package com.tongchuang.realtime.mds;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import com.tongchuang.realtime.bean.ULEParamConfig;
import com.tongchuang.realtime.util.KafkaUtils;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.state.;
import org.apache.flink.api.common.time.Time;
import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
import org.apache.flink.api.common.typeinfo.TypeHint;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.connector.kafka.source.KafkaSource;
import org.apache.flink.connector.kafka.source.enumerator.initializer.OffsetsInitializer;
import org.apache.flink.streaming.api.datastream.;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.co.KeyedBroadcastProcessFunction;
import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
import org.apache.flink.util.Collector;
import org.apache.flink.util.OutputTag;
import java.io.Serializable;
import java.sql.;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.time.Duration;
import java.util.;
import java.util.Date;
import java.util.concurrent.TimeUnit;
public class ULEDataanomalyanalysis {
public static void main(String[] args) throws Exception { final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); env.setParallelism(1); env.getConfig().setAutoWatermarkInterval(1000); // Kafka消费者配置 KafkaSource kafkaConsumer = KafkaUtils.getKafkaConsumer( “realdata_minute”, “minutedata_uledataanomalyanalysis”, OffsetsInitializer.latest() ); // 修改Watermark策略 DataStreamSource kafkaDS = env.fromSource( kafkaConsumer, WatermarkStrategy.forBoundedOutOfOrderness(Duration.ofMinutes(1)) .withTimestampAssigner((event, timestamp) -> { try { JSONObject json = JSON.parseObject(event); return new SimpleDateFormat(“yyyy-MM-dd HH:mm”).parse(json.getString(“times”)).getTime(); } catch (ParseException e) { return System.currentTimeMillis(); } }), “realdata_uledataanomalyanalysis” ); kafkaDS.print(“分钟数据流”); // 解析JSON并拆分tag SingleOutputStreamOperator splitStream = kafkaDS .map(JSON::parseObject) .returns(TypeInformation.of(JSONObject.class)) .flatMap((JSONObject value, Collector out) -> { JSONObject data = value.getJSONObject(“datas”); String time = value.getString(“times”); for (String tag : data.keySet()) { JSONObject tagData = data.getJSONObject(tag); JSONObject newObj = new JSONObject(); newObj.put(“time”, time); newObj.put(“tag”, tag); newObj.put(“ontime”, tagData.getDouble(“ontime”)); newObj.put(“avg”, tagData.getDouble(“avg”)); out.collect(newObj); } }) .returns(TypeInformation.of(JSONObject.class)) .name(“Split-By-Tag”); // 配置数据源 DataStream configDataStream = env .addSource(new MysqlConfigSource()) .setParallelism(1) .filter(Objects::nonNull) .name(“Config-Source”); // 标签值数据流 DataStream<Map<String, Object>> tagValueStream = splitStream .map(json -> { Map<String, Object> valueMap = new HashMap<>(); valueMap.put(“tag”, json.getString(“tag”)); valueMap.put(“value”, “436887485805570949”.equals(json.getString(“datatype”)) ? json.getDouble(“ontime”) : json.getDouble(“avg”)); return valueMap; }) .returns(new TypeHint<Map<String, Object>>() {}) .name(“Tag-Value-Stream”); // 合并配置流和标签值流 DataStreambroadcastStream = configDataStream .map(config -> (Object) config) .returns(TypeInformation.of(Object.class)) .union( tagValueStream.map(tagValue -> (Object) tagValue) .returns(TypeInformation.of(Object.class)) ); // 广播流 BroadcastStreamfinalBroadcastStream = broadcastStream .broadcast(Descriptors.configStateDescriptor, Descriptors.tagValuesDescriptor); // 按tag分组 KeyedStream<JSONObject, String> keyedStream = splitStream .keyBy(json -> json.getString(“tag”)); BroadcastConnectedStream<JSONObject, Object> connectedStream = keyedStream.connect(finalBroadcastStream); // 异常检测处理 SingleOutputStreamOperator anomalyStream = connectedStream .process(new OptimizedAnomalyDetectionFunction()) .name(“Anomaly-Detection”); anomalyStream.print(“异常检测结果”); // 离线检测结果侧输出 DataStream offlineCheckStream = anomalyStream.getSideOutput(OptimizedAnomalyDetectionFunction.OFFLINE_CHECK_TAG); offlineCheckStream.print(“离线检测结果”); env.execute(“uledataanomalyanalysis”); } // 配置集合类 public static class ConfigCollection implements Serializable { private static final long serialVersionUID = 1L; public final Map<String, List> tagToConfigs; public final Map<String, ULEParamConfig> encodeToConfig; public final Set allTags; public final long checkpointTime; public ConfigCollection(Map<String, List> tagToConfigs, Map<String, ULEParamConfig> encodeToConfig) { this.tagToConfigs = new HashMap<>(tagToConfigs); this.encodeToConfig = new HashMap<>(encodeToConfig); this.allTags = new HashSet<>(tagToConfigs.keySet()); this.checkpointTime = System.currentTimeMillis(); } } // MySQL配置源 public static class MysqlConfigSource extends RichSourceFunction { private volatile boolean isRunning = true; private final long interval = TimeUnit.MINUTES.toMillis(5); @Override public void run(SourceContext ctx) throws Exception { while (isRunning) { ConfigCollection newConfig = loadParams(); if (newConfig != null) { ctx.collect(newConfig); System.out.println("配置加载完成，检查点时间: " + new Date(newConfig.checkpointTime)); } else { System.out.println(“配置加载失败”); } Thread.sleep(interval); } } private ConfigCollection loadParams() { Map<String, List> tagToConfigs = new HashMap<>(5000); Map<String, ULEParamConfig> encodeToConfig = new HashMap<>(5000); String url = “jdbc:mysql://10.51.37.73:3306/eps?