(InitialBandwidthTraffic initialBandwidthTraffic) {
-//        // 主网卡流量信息
-//        List<InitialBandwidthTraffic> mainList = getListByTableName(initialBandwidthTraffic);
-//        String originalName = initialBandwidthTraffic.getName();
-//        String name = originalName;
-//
-//        if (originalName != null && originalName.contains("(")) {
-//            int index = originalName.indexOf("(");
-//            name = originalName.substring(0, index);
-//        }
-//
-//        // 存储所有网卡的数据
-//        Map<String, List<InitialBandwidthTraffic>> interfaceDataMap = new LinkedHashMap<>();
-//        // 展示关系
-//        Map<String, String> showRealation = new HashMap<>();
-//
-//        // 添加主网卡数据
-//        interfaceDataMap.put(name, mainList);
-//        showRealation.put(name+"pingDropped", name+"的ping丢包率");
-//
-//        boolean hasSubInterface = false;
-//
-//        // 如果是Ethernet类型，查询子网卡
-//        if(isEthernetInterface(name)){
-//            RmNetworkInterfaceChild query = new RmNetworkInterfaceChild();
-//            query.setClientId(initialBandwidthTraffic.getClientId());
-//            query.setParentInterface(name);
-//            List<RmNetworkInterfaceChild> children = rmNetworkInterfaceChildMapper.selectRmNetworkInterfaceChildList(query);
-//            if(children != null && !children.isEmpty()){
-//                hasSubInterface = true;
-//                for (RmNetworkInterfaceChild child : children) {
-//                    InitialBandwidthTraffic childTraffic = new InitialBandwidthTraffic();
-//                    BeanUtils.copyProperties(initialBandwidthTraffic, childTraffic);
-//                    childTraffic.setName(child.getInterfaceName());
-//                    List<InitialBandwidthTraffic> childTrafficList = getListByTableName(childTraffic);
-//
-//                    if(childTrafficList != null && !childTrafficList.isEmpty()){
-//                        interfaceDataMap.put(child.getInterfaceName(), childTrafficList);
-//                        showRealation.put(child.getInterfaceName()+"pingDropped", child.getInterfaceName() + "的ping丢包率");
-//                    }
-//                }
-//            }
-//        }
-//
-//        try {
-//            // 获取ping丢包率图表数据
-//            Map<String, Object> resultMap = EchartsMoreDataUtils.buildMultiInterfaceEchartsDataWithTotal(
-//                    interfaceDataMap,
-//                    InitialBandwidthTraffic::getCreateTime,
-//                    info -> info.getPingDropped() != null ? new BigDecimal(info.getPingDropped()) : null,
-//                    null, // 出站流量设为null，因为ping丢包率只有单向数据
-//                    initialBandwidthTraffic.getStartTime(),
-//                    initialBandwidthTraffic.getEndTime(),
-//                    BigDecimal.ONE // 使用1作为除数，因为ping丢包率通常是百分比，不需要单位转换
-//            );
-//
-//            // 如果有子网卡，添加总丢包率显示
-//            if(hasSubInterface){
-//                showRealation.put("totalPingDropped", name+"总ping丢包率");
-//            }
-//
-//            // 排序显示关系
-//            Map<String, String> sortedShowRealation = EchartsMoreDataUtils.sortInterfaceMap(showRealation, name, hasSubInterface);
-//            resultMap.put("showRealation", sortedShowRealation);
-//
-//            // 添加单位信息（ping丢包率通常用百分比表示）
-//            resultMap.put("unit", "%");
-//
-//            return resultMap;
-//
-//        } catch (Exception e){
-//            e.printStackTrace();
-//            return new HashMap<>();
-//        }
-//    }

