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经过一段时间项目的沉淀之后，对实际应用中的多线程开发及队列使用产生了深厚的兴趣，也将<<java并发编程实战>>仔细的阅读了两三遍，也看了很多并发编程的实践项目，也有了深刻的理解与在实践中合理应用队列、多线程开发的应用场景
1、真实应用场景描述：
由于一段时间以来要针对公司整个电商平台包括官网、移动端所有的交易数据进行统计，统计指标包括：pv、uv、实付金额、转化率、毛利率等等，按照各种不同的维度来统计计算出当前交易系统的各个指标的数据，但要求该项目是独立的，没有任务其它资源的协助及接品提供。经过一番xxxx思考讨论之后。业务上决定用以下解决方案：
A: 用一个定时服务每隔10秒去别的系统数据库抓取上一次查询时间以来新确认的订单（这种订单表示已经支付完在或者客户已经审核确认了），然后将这些订单的唯一编号放入redis队列。
B: 由于用到了队列，根据经验自然而然的想到了 启动单独的线程去redis队列中不断获取要统计处理的订单编号，然后将获取到的订单编号放入线程池中进行订单的统计任务处理。
开发实现：
FetchConfirmOrdersFromErpJob.java
1 /**
2 * 1、从redis中获取上次查询的时间戳
3 * 2、将当前时间戳放入到redis中，以便 下次按这个时间查询
4 * 3、去erp订单表查询confirm_time>=上次查询的时间的订单，放入队列中
5 */
6 @Scheduled(cron = "0/30 * * * * ?")
7 public void start(){
8 logger.info("FetchConfirmOrdersFromErpJob start................."+ new Date());
9 StopWatch watch=new StopWatch();
10 watch.start();
11 //上次查询的时间
12 String preQueryTimeStr=this.readRedisService.get(Constans.CACHE_PREQUERYORDERTIME);
13
14 Date now=new Date();
15 if(StringUtils.isBlank(preQueryTimeStr)){
16 preQueryTimeStr=DateFormatUtils.format(DateUtils.addHours(now, -1), Constans.DATEFORMAT_PATTERN_YYYYMMDDHHMMSS);//第一次查询之前一个小时的订单
17 // preQueryTimeStr="2015-05-07 10:00:00";//本地测试的时候使用
18 }
19 //设置当前时间为上次查询的时间
20 this.writeRedisService.set(Constans.CACHE_PREQUERYORDERTIME, DateFormatUtils.format(now, Constans.DATEFORMAT_PATTERN_YYYYMMDDHHMMSS));
21
22 List<Map<String, Object>> confirmOrderIds = this.erpOrderService.selectOrderIdbyConfirmtime(preQueryTimeStr);
23 if(confirmOrderIds==null){
24 logger.info("query confirmOrderIds is null,without order data need dealth..........");
25 return;
26 }
27 for (Map<String, Object> map : confirmOrderIds) { //将订单编号放入队列中
28 this.writeRedisService.lpush(Constans.CACHE_ORDERIDS, map.get("channel_orderid").toString());
29 logger.info("=======lpush orderid:"+map.get("channel_orderid").toString());
30 }
31
32 watch.stop();
33 logger.info("FetchConfirmOrdersFromErpJob end................."+ new Date()+" total cost time:"+watch.getTime()+" dealth data count:"+confirmOrderIds.size());
34 }
OrderCalculate.java 队列获取订单线程
1 public class OrderCalculate {
2
3 private static final Log logger = LogFactory.getLog(OrderCalculate.class);
4
5 @Autowired
6 private static WriteRedisService writeRedisService;
7
8 private static ExecutorService threadPool=Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors()*4
9 ,new TjThreadFactory("CalculateAmount"));
10 static{
11 Runtime.getRuntime().addShutdownHook(new Thread(new Runnable() {
12 @Override
13 public void run() {
14 QueuePop.stop();
15 threadPool.shutdown();
16 }
17 }));
18 }
19
20 public void init(){
21 if(writeRedisService==null){
22 writeRedisService=SpringContext.getBean(WriteRedisService.class);
23 }
24 new Thread(new QueuePop(),"OrderIdQueuePop").start();//由于是用redis做的队列，所以只要使用一个线程从队列里拿就ok
25 }
26
27 static class QueuePop implements Runnable{
28
29 volatile static boolean stop=false;
30
31 @Override
32 public void run() {
33 while(!stop){
34 //不断循环从队列里取出订单id
35 String orderId=null;
36 try {
37 orderId = writeRedisService.rpop(Constans.CACHE_ORDERIDS);
38 if(orderId!=null){
39 logger.info("pop orderId:"+orderId); //将获取的订单编号交给订单统计任务处理线程处理
40 threadPool.submit(new CalculateAmount(Integer.parseInt(orderId),new Date()));
41 }
42 } catch (Exception e1) {
43 logger.error("",e1);
44 }
45 //根据上线后的业务反馈来确定是否改成wait/notify策略来及时处理确认的订单
46 try {
47 Thread.sleep(10);
48 } catch (InterruptedException e) {
49 logger.error("",e);
50 // Thread.currentThread().interrupt();