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8”; String user = “root”; String password = “6CKIm5jDVsLrahSw”; String query = "SELECT F_tag AS tag, F_enCode AS encode, F_dataTypes AS datatype, " + "F_isConstantValue AS constantvalue, F_isOnline AS isonline, " + "F_isSync AS issync, F_syncParaEnCode AS syncparaencode, " + "F_isZero AS iszero, F_isHigh AS ishigh, F_highThreshold AS highthreshold, " + "F_isLow AS islow, F_lowThreshold AS lowthreshold, F_duration AS duration " + "FROM t_equipmentparameter " + "WHERE F_enabledmark = ‘1’ AND (F_isConstantValue=‘1’ OR F_isZero=‘1’ " + “OR F_isHigh=‘1’ OR F_isLow=‘1’ OR F_isOnline=‘1’ OR F_isSync=‘1’)”; try (Connection conn = DriverManager.getConnection(url, user, password); Statement stmt = conn.createStatement(); ResultSet rs = stmt.executeQuery(query)) { while (rs.next()) { ULEParamConfig config = new ULEParamConfig(); config.tag = rs.getString(“tag”); config.encode = rs.getString(“encode”); config.datatype = rs.getString(“datatype”); config.constantvalue = rs.getInt(“constantvalue”); config.iszero = rs.getInt(“iszero”); config.ishigh = rs.getInt(“ishigh”); config.highthreshold = rs.getDouble(“highthreshold”); config.islow = rs.getInt(“islow”); config.lowthreshold = rs.getDouble(“lowthreshold”); config.duration = rs.getLong(“duration”); config.isonline = rs.getInt(“isonline”); config.issync = rs.getInt(“issync”); config.syncparaencode = rs.getString(“syncparaencode”); if (config.encode == null || config.encode.isEmpty()) { System.err.println(“忽略无效配置: 空encode”); continue; } String tag = config.tag; tagToConfigs.computeIfAbsent(tag, k -> new ArrayList<>(10)).add(config); encodeToConfig.put(config.encode, config); } System.out.println(“加载配置: " + encodeToConfig.size() + " 个参数”); return new ConfigCollection(tagToConfigs, encodeToConfig); } catch (SQLException e) { System.err.println(“加载参数配置错误:”); e.printStackTrace(); return null; } } @Override public void cancel() { isRunning = false; } } // 状态描述符 public static class Descriptors { public static final MapStateDescriptor<Void, ConfigCollection> configStateDescriptor = new MapStateDescriptor<>( “configState”, TypeInformation.of(Void.class), TypeInformation.of(ConfigCollection.class) ); public static final MapStateDescriptor<String, Double> tagValuesDescriptor = new MapStateDescriptor<>( “tagValuesBroadcastState”, BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO ); } // 优化后的异常检测函数（已修复离线检测问题） public static class OptimizedAnomalyDetectionFunction extends KeyedBroadcastProcessFunction<String, JSONObject, Object, JSONObject> { public static final OutputTag OFFLINE_CHECK_TAG = new OutputTag(“offline-check”){}; // 状态管理 private transient MapState<String, AnomalyState> stateMap; private transient MapState<String, Double> lastValuesMap; private transient MapState<String, Long> lastDataTimeMap; private transient MapState<String, Long> offlineTimerState; private transient MapState<String, Long> tagInitTimeState; // 标签初始化时间状态 private transient SimpleDateFormat timeFormat; private transient long lastSyncLogTime = 0; @Override public void open(Configuration parameters) { StateTtlConfig ttlConfig = StateTtlConfig.newBuilder(Time.days(30)) .setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite) .setStateVisibility(StateTtlConfig.StateVisibility.NeverReturnExpired) .cleanupFullSnapshot() .build(); // 异常状态存储 MapStateDescriptor<String, AnomalyState> stateDesc = new MapStateDescriptor<>( “anomalyState”, BasicTypeInfo.STRING_TYPE_INFO, TypeInformation.of(AnomalyState.class) ); stateDesc.enableTimeToLive(ttlConfig); stateMap = getRuntimeContext().getMapState(stateDesc); // 最新值存储 MapStateDescriptor<String, Double> valuesDesc = new MapStateDescriptor<>( “lastValuesState”, BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO ); valuesDesc.enableTimeToLive(ttlConfig); lastValuesMap = getRuntimeContext().getMapState(valuesDesc); // 最后数据时间存储 MapStateDescriptor<String, Long> timeDesc = new MapStateDescriptor<>( “lastDataTimeState”, BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO ); timeDesc.enableTimeToLive(ttlConfig); lastDataTimeMap = getRuntimeContext().getMapState(timeDesc); // 离线检测定时器状态 MapStateDescriptor<String, Long> timerDesc = new MapStateDescriptor<>( “offlineTimerState”, BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO ); timerDesc.enableTimeToLive(ttlConfig); offlineTimerState = getRuntimeContext().getMapState(timerDesc); // 标签初始化时间状态 MapStateDescriptor<String, Long> initTimeDesc = new MapStateDescriptor<>( “tagInitTimeState”, BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO ); initTimeDesc.enableTimeToLive(ttlConfig); tagInitTimeState = getRuntimeContext().getMapState(initTimeDesc); timeFormat = new SimpleDateFormat(“yyyy-MM-dd HH:mm”); } @Override public void processElement(JSONObject data, ReadOnlyContext ctx, Collector out) throws Exception { String tag = ctx.getCurrentKey(); String timeStr = data.getString(“time”); long eventTime = timeFormat.parse(timeStr).getTime(); // 更新最后数据时间 lastDataTimeMap.put(tag, eventTime); // 获取广播配置 ConfigCollection configCollection = getBroadcastConfig(ctx); if (configCollection == null) return; List configs = configCollection.tagToConfigs.get(tag); if (configs == null || configs.isEmpty()) return; // 清理无效状态 List keysToRemove = new ArrayList<>(); for (String encode : stateMap.keys()) { boolean found = false; for (ULEParamConfig cfg : configs) { if (cfg.encode.equals(encode)) { found = true; break; } } if (!found) { System.out.println("清理过期状态: " + encode); keysToRemove.add(encode); } } for (String encode : keysToRemove) { stateMap.remove(encode); } double value = 0; boolean valueSet = false; // 检查是否需要离线检测 boolean hasOnlineConfig = false; long minDuration = Long.MAX_VALUE; for (ULEParamConfig config : configs) { if (config.isonline == 