    @Override
    public int countByClientIdAndTime(InitialBandwidthTraffic countQuery) {
@@ -175,7 +175,6 @@ public class InitialSystemOtherCollectDataServiceImpl implements IInitialSystemO
                })
                .collect(Collectors.toList());
    }
-
    /**
     * 查询系统登陆用户数(个)监控信息列表并封装为多折线ECharts图表数据
     * @param initialSystemOtherCollectData
@@ -217,9 +216,55 @@ public class InitialSystemOtherCollectDataServiceImpl implements IInitialSystemO
    public Map<String, Object> memoryUtilizationEcharts(InitialSystemOtherCollectData initialSystemOtherCollectData) {
        initialSystemOtherCollectData.setCollectType(ServerLogoEnum.内存利用率.getCode());
        List<InitialSystemOtherCollectData> list = getOtherMsgSharding(initialSystemOtherCollectData);
+        initialSystemOtherCollectData.setCollectType(ServerLogoEnum.可用内存.getCode());
+        List<InitialSystemOtherCollectData> usedList = getOtherMsgSharding(initialSystemOtherCollectData);

+        InitialSystemOtherCollectData memQuery = new InitialSystemOtherCollectData();
+        memQuery.setClientId(initialSystemOtherCollectData.getClientId());
+        memQuery.setTableName(TableSubUtil.getTableName(DateUtils.getNowDate(), TABLE_PREFIX));
+        // 总内存
+        String memTotalSize = initialSystemOtherCollectDataMapper.getMemTotalSizeNoConvert(memQuery);
+        Double totalMemory = 0d;
+        if(memTotalSize != null){
+            totalMemory = Double.parseDouble(memTotalSize);
+        }
+        // 将usedList转换为Map，key为createTime，value为collectValue字符串
+        // 将usedList转换为Map，key为createTime，value为已用内存（GB）
+        Map<Date, Double> usedMemoryGBMap = new HashMap<>();
+        for (InitialSystemOtherCollectData data : usedList) {
+            if (data.getCreateTime() != null && data.getCollectValue() != null) {
+                try {
+                    // 获取可用内存字符串（字节），防止科学计数法
+                    String availableMemoryStr = data.getCollectValue();
+
+                    // 将可用内存从字节转换为GB
+                    double availableMemory = Double.parseDouble(availableMemoryStr);
+
+                    // 计算已用内存 = 总内存 - 可用内存
+                    double usedMemoryGB = (totalMemory - availableMemory)/(1024 * 1024);
+
+                    // 确保已用内存不为负数
+                    usedMemoryGB = Math.max(0.0, usedMemoryGB);
+
+                    usedMemoryGBMap.put(data.getCreateTime(), usedMemoryGB);
+                } catch (NumberFormatException e) {
+                    // 处理转换异常，可以记录日志或跳过该数据
+                    System.err.println("无法转换collectValue为数字: " + data.getCollectValue());
+                }
+            }
+        }
+        // 遍历list，从Map中获取对应的已用内存值
+        for (InitialSystemOtherCollectData item : list) {
+            Double memUsed = usedMemoryGBMap.get(item.getCreateTime());
+            if (memUsed != null) {
+                // 格式化保留一位小数
+                String formattedMemUsed = String.format("%.1f", memUsed);
+                item.setMemUsed(formattedMemUsed);
+            }
+        }
        Map<String, Function<InitialSystemOtherCollectData, ?>> extractors = new LinkedHashMap<>();
        extractors.put("memoryUtilizationData", info -> UnitChangeUtil.formatDecimal(info.getCollectValue()));
+        extractors.put("memoryUsedData", info -> info.getMemUsed());

        return EchartsDataUtils.buildEchartsData(list, InitialSystemOtherCollectData::getCreateTime, extractors);
    }
@@ -139,4 +139,20 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
        AND d.create_time = latest.max_time
        AND d.collect_type='memorySizeTotalCollect'
    </select>
+    <select id="getMemTotalSizeNoConvert" parameterType="String" resultType="String">
+        select
+            d.collect_value  as memTotalSize
+        FROM ${tableName} d
+                 INNER JOIN (
+            SELECT
+                client_id,
+                MAX(create_time) as max_time
+            FROM ${tableName}
+            WHERE collect_type='memorySizeTotalCollect'
+              AND client_id = #{clientId}
+            GROUP BY client_id
+        ) latest ON d.client_id = latest.client_id
+            AND d.create_time = latest.max_time
+            AND d.collect_type='memorySizeTotalCollect'
+    </select>
 </mapper>