51 //stop=true;//线程被打算继续执行，不应该被关闭，保证该线程永远不会死掉
52 }
53 }
54 }
55
56 public static void stop(){
57 stop=true;
58 }
59
60 }
61
62 }
CalculateAmoiunt.java 订单任务处理
1 public class CalculateAmount implements Runnable {
2 private static final Log logger = LogFactory.getLog(CalculateAmount.class);
3 private int orderId;
4 private Date now;//确认时间 这个时间有一定的延迟，基本可以忽略，如果没什么用
5 private OrderService orderServices;
6 private OrdHaveProductService ordHaveProductService;
7 private OrdPayByCashbackService ordPayByCashbackService;
8 private OrdPayByCouponService ordPayByCouponService;
9 private OrdPayByGiftCardService ordPayByGiftCardService;
10 private StatisticsService statisticsService;
11 private WriteRedisService writeRedisService;
12 private ReadRedisService readRedisService;
13 private ErpOrderGoodsService erpOrderGoodsService;
14 private ErpOrderService erpOrderService;
15
16
17 public CalculateAmount(int orderId,Date now) {
18 super();
19 this.orderId = orderId;
20 this.now=now;
21 orderServices=SpringContext.getBean(OrderService.class);
22 ordHaveProductService=SpringContext.getBean(OrdHaveProductService.class);
23 ordPayByCashbackService=SpringContext.getBean(OrdPayByCashbackService.class);
24 ordPayByCouponService=SpringContext.getBean(OrdPayByCouponService.class);
25 ordPayByGiftCardService=SpringContext.getBean(OrdPayByGiftCardService.class);
26 statisticsService=SpringContext.getBean(StatisticsService.class);
27 writeRedisService=SpringContext.getBean(WriteRedisService.class);
28 readRedisService=SpringContext.getBean(ReadRedisService.class);
29 erpOrderGoodsService=SpringContext.getBean(ErpOrderGoodsService.class);
30 erpOrderService=SpringContext.getBean(ErpOrderService.class);
31 }
32
33 @Override
34 public void run() {
35 logger.info("CalculateAmount task run start........orderId:"+orderId);
36 StopWatch watch=new StopWatch();
37 watch.start();
38 /**
39 * 取出订单相关的所有数据同步到统计的库中
40 */
41 //TODO 考虑要不要将下面所有操作放到一个事务里面
42 List<Map<String, Object>> orders = this.orderServices.selectOrderById(orderId);
43 if(orders!=null&&orders.size()>0){
44 Map<String, Object> order = orders.get(0);
45
46 String orderSN=U.nvl(order.get("OrderSN"));//订单编号
47 Integer userId=U.nvlInt(order.get("usr_UserID"),null);//用户d
48 Integer status=U.nvlInt(order.get("Status"),null);//状态
49 Date createTime=now;//(Date)order.get("CreateTime");//创建时间
50 Date modifyTime=now;//(Date)order.get("ModifyTime");// 更新时间
51 BigDecimal discountPrice=U.nvlDecimal(order.get("DiscountPrice"),null);//优惠总额 满减金额
52 BigDecimal payPrice=U.nvlDecimal(order.get("PayPrice"), null);//实付金额
53 BigDecimal totalPrice=U.nvlDecimal(order.get("TotalPrice"), null);//总金额
54
55 //从erp里查询出订单的确认时间
56 int dbConfirmTime=0;
57 try {
58 dbConfirmTime = this.erpOrderService.selectConfirmTimeByOrderId(orderId);
59 } catch (Exception e2) {
60 logger.error("",e2);
61 }
62 Date ct=new Date(dbConfirmTime*1000L);
63
64 int[] dates=U.getYearMonthDayHour(ct);//
65 if(modifyTime!=null){
66 dates=U.getYearMonthDayHour(modifyTime);//
67 }
68 int year=dates[0];//年
69 int month=dates[1];//月
70 int day=dates[2];//日
71 int hour=dates[3];//小时
72
73 String ordersId=orderId+"";//生成订单id
74
75 //查询订单的来源和搜索引擎关键字
76 String source="";
77 String seKeyWords="";
78 List<OrdersData> orderDataList=this.statisticsService.selectOrdersDataByOrdersId(orderSN);
79 if(orderDataList!=null&&!orderDataList.isEmpty()){
80 OrdersData ordersData = orderDataList.get(0);
81 source=ordersData.getSource();
82 seKeyWords=ordersData.getSeKeyWords();
83 }
84
85 //TODO 将订单入库
86 ArrayList<RelOrders> relOrdersList = Lists.newArrayList();