1) { hasOnlineConfig = true; minDuration = Math.min(minDuration, config.duration); // 初始化标签检测时间（如果尚未初始化） if (!tagInitTimeState.contains(tag)) { tagInitTimeState.put(tag, System.currentTimeMillis()); System.out.println(“初始化在线检测: tag=” + tag + “, 时间=” + timeFormat.format(new Date())); } } } // 管理离线检测定时器 if (hasOnlineConfig) { // 删除现有定时器 Long currentTimer = offlineTimerState.get(tag); if (currentTimer != null) { ctx.timerService().deleteEventTimeTimer(currentTimer); } // 注册新定时器（使用最小duration） long offlineTimeout = eventTime + minDuration * 60 * 1000; ctx.timerService().registerEventTimeTimer(offlineTimeout); offlineTimerState.put(tag, offlineTimeout); // 重置离线状态（数据到达表示恢复） for (ULEParamConfig config : configs) { if (config.isonline == 1) { AnomalyState state = getOrCreateState(config.encode); AnomalyStatus status = state.getStatus(6); if (status.reported) { reportAnomaly(6, 0, 0.0, timeStr, config, out); status.reset(); stateMap.put(config.encode, state); System.out.println(“离线恢复: tag=” + tag + “, encode=” + config.encode); } } } } // 遍历配置项进行异常检测 for (ULEParamConfig config : configs) { if (!valueSet) { value = “436887485805570949”.equals(config.datatype) ? data.getDouble(“ontime”) : data.getDouble(“avg”); lastValuesMap.put(tag, value); valueSet = true; } AnomalyState state = getOrCreateState(config.encode); // 处理异常类型 checkConstantValueAnomaly(config, value, timeStr, state, out); // 1. 恒值检测 checkZeroValueAnomaly(config, value, timeStr, state, out); // 2. 零值检测 checkThresholdAnomaly(config, value, timeStr, state, out); // 3. 上阈值, 4. 下阈值 checkSyncAnomaly(config, value, timeStr, state, configCollection, ctx, out); // 5. 同步检测 stateMap.put(config.encode, state); } } @Override public void onTimer(long timestamp, OnTimerContext ctx, Collector out) throws Exception { String tag = ctx.getCurrentKey(); Long lastEventTime = lastDataTimeMap.get(tag); ConfigCollection configCollection = getBroadcastConfig(ctx); if (configCollection == null) return; List configs = configCollection.tagToConfigs.get(tag); if (configs == null) return; // 检查所有需要离线检测的配置项 boolean hasOnlineConfig = false; for (ULEParamConfig config : configs) { if (config.isonline == 1) { hasOnlineConfig = true; AnomalyState state = getOrCreateState(config.encode); AnomalyStatus status = state.getStatus(6); // 处理从未收到数据的情况 if (lastEventTime == null) { // 获取标签初始化时间 Long initTime = tagInitTimeState.get(tag); if (initTime == null) { // 如果状态中不存在，使用配置加载时间 initTime = configCollection.checkpointTime; tagInitTimeState.put(tag, initTime); } // 检查是否超过配置的duration long elapsed = System.currentTimeMillis() - initTime; long durationMs = config.duration * 60 * 1000; if (elapsed >= durationMs) { if (!status.reported) { String triggerTime = timeFormat.format(new Date()); reportAnomaly(6, 1, 0.0, triggerTime, config, out); status.reported = true; // 输出到侧输出流 ctx.output(OFFLINE_CHECK_TAG, String.format(“离线异常(从未收到数据): tag=%s, encode=%s, 初始化时间=%s, 当前时间=%s, 时间差=%dms (阈值=%dms)”, config.tag, config.encode, timeFormat.format(new Date(initTime)), triggerTime, elapsed, durationMs) ); System.out.println("检测到从未接收数据的离线异常: " + config.tag); } } } // 处理已有数据但超时的情况 else if (timestamp - lastEventTime >= config.duration * 60 * 1000) { if (!status.reported) { String triggerTime = timeFormat.format(new Date(timestamp)); reportAnomaly(6, 1, 0.0, triggerTime, config, out); status.reported = true; ctx.output(OFFLINE_CHECK_TAG, String.format(“离线异常: tag=%s, encode=%s, 最后数据时间=%s, 超时时间=%s, 时间差=%dms (阈值=%dms)”, config.tag, config.encode, timeFormat.format(new Date(lastEventTime)), triggerTime, timestamp - lastEventTime, config.duration * 60 * 1000) ); System.out.println("检测到数据中断的离线异常: " + config.tag); } } else { // 数据已恢复，重置状态 if (status.reported) { reportAnomaly(6, 0, 0.0, timeFormat.format(new Date()), config, out); status.reset(); System.out.println("离线状态恢复: " + config.tag); } } stateMap.put(config.encode, state); } } // 重新注册定时器（每分钟检查一次） if (hasOnlineConfig) { long newTimeout = timestamp + TimeUnit.MINUTES.toMillis(1); ctx.timerService().registerEventTimeTimer(newTimeout); offlineTimerState.put(tag, newTimeout); } else { offlineTimerState.remove(tag); } } // 恒值检测 - 异常类型1 private void checkConstantValueAnomaly(ULEParamConfig config, double currentValue, String timeStr, AnomalyState state, Collector out) { if (config.constantvalue != 1) return; try { AnomalyStatus status = state.getStatus(1); long durationThreshold = config.duration * 60 * 1000; Date timestamp = timeFormat.parse(timeStr); if (status.lastValue == null) { status.lastValue = currentValue; status.lastChangeTime = timestamp; return; } if (Math.abs(currentValue - status.lastValue) > 0.001) { status.lastValue = currentValue; status.lastChangeTime = timestamp; if (status.reported) { reportAnomaly(1, 0, currentValue, timeStr, config, out); } status.reset(); return; } long elapsed = timestamp.getTime() - status.lastChangeTime.getTime(); if (elapsed > durationThreshold) { if (!status.reported) { reportAnomaly(1, 1, currentValue, timeStr, config, out); status.reported = true; } } } catch (Exception e) { System.err.println("恒值检测错误: " + config.encode + " - " + e.getMessage()); } } // 零值检测 - 异常类型2 private void checkZeroValueAnomaly(ULEParamConfig config, double currentValue, String timeStr, AnomalyState state, Collector out) { if (config.iszero != 1) return; try { AnomalyStatus status = state.getStatus(2); Date timestamp = timeFormat.parse(timeStr); boolean isZero = Math.abs(currentValue) < 0.001; if (isZero) { if (status.startTime == null) { status.startTime = timestamp; } else if (!status.reported) { long elapsed = timestamp.getTime() - status.startTime.getTime(); if (elapsed >= config.duration * 60 * 1000) { reportAnomaly(2, 1, currentValue, timeStr, config, out); status.reported = true; } } } else { if (status.reported) { reportAnomaly(2, 0, currentValue, timeStr, config, out); status.reset(); } else if (status.startTime != null) { status.startTime = null; } } } catch (Exception e) { System.err.println("零值检测错误: " + config.encode + " - " + e.getMessage()); } } // 阈值检测 - 异常类型3(上阈值)和4(下阈值) private void checkThresholdAnomaly(ULEParamConfig config, double currentValue, String timeStr, AnomalyState state, Collector out) { try { if (config.ishigh == 1) { AnomalyStatus highStatus = state.getStatus(3); processThresholdAnomaly(highStatus, currentValue, timeStr, currentValue > config.highthreshold, config, 3, out); } if (config.islow == 1) { AnomalyStatus lowStatus = state.getStatus(4); processThresholdAnomaly(lowStatus, currentValue, timeStr, currentValue < config.lowthreshold, config, 4, out); } } catch (Exception e) { System.err.println("阈值检测错误: " + config.encode + " - " + e.getMessage()); } } private void processThresholdAnomaly(AnomalyStatus status, double currentValue, String timeStr, boolean isAnomaly, ULEParamConfig config, int anomalyType, Collector out) { try { Date timestamp = timeFormat.parse(timeStr); if (isAnomaly) { if (status.startTime == null) { status.startTime = timestamp; } else if (!status.reported) { long elapsed = timestamp.getTime() - status.startTime.getTime(); if (elapsed >= config.duration * 60 * 1000) { reportAnomaly(anomalyType, 1, currentValue, timeStr, config, out); status.reported = true; } } } else { if (status.reported) { reportAnomaly(anomalyType, 0, currentValue, timeStr, config, out); status.reset(); } else if (status.startTime != null) { status.startTime = null; } } } catch (Exception e) { System.err.println("阈值处理错误:极速版 " + config.encode + " - " + e.getMessage()); } } // 同步检测 - 异常类型5（优化日志输出） private void checkSyncAnomaly(ULEParamConfig config, double currentValue, String timeStr, AnomalyState state, ConfigCollection configCollection, ReadOnlyContext ctx, Collector out) { if (config.issync != 1 || config.syncparaencode == null || config.syncparaencode.isEmpty()) { return; } try { // 通过encode获取关联配置 ULEParamConfig relatedConfig = configCollection.encodeToConfig.get(config.syncparaencode); if (relatedConfig == null) { if (System.currentTimeMillis() - lastSyncLogTime > 60000) { System.out.println(“同步检测错误: 未找到关联配置, encode=” + config.syncparaencode); lastSyncLogTime = System.currentTimeMillis(); } return; } // 获取关联配置的tag String relatedTag = relatedConfig.tag; if (relatedTag == null || relatedTag.isEmpty()) { if (System.currentTimeMillis() - lastSyncLogTime > 60000) { System.out.println(“同步检测错误: 关联配置没有tag, encode=” + config.syncparaencode); lastSyncLogTime = System.currentTimeMillis(); } return; } // 从广播状态获取关联值 ReadOnlyBroadcastState<String, Double> tagValuesState = ctx.getBroadcastState(Descriptors.tagValuesDescriptor); Double relatedValue = tagValuesState.get(relatedTag); if (relatedValue == null) { if (System.currentTimeMillis() - lastSyncLogTime > 60000) { // 优化日志：添加当前标签信息 System.out.printf(“同步检测警告: 关联值未初始化 [主标签=%s(%s), 关联标签=%s(%s)]%n”, config.tag, config.encode, relatedTag, config.syncparaencode); lastSyncLogTime = System.currentTimeMillis(); } return; } // 同步检测逻辑 AnomalyStatus status = state.getStatus(5); Date timestamp = timeFormat.parse(timeStr); // 业务逻辑：当前值接近1且关联值接近0时异常 boolean isAnomaly = (currentValue >= 0.99) && (Math.abs(relatedValue) < 0.01); // 日志记录 if (System.currentTimeMillis() - lastSyncLogTime > 60000) { System.out.printf(“同步检测: %s (%.4f) vs %s (%.4f) -> %b%n”, config.tag, currentValue, relatedTag, relatedValue, isAnomaly); lastSyncLogTime = System.currentTimeMillis(); } // 处理异常状态 if (isAnomaly) { if (status.startTime == null) { status.startTime = timestamp; } else if (!status.reported) { long elapsed = timestamp.getTime() - status.startTime.getTime(); if (elapsed >= config.duration * 60 * 1000) { reportAnomaly(5, 1, currentValue, timeStr, config, out); status.reported = true; } } } else { if (status.reported) { reportAnomaly(5, 0, currentValue, timeStr, config, out); status.reset(); } else if (status.startTime != null) { status.startTime = null; } } } catch (ParseException e) { System.err.println("同步检测时间解析错误: " + config.encode + " - " + e.getMessage()); } catch (Exception e) { System.err.println("同步检测错误: " + config.encode + " - " + e.getMessage()); } } // 报告异常（添加详细日志） private void reportAnomaly(int anomalyType, int statusFlag, double value, String time, ULEParamConfig config, Collector out) { JSONObject event = new JSONObject(); event.put(“tag”, config.tag); event.put(“paracode”, config.encode); event.put(“abnormaltype”, anomalyType); event.put(“statusflag”, statusFlag); event.put(“datavalue”, value); event.put(“triggertime”, time); out.collect(event); // 添加详细日志输出 String statusDesc = statusFlag == 1 ? “异常开始” : “异常结束”; System.out.printf(“报告异常: 类型=%d, 状态=%s, 标签=%s, 编码=%s, 时间=%s%n”, anomalyType, statusDesc, config.tag, config.encode, time); } @Override public void processBroadcastElement(Object broadcastElement, Context ctx, Collector out) throws Exception { // 处理配置更新 if (broadcastElement instanceof ConfigCollection) { ConfigCollection newConfig = (ConfigCollection) broadcastElement; BroadcastState<Void, ConfigCollection> configState = ctx.getBroadcastState(Descriptors.configStateDescriptor); // 获取旧配置 ConfigCollection oldConfig = configState.get(null); // 处理配置变更：清理不再启用的报警 if (oldConfig != null) { for (Map.Entry<String, ULEParamConfig> entry : oldConfig.encodeToConfig.entrySet()) { String