package com.qianwen.mdc.collect.service;

import java.util.ArrayList;
import java.util.List;
import java.util.Set;

import org.apache.commons.lang3.StringUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;

import com.alibaba.fastjson.JSONArray;
import com.alibaba.fastjson.JSONObject;
import com.qianwen.mdc.collect.domain.TelemetryData;
import com.qianwen.mdc.collect.domain.TelemetryDataItem;
import com.qianwen.mdc.collect.utils.redis.RedisUtil;
import com.qianwen.mdc.collect.vo.WorkstationDatapointsVO;

@Service
public class IOTMqttReceiveService {
	private static final Logger log = LoggerFactory.getLogger(IOTMqttReceiveService.class);
	@Autowired
	private CollectDataService collectDataService;
	
	@Autowired
	private PackedDataService packedDataService;
	@Autowired
    private WorkstationDatapointsService dpService;
	/**
	 * 处理收到的消息,对应TelemetryDataPostingConsumer
	 * @param payload
	 */
	public void handle(String payload) {
        //解析消息
        List<TelemetryData> teleList = parsePayload(payload);
        
        collectDataService.handleCollectData(teleList);
        
        packedDataService.handle(teleList);
	}
	
	/**
	 * 解析消息体字符串未列表，每个列表项是一个工位的数据
	 * @param payload
	 * @return
	 */
	List<TelemetryData> parsePayload(String payload){
		List<TelemetryData> dtList = new ArrayList<TelemetryData> ();
    	//多条 数据格式：{"174":[{"values":{"output":11},"ts":"1722478128278"},{"values":{"spindleSpeed":22},"ts":"1722478128281"}]}   174是应用id
		//解析消息 name,value形式，如n=output,v=11
        JSONObject jsonObj = JSONObject.parseObject(payload);
        
        Set<String> keySet = jsonObj.keySet();
        String[] keys = keySet.toArray(new String[] {});
        
        //WorkstationDatapointsVO dpVo;
        
        final String NEWDP_SUFFIX = "_n";//计算规则使用之后新数据点的结尾
        for(String key : keys) {
        	String appId = key;//iot系统中的应用id，本应用中应该用表去对应
        	
        	
        	//TODO 获取工位数据点配置,只保存配置好的数据点，没有配置的采集数据抛弃。
        	final WorkstationDatapointsVO dpVo = dpService.getDatapointsByAppIdFromCache(appId);
        	if(dpVo == null) {
        		//工位没有定义过数据点或者appId不匹配
        		log.warn("appId={}未找到数据点定义记录，丢弃数据",appId);
        		continue;
        	}
        	
        	TelemetryData tdata = new TelemetryData();
        	//tdata.setWorkstationId(workstationId);
        	tdata.setAppId(appId);
        	tdata.setWorkstationId(dpVo.getWorkstationId());
        	
        	JSONArray dtArr = jsonObj.getJSONArray(appId);
        	for(int i=0;i<dtArr.size();i++) {
        		
        		TelemetryDataItem tdataItem = new TelemetryDataItem();
        		JSONObject jsonDataItem = dtArr.getJSONObject(i);//每一项中dataItem还有values对象和ts时间戳2个属性
	        	
	        	long time = jsonDataItem.getLong("ts");
	        	tdataItem.setTime(time);
	        	JSONObject values = jsonDataItem.getJSONObject("values");
	        	
	        	Set<String> valueKeySet = values.keySet();
	        	valueKeySet.forEach(valueKey ->{
	        		String oriValueKey = valueKey;;//由于使用计算规则的采集点名称会后面增加一个"_n",所以这个oriValueKey代表没有增加"_n"的
	        		if(StringUtils.endsWith(valueKey, NEWDP_SUFFIX)) {
	        			oriValueKey = StringUtils.removeEnd(valueKey, NEWDP_SUFFIX);
	        		}
	        		if(!dpVo.containsDataPoint(oriValueKey)) {
	    				//如果不存在该数据点配置，该数据直接忽略
	    				return;
	    			}
	        		tdataItem.addPoint(oriValueKey,values.getString(valueKey));//使用原始配置点保持保存数据
	        	});
	        	
	        	tdata.addItem(tdataItem);
        	}
        	
        	dtList.add(tdata);
        }
		
        return dtList;
	}
	
}