encode = entry.getKey(); ULEParamConfig oldCfg = entry.getValue(); ULEParamConfig newCfg = newConfig.encodeToConfig.get(encode); if (newCfg == null || !isAlarmEnabled(newCfg, oldCfg)) { // 发送恢复事件 sendRecoveryEvents(encode, oldCfg, ctx, out); } } } // 更新广播状态 configState.put(null, newConfig); System.out.println("广播配置更新完成, 配置项: " + newConfig.encodeToConfig.size()); } // 处理标签值更新 else if (broadcastElement instanceof Map) { @SuppressWarnings(“unchecked”) Map<String, Object> tagValue = (Map<String, Object>) broadcastElement; String tag = (String) tagValue.get(“tag”); Double value = (Double) tagValue.get(“value”); if (tag != null && value != null) { BroadcastState<String, Double> tagValuesState = ctx.getBroadcastState(Descriptors.tagValuesDescriptor); tagValuesState.put(tag, value); } } } // 检查报警是否启用 private boolean isAlarmEnabled(ULEParamConfig newCfg, ULEParamConfig oldCfg) { return (oldCfg.constantvalue == 1 && newCfg.constantvalue == 1) || (oldCfg.iszero == 1 && newCfg.iszero == 1) || (oldCfg.ishigh == 1 && newCfg.ishigh == 1) || (oldCfg.islow == 1 && newCfg.islow == 1) || (oldCfg.isonline == 1 && newCfg.isonline == 1) || (oldCfg.issync == 1 && newCfg.issync == 1); } // 发送恢复事件 private void sendRecoveryEvents(String encode, ULEParamConfig config, Context ctx, Collector out) { try { AnomalyState state = stateMap.get(encode); if (state == null) return; // 遍历所有可能的报警类型 for (int type = 1; type <= 6; type++) { AnomalyStatus status = state.getStatus(type); if (status.reported) { JSONObject recoveryEvent = new JSONObject(); recoveryEvent.put(“tag”, config.tag); recoveryEvent.put(“paracode”, config.encode); recoveryEvent.put(“abnormaltype”, type); recoveryEvent.put(“statusflag”, 0); // 恢复事件 recoveryEvent.put(“datavalue”, 0.0); recoveryEvent.put(“triggertime”, timeFormat.format(new Date())); out.collect(recoveryEvent); System.out.println(“发送恢复事件: 类型=” + type + “, 标签=” + config.tag); status.reset(); } } // 更新状态 stateMap.put(encode, state); } catch (Exception e) { System.err.println("发送恢复事件失败: " + e.getMessage()); } } // 辅助方法 private ConfigCollection getBroadcastConfig(ReadOnlyContext ctx) throws Exception { return ctx.getBroadcastState(Descriptors.configStateDescriptor).get(null); } private AnomalyState getOrCreateState(String encode) throws Exception { AnomalyState state = stateMap.get(encode); if (state == null) { state = new AnomalyState(); } return state; } } // 异常状态类 public static class AnomalyState implements Serializable { private static final long serialVersionUID = 1L; private final Map<Integer, AnomalyStatus> statusMap = new HashMap<>(); public AnomalyStatus getStatus(int type) { return statusMap.computeIfAbsent(type, k -> new AnomalyStatus()); } } // 异常状态详情 public static class AnomalyStatus implements Serializable { private static final long serialVersionUID = 1L; public Date startTime; // 异常开始时间 public Double lastValue; // 用于恒值检测 public Date lastChangeTime; // 值最后变化时间 public boolean reported; // 是否已报告 public void reset() { startTime = null; lastValue = null; lastChangeTime = null; reported = false; } }
}
运行日志为：“C:\Program Files (x86)\Java\jdk1.8.0_102\bin\java.exe” -agentlib:jdwp=transport=dt_socket,address=127.0.0.1:21889,suspend=y,server=n -javaagent:C:\Users\Administrator\AppData\Local\JetBrains\IntelliJIdea2021.2\captureAgent\debugger-agent.jar=file:/C:/Users/Administrator/AppData/Local/Temp/capture.props -Dfile.encoding=UTF-8 -classpath C:\Users\Administrator\AppData\Local\Temp\classpath739647490.jar com.tongchuang.realtime.mds.ULEDataanomalyanalysis
已连接到目标 VM, 地址: ‘‘127.0.0.1:21889’，传输: ‘套接字’’
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/F:/flink/flinkmaven/repository/org/apache/logging/log4j/log4j-slf4j-impl/2.10.0/log4j-slf4j-impl-2.10.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/F:/flink/flinkmaven/repository/org/slf4j/slf4j-log4j12/1.7.25/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
加载配置: 30 个参数
配置加载完成，检查点时间: Wed Aug 06 08:06:53 CST 2025
广播配置更新完成, 配置项: 30
分钟数据流> {“times”:“2025-08-06 08:06”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3028.0762,“avg”:3002.0539,“min”:2943.5588,“max”:3055.423},“DA-LT-6BT008”:{“ontime”:182.708,“avg”:184.5047,“min”:182.708,“max”:186.0057},“DA-LT-5BT0005”:{“ontime”:408.72,“avg”:409.09,“min”:408.72,“max”:409.5},“DA-LT-6BT004”:{“ontime”:1211.9675,“avg”:1211.8802,“min”:1211.6671,“max”:1212.0676},“DA-LT-5BT0004”:{“ontime”:1196.8,“avg”:1197.8467,“min”:1196.8,“max”:1198.9},“DA-LT-6BT005”:{“ontime”:401.0593,“avg”:401.0972,“min”:400.8238,“max”:401.4126},“DA-LT-5BT0008”:{“ontime”:191.24,“avg”:191.4387,“min”:190.88,“max”:193.04},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:134.125,“avg”:133.6627,“min”:133.0,“max”:134.6625},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1210.0,“avg”:1209.2167,“min”:1209.0,“max”:1210.0},“DA-LT-6BT001”:{“ontime”:178782.56,“avg”:178583.6142,“min”:177692.36,“max”:179265.8},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:302.125,“avg”:302.4458,“min”:301.25,“max”:303.5625},“DA_DB195_RH_R_0281”:{“ontime”:407.41,“avg”:407.1857,“min”:363.58,“max”:465.25},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:128130.79,“avg”:125782.1916,“min”:122764.53,“max”:129377.766}}}
初始化在线检测: tag=DA-LT-5BT0001, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-6BT008, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-5BT0005, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-6BT004, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-5BT0004, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-6BT005, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-5BT0008, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-4BT0008, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-4BT0004, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-6BT001, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-LT-4BT0005, 时间=2025-08-06 08:07
初始化在线检测: tag=DA_DB195_RH_R_0281, 时间=2025-08-06 08:07
初始化在线检测: tag=DA-DB195-RH-B-0201, 时间=2025-08-06 08:07
同步检测警告: 关联值未初始化 [主标签=DA-DB195-RH-B-0201(EP000001), 关联标签=DA-LT-4BT0007(EP000022)]
初始化在线检测: tag=DA-LT-4BT0001, 时间=2025-08-06 08:07
分钟数据流> {“times”:“2025-08-06 08:07”,“datas”:{“DA-LT-5BT0001”:{“ontime”:2983.723,“avg”:2998.5335,“min”:2933.6702,“max”:3050.6917},“DA-LT-6BT008”:{“ontime”:183.4736,“avg”:182.5906,“min”:182.0799,“max”:183.4736},“DA-LT-5BT0005”:{“ontime”:409.5,“avg”:411.009,“min”:409.5,“max”:412.02},“DA-LT-5BT0004”:{“ontime”:1198.8,“avg”:1200.8084,“min”:1198.8,“max”:1202.6},“DA-LT-6BT004”:{“ontime”:1211.6671,“avg”:1211.3646,“min”:1211.1666,“max”:1211.7673},“DA-LT-6BT005”:{“ontime”:401.5108,“avg”:402.1448,“min”:401.5108,“max”:402.7081},“DA-LT-5BT0008”:{“ontime”:191.18,“avg”:192.5137,“min”:190.98,“max”:193.82},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:133.75,“avg”:133.5158,“min”:128.8375,“max”:138.0625},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1209.0,“avg”:1208.5333,“min”:1208.0,“max”:1209.0},“DA-LT-6BT001”:{“ontime”:178991.39,“avg”:178253.286,“min”:177076.5,“max”:179702.92},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:302.25,“avg”:302.6656,“min”:298.4375,“max”:307.75},“DA_DB195_RH_R_0281”:{“ontime”:418.74,“avg”:386.4635,“min”:318.91,“max”:493.5399},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:123272.95,“avg”:126419.8397,“min”:120245.72,“max”:130466.016},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
异常检测结果> {“abnormaltype”:3,“paracode”:“EP100010”,“datavalue”:178253.286,“tag”:“DA-LT-6BT001”,“triggertime”:“2025-08-06 08:07”,“statusflag”:1}
报告异常: 类型=3, 状态=异常开始, 标签=DA-LT-6BT001, 编码=EP100010, 时间=2025-08-06 08:07
异常检测结果> {“abnormaltype”:3,“paracode”:“EP000010”,“datavalue”:178253.286,“tag”:“DA-LT-6BT001”,“triggertime”:“2025-08-06 08:07”,“statusflag”:1}
报告异常: 类型=3, 状态=异常开始, 标签=DA-LT-6BT001, 编码=EP000010, 时间=2025-08-06 08:07
异常检测结果> {“abnormaltype”:3,“paracode”:“EP000002”,“datavalue”:126419.8397,“tag”:“DA-LT-4BT0001”,“triggertime”:“2025-08-06 08:07”,“statusflag”:1}
报告异常: 类型=3, 状态=异常开始, 标签=DA-LT-4BT0001, 编码=EP000002, 时间=2025-08-06 08:07
异常检测结果> {“abnormaltype”:4,“paracode”:“EP000001”,“datavalue”:1.0,“tag”:“DA-DB195-RH-B-0201”,“triggertime”:“2025-08-06 08:07”,“statusflag”:1}
报告异常: 类型=4, 状态=异常开始, 标签=DA-DB195-RH-B-0201, 编码=EP000001, 时间=2025-08-06 08:07
分钟数据流> {“times”:“2025-08-06 08:08”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3042.6296,“avg”:3003.8981,“min”:2967.8362,“max”:3055.9065},“DA-LT-6BT008”:{“ontime”:182.3939,“avg”:183.4896,“min”:182.3939,“max”:185.3776},“DA-LT-5BT0005”:{“ontime”:411.96,“avg”:412.596,“min”:411.84,“max”:413.04},“DA-LT-5BT0004”:{“ontime”:1202.8,“avg”:1203.81,“min”:1202.8,“max”:1204.6},“DA-LT-6BT004”:{“ontime”:1211.2,“avg”:1211.1372,“min”:1211.0332,“max”:1211.2667},“DA-LT-6BT005”:{“ontime”:402.3745,“avg”:402.7078,“min”:402.3548,“max”:402.9437},“DA-LT-5BT0008”:{“ontime”:193.76,“avg”:195.1453,“min”:193.72,“max”:197.06},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.9333,“min”:0.0,“max”:1.0},“DA-LT-4BT0008”:{“ontime”:137.3625,“avg”:139.1331,“min”:137.225,“max”:140.85},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1209.0,“avg”:1209.8,“min”:1209.0,“max”:1211.0},“DA-LT-6BT001”:{“ontime”:178882.36,“avg”:178488.8015,“min”:177432.6,“max”:179877.9},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.75,“min”:0.0,“max”:1.0},“DA-LT-4BT0005”:{“ontime”:307.5625,“avg”:309.2396,“min”:307.5625,“max”:310.75},“DA_DB195_RH_R_0281”:{“ontime”:396.59,“avg”:401.5442,“min”:346.05,“max”:450.32},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:121446.11,“avg”:119290.5578,“min”:117657.12,“max”:122175.7},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
异常检测结果> {“abnormaltype”:1,“paracode”:“EP000001”,“datavalue”:1.0,“tag”:“DA-DB195-RH-B-0201”,“triggertime”:“2025-08-06 08:08”,“statusflag”:1}
报告异常: 类型=1, 状态=异常开始, 标签=DA-DB195-RH-B-0201, 编码=EP000001, 时间=2025-08-06 08:08
同步检测警告: 关联值未初始化 [主标签=DA-DB195-RH-B-0201(EP000001), 关联标签=DA-LT-4BT0007(EP000022)]
分钟数据流> {“times”:“2025-08-06 08:09”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3033.7747,“avg”:3002.4513,“min”:2962.6672,“max”:3055.1338},“DA-LT-6BT008”:{“ontime”:185.3776,“avg”:184.3745,“min”:183.5324,“max”:185.672},“DA-LT-5BT0005”:{“ontime”:412.86,“avg”:412.575,“min”:412.14,“max”:412.86},“DA-LT-6BT004”:{“ontime”:1211.0665,“avg”:1210.6939,“min”:1210.2991,“max”:1211.0999},“DA-LT-5BT0004”:{“ontime”:1204.6,“avg”:1205.0734,“min”:1204.6,“max”:1205.7001},“DA-LT-6BT005”:{“ontime”:402.3352,“avg”:402.9368,“min”:402.2763,“max”:403.6503},“DA-LT-5BT0008”:{“ontime”:196.7,“avg”:195.9777,“min”:195.26,“max”:196.7},“DA-NY-LG1ZL-2-001”:{“ontime”:1.0,“avg”:0.9333,“min”:0.0,“max”:1.0},“DA-LT-4BT0008”:{“ontime”:139.5875,“avg”:140.9713,“min”:139.5875,“max”:142.825},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1211.0,“avg”:1211.75,“min”:1211.0,“max”:1212.0},“DA-LT-6BT001”:{“ontime”:178391.67,“avg”:178443.7467,“min”:177628.52,“max”:179565.55},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:309.6875,“avg”:310.8229,“min”:309.5,“max”:312.625},“DA_DB195_RH_R_0281”:{“ontime”:450.32,“avg”:408.5857,“min”:379.12,“max”:450.32},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:118694.516,“avg”:118275.7408,“min”:117089.89,“max”:120421.92},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
同步检测警告: 关联值未初始化 [主标签=DA-DB195-RH-B-0201(EP000001), 关联标签=DA-LT-4BT0007(EP000022)]
分钟数据流> {“times”:“2025-08-06 08:10”,“datas”:{“DA-LT-5BT0001”:{“ontime”:2973.0352,“avg”:3002.7071,“min”:2957.5095,“max”:3051.2454},“DA-LT-6BT008”:{“ontime”:185.6328,“avg”:184.5608,“min”:183.4343,“max”:186.0842},“DA-LT-5BT0005”:{“ontime”:412.2,“avg”:411.9946,“min”:411.54,“max”:412.2},“DA-LT-6BT004”:{“ontime”:1210.2991,“avg”:1210.0581,“min”:1209.7651,“max”:1210.3992},“DA-LT-5BT0004”:{“ontime”:1205.7001,“avg”:1207.1034,“min”:1205.6,“max”:1208.6},“DA-LT-6BT005”:{“ontime”:403.1989,“avg”:403.2295,“min”:402.9437,“max”:403.5129},“DA-LT-5BT0008”:{“ontime”:195.32,“avg”:193.6475,“min”:192.74,“max”:195.32},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:141.7875,“avg”:144.065,“min”:141.325,“max”:145.6125},“DA-LT-4BT0007”:{“ontime”:170.7,“avg”:170.3056,“min”:169.9,“max”:170.7},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1212.0,“avg”:1211.9831,“min”:1211.0,“max”:1212.0},“DA-LT-6BT001”:{“ontime”:178867.8,“avg”:178457.1483,“min”:177291.66,“max”:179163.56},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:312.1875,“avg”:313.2235,“min”:311.625,“max”:314.3125},“DA_DB195_RH_R_0281”:{“ontime”:384.85,“avg”:413.9697,“min”:360.35,“max”:446.67},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:117148.07,“avg”:117013.164,“min”:115852.336,“max”:118035.484}}}
初始化在线检测: tag=DA-LT-4BT0007, 时间=2025-08-06 08:11
加载配置: 30 个参数
配置加载完成，检查点时间: Wed Aug 06 08:11:54 CST 2025
广播配置更新完成, 配置项: 30
分钟数据流> {“times”:“2025-08-06 08:11”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3015.391,“avg”:3009.9417,“min”:2954.6865,“max”:3061.303},“DA-LT-6BT008”:{“ontime”:184.141,“avg”:184.0843,“min”:183.7876,“max”:184.3176},“DA-LT-5BT0005”:{“ontime”:411.48,“avg”:409.439,“min”:407.16,“max”:411.48},“DA-LT-6BT004”:{“ontime”:1209.8318,“avg”:1209.5916,“min”:1209.1644,“max”:1209.8986},“DA-LT-5BT0004”:{“ontime”:1208.6,“avg”:1209.5684,“min”:1208.6,“max”:1210.4},“DA-LT-6BT005”:{“ontime”:403.3755,“avg”:403.1174,“min”:402.9241,“max”:403.3755},“DA-LT-5BT0008”:{“ontime”:192.68,“avg”:191.2343,“min”:190.24,“max”:192.68},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:144.4375,“avg”:144.1377,“min”:142.95,“max”:146.5375},“DA-LT-4BT0007”:{“ontime”:170.6,“avg”:170.6117,“min”:170.3,“max”:171.4},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1212.0,“avg”:1211.15,“min”:1211.0,“max”:1212.0},“DA-LT-6BT001”:{“ontime”:177777.17,“avg”:178292.1055,“min”:177513.31,“max”:179294.77},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:313.4375,“avg”:313.074,“min”:312.25,“max”:315.4375},“DA_DB195_RH_R_0281”:{“ontime”:416.57,“avg”:420.0408,“min”:398.11,“max”:440.25},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:116889.69,“avg”:117360.7005,“min”:116638.09,“max”:118252.67}}}
同步检测: DA-DB195-RH-B-0201 (1.0000) vs DA-LT-4BT0007 (170.3056) -> false
分钟数据流> {“times”:“2025-08-06 08:12”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3024.455,“avg”:3003.0229,“min”:2952.1091,“max”:3051.3713},“DA-LT-6BT008”:{“ontime”:184.1213,“avg”:183.9952,“min”:183.611,“max”:185.829},“DA-LT-5BT0005”:{“ontime”:407.1,“avg”:405.0824,“min”:403.5,“max”:407.1},“DA-LT-6BT004”:{“ontime”:1209.2645,“avg”:1209.0078,“min”:1208.7306,“max”:1209.2979},“DA-LT-5BT0004”:{“ontime”:1210.3,“avg”:1210.6475,“min”:1210.3,“max”:1210.9},“DA-LT-6BT005”:{“ontime”:402.9633,“avg”:402.4523,“min”:402.0407,“max”:403.0026},“DA-LT-5BT0008”:{“ontime”:191.1,“avg”:190.6654,“min”:188.58,“max”:192.0},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:143.45,“avg”:142.3155,“min”:140.975,“max”:143.45},“DA-LT-4BT0007”:{“ontime”:171.4,“avg”:171.3667,“min”:171.3,“max”:171.5},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1211.0,“avg”:1210.9322,“min”:1210.0,“max”:1211.0},“DA-LT-6BT001”:{“ontime”:177789.66,“avg”:178372.5054,“min”:177478.8,“max”:179600.3},“DA-LT-4BT0005”:{“ontime”:313.25,“avg”:311.9121,“min”:310.375,“max”:313.25},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA_DB195_RH_R_0281”:{“ontime”:424.16,“avg”:413.6031,“min”:359.99,“max”:447.09},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:117766.25,“avg”:118432.5507,“min”:117581.59,“max”:119435.39},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
同步检测: DA-DB195-RH-B-0201 (1.0000) vs DA-LT-4BT0007 (171.3667) -> false
分钟数据流> {“times”:“2025-08-06 08:13”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3034.6885,“avg”:3021.2272,“min”:2973.6846,“max”:3070.9446},“DA-LT-6BT008”:{“ontime”:185.829,“avg”:185.7005,“min”:184.0231,“max”:186.7712},“DA-LT-5BT0005”:{“ontime”:403.5,“avg”:404.826,“min”:403.26,“max”:407.16},“DA-LT-6BT004”:{“ontime”:1208.7974,“avg”:1208.477,“min”:1208.13,“max”:1208.7974},“DA-LT-5BT0004”:{“ontime”:1210.8,“avg”:1210.895,“min”:1210.7001,“max”:1211.1},“DA-LT-6BT005”:{“ontime”:402.0407,“avg”:402.2606,“min”:401.7463,“max”:403.2774},“DA-LT-5BT0008”:{“ontime”:189.26,“avg”:188.3993,“min”:187.28,“max”:189.62},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:142.225,“avg”:140.6388,“min”:139.025,“max”:143.575},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1211.0,“avg”:1210.4,“min”:1210.0,“max”:1211.0},“DA-LT-6BT001”:{“ontime”:178168.95,“avg”:178193.5373,“min”:177064.11,“max”:179223.0},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:311.625,“avg”:309.7354,“min”:308.125,“max”:312.875},“DA_DB195_RH_R_0281”:{“ontime”:405.55,“avg”:420.8507,“min”:394.22,“max”:446.28},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:119361.805,“avg”:119400.946,“min”:118796.96,“max”:120133.164},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
同步检测: DA-DB195-RH-B-0201 (1.0000) vs DA-LT-4BT0007 (171.3667) -> false
分钟数据流> {“times”:“2025-08-06 08:14”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3029.965,“avg”:3031.526,“min”:2987.0623,“max”:3073.6565},“DA-LT-6BT008”:{“ontime”:185.3579,“avg”:184.7612,“min”:183.8858,“max”:185.3579},“DA-LT-5BT0005”:{“ontime”:407.16,“avg”:408.448,“min”:407.16,“max”:409.2},“DA-LT-6BT004”:{“ontime”:1208.1968,“avg”:1207.8436,“min”:1207.5293,“max”:1208.2301},“DA-LT-5BT0004”:{“ontime”:1211.0,“avg”:1210.8483,“min”:1210.5,“max”:1211.1},“DA-LT-6BT005”:{“ontime”:402.7278,“avg”:403.5316,“min”:402.5511,“max”:404.6122},“DA-LT-5BT0008”:{“ontime”:189.36,“avg”:191.098,“min”:189.36,“max”:191.72},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:140.4125,“avg”:140.0025,“min”:139.15,“max”:141.5625},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1210.0,“avg”:1210.0,“min”:1210.0,“max”:1210.0},“DA-LT-6BT001”:{“ontime”:178750.7,“avg”:178188.4007,“min”:177176.88,“max”:179348.72},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:309.3125,“avg”:308.1458,“min”:307.3125,“max”:309.3125},“DA_DB195_RH_R_0281”:{“ontime”:424.4,“avg”:411.3922,“min”:369.9,“max”:448.17},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:120119.95,“avg”:120058.3205,“min”:119094.73,“max”:121310.28},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
分钟数据流> {“times”:“2025-08-06 08:15”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3023.7253,“avg”:3028.9999,“min”:2966.9814,“max”:3080.395},“DA-LT-6BT008”:{“ontime”:184.5335,“avg”:185.1561,“min”:184.4746,“max”:185.7505},“DA-LT-5BT0005”:{“ontime”:409.2,“avg”:410.104,“min”:409.2,“max”:410.7},“DA-LT-6BT004”:{“ontime”:1207.5293,“avg”:1207.1667,“min”:1206.7952,“max”:1207.5293},“DA-LT-5BT0004”:{“ontime”:1210.6,“avg”:1210.5767,“min”:1210.3,“max”:1210.8},“DA-LT-6BT005”:{“ontime”:404.4944,“avg”:404.7401,“min”:404.4551,“max”:404.887},“DA-LT-5BT0008”:{“ontime”:191.0,“avg”:192.0173,“min”:191.0,“max”:193.7},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:142.4875,“avg”:140.1067,“min”:139.3,“max”:142.4875},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1210.0,“avg”:1209.9833,“min”:1209.0,“max”:1210.0},“DA-LT-6BT001”:{“ontime”:178105.47,“avg”:178441.7792,“min”:176945.67,“max”:179479.31},“DA-LT-4BT0005”:{“ontime”:308.6875,“avg”:307.0417,“min”:306.375,“max”:308.6875},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA_DB195_RH_R_0281”:{“ontime”:427.36,“avg”:418.5213,“min”:394.84,“max”:459.6199},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:119546.92,“avg”:120351.8229,“min”:119268.62,“max”:121035.23},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0}}}
同步检测: DA-DB195-RH-B-0201 (1.0000) vs DA-LT-4BT0007 (171.3667) -> false
加载配置: 30 个参数
配置加载完成，检查点时间: Wed Aug 06 08:16:54 CST 2025
广播配置更新完成, 配置项: 30
分钟数据流> {“times”:“2025-08-06 08:16”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3025.5146,“avg”:3039.6875,“min”:2985.3137,“max”:3098.7444},“DA-LT-6BT008”:{“ontime”:185.7505,“avg”:185.0521,“min”:183.0417,“max”:187.0461},“DA-LT-5BT0005”:{“ontime”:410.76,“avg”:410.988,“min”:410.64,“max”:411.24},“DA-LT-6BT004”:{“ontime”:1206.7952,“avg”:1206.4737,“min”:1205.8943,“max”:1206.8286},“DA-LT-5BT0004”:{“ontime”:1210.4,“avg”:1210.1584,“min”:1209.8,“max”:1210.5},“DA-LT-6BT005”:{“ontime”:404.6907,“avg”:403.4472,“min”:402.1782,“max”:404.7103},“DA-LT-5BT0008”:{“ontime”:191.96,“avg”:192.4993,“min”:191.9,“max”:193.56},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:139.325,“avg”:139.0523,“min”:137.3125,“max”:142.2375},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1209.0,“avg”:1209.3667,“min”:1209.0,“max”:1210.0},“DA-LT-6BT001”:{“ontime”:178384.45,“avg”:178832.4795,“min”:177665.1,“max”:180298.0},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0005”:{“ontime”:307.125,“avg”:307.7823,“min”:306.375,“max”:311.4375},“DA_DB195_RH_R_0281”:{“ontime”:399.44,“avg”:418.7185,“min”:379.25,“max”:471.42},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:120173.64,“avg”:119901.6293,“min”:118565.47,“max”:121078.25}}}
分钟数据流> {“times”:“2025-08-06 08:17”,“datas”:{“DA-LT-5BT0001”:{“ontime”:3088.785,“avg”:3038.1858,“min”:2982.0671,“max”:3088.785},“DA-LT-6BT008”:{“ontime”:183.2576,“avg”:185.1267,“min”:183.2576,“max”:186.1431},“DA-LT-5BT0005”:{“ontime”:410.58,“avg”:410.86,“min”:410.52,“max”:411.24},“DA-LT-6BT004”:{“ontime”:1206.0945,“avg”:1205.5561,“min”:1205.0934,“max”:1206.0945},“DA-LT-5BT0004”:{“ontime”:1209.8,“avg”:1209.4934,“min”:1209.2001,“max”:1209.9},“DA-LT-6BT005”:{“ontime”:402.2763,“avg”:403.2048,“min”:402.0996,“max”:404.3177},“DA-LT-5BT0008”:{“ontime”:193.58,“avg”:194.234,“min”:193.58,“max”:194.58},“DA-NY-LG1ZL-2-001”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA-LT-4BT0008”:{“ontime”:139.6,“avg”:138.4794,“min”:137.55,“max”:139.6},“DB5701P250A00_101”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0004”:{“ontime”:1209.0,“avg”:1209.0,“min”:1209.0,“max”:1209.0},“DA-LT-6BT001”:{“ontime”:178429.75,“avg”:178591.9377,“min”:177682.62,“max”:179453.27},“DA-LT-4BT0005”:{“ontime”:308.0,“avg”:307.6677,“min”:307.0625,“max”:308.375},“DA-NY-LG2ZL-2-003”:{“ontime”:0.0,“avg”:0.0,“min”:0.0,“max”:0.0},“DA_DB195_RH_R_0281”:{“ontime”:434.05,“avg”:416.3023,“min”:387.8,“max”:444.66},“DA-DB195-RH-B-0200”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-DB195-RH-B-0201”:{“ontime”:1.0,“avg”:1.0,“min”:1.0,“max”:1.0},“DA-LT-4BT0001”:{“ontime”:119510.79,“avg”:120487.2018,“min”:119177.92,“max”:121636.37}}}
同步检测: DA-DB195-RH-B-0201 (1.0000) vs DA-LT-4BT0007 (171.3667) -> false
其中DA-LT-4BT0007配置了isonline=1，duration=1，DA-LT-4BT0007在分钟数据流中，初始没有数据，然后有几分钟有数据，而后有没有数据.但未生成DA-LT-4BT0007的离线异常报告。请改变实现思路。生成完整代码。
最新发布
博客提到上午讲解了for循环，下午讲解了函数，忽略无关信息后，关键信息为课程中for循环和函数的讲解。
扫一扫
349
被折叠的 条评论
为什么被折叠?
到【灌水乐园】发言