87 RelOrders relOrders=new RelOrders(orderSN,userId+"",Byte.valueOf(status+""),source,seKeyWords,IsCal.未计算.getFlag(),(byte)U.getSimpleYearByYear(year),(byte)month,(byte)day,(byte)hour,ct,createTime,modifyTime);
88 relOrdersList.add(relOrders);
89
90 try {
91 relOrders.setConfirmTime(ct);
92 //查询RelOrders是否存在
93 RelOrders dbOrders=this.statisticsService.selectByPrimaryKey(orderSN);
94 if(dbOrders!=null){
95 //更新
96 dbOrders.setStatus(Byte.valueOf(status+""));
97 dbOrders.setConfirmTime(ct);
98 dbOrders.setModifyTime(modifyTime);
99 this.statisticsService.updateByPrimaryKeySelective(dbOrders);
100 return;
101 }else{
102 Integer relResult=this.statisticsService.insertRelOrdersBatch(relOrdersList);
103 }
104 } catch (Exception e) {
105 logger.error("insertRelOrdersBatch error",e);
106 }
107 /**
108 * 查这个订单的返现、优惠券、礼品卡 的金额
109 */
110 List<Map<String, Object>> cashs = this.ordPayByCashbackService.selectDecutionPriceByOrderId(orderId);
111 List<Map<String, Object>> coupons = this.ordPayByCouponService.selectDecutionPriceByOrderId(orderId);
112
113 BigDecimal cashAmount=U.getValueByKey(cashs, "DeductionPrice", BigDecimal.class, BigDecimal.ZERO);//返现金额
114 BigDecimal couponAmont=U.getValueByKey(coupons, "DeductionPrice", BigDecimal.class, BigDecimal.ZERO);//红包金额
115 /**
116 * 查询出这个订单的所有商品
117 */
118 List<Map<String, Object>> products=null;
119 Map<String,Object> productToKeyWordMap=Maps.newHashMap();
120 try {
121 products = this.ordHaveProductService.selectByOrderId(orderId);
122 List<OrdersItemData> ordersItemDataList=this.statisticsService.selectOrdersItemDataByOrdersId(orderSN);
123 if(ordersItemDataList!=null){
124 for (OrdersItemData ordersItemData : ordersItemDataList) {
125 productToKeyWordMap.put(ordersItemData.getItemId(), ordersItemData.getKeyWords());
126 }
127 }
128 } catch (Exception e1) {
129 logger.error("",e1);
130 }
131 if(products!=null){
132 ArrayList<RelOrdersItem> relOrdersItemList = Lists.newArrayList();
133 for (Map<String, Object> product : products) {
134 Integer productId=U.nvlInt(product.get("pro_ProductID"), null);//商品Id
135 Integer buyNo=U.nvlInt(product.get("BuyNo"), 0);//购买数量
136 String SN=U.nvl(product.get("SN"),"");
137 BigDecimal buyPrice=U.nvlDecimal(product.get("BuyPrice"), BigDecimal.ZERO);//购买价格
138 BigDecimal buyTotalPrice=U.nvlDecimal(product.get("BuyTotalPrice"), null);//购买总价格
139 BigDecimal productPayPrice=U.nvlDecimal(product.get("PayPrice"), null);//单品实付金额
140
141 BigDecimal cost=null;//商品成本 TODO 调别人的接口
142 BigDecimal realtimeAmount=null;//实付金额
143
144 BigDecimal pdCashAmount=BigDecimal.ZERO;//每个商品的返现
145 BigDecimal pdcouponAmont=BigDecimal.ZERO;//每个商品的优惠券
146
147 //商品价格所占订单比例
148 if(buyTotalPrice!=null&&totalPrice!=null&&totalPrice.doubleValue()!=0){
149 pdCashAmount=buyTotalPrice.divide(totalPrice,8,BigDecimal.ROUND_HALF_UP).multiply(cashAmount).setScale(2,BigDecimal.ROUND_HALF_UP);
150 pdcouponAmont=buyTotalPrice.divide(totalPrice,8,BigDecimal.ROUND_HALF_UP).multiply(couponAmont).setScale(2,BigDecimal.ROUND_HALF_UP);
151 discountPrice=buyTotalPrice.divide(totalPrice,8,BigDecimal.ROUND_HALF_UP).multiply(discountPrice).setScale(2,BigDecimal.ROUND_HALF_UP);
152 }
153
154 realtimeAmount=buyTotalPrice.subtract((pdCashAmount.add(pdcouponAmont).add(discountPrice))).setScale(2,BigDecimal.ROUND_HALF_UP);
155
156 RelOrdersItem item=new RelOrdersItem(U.randomUUID(),orderSN,productId,SN,buyNo,realtimeAmount,U.nvl(productToKeyWordMap.get(productId)));
157
158 relOrdersItemList.add(item);
159
160 //如果确认时间属于同一天的话，将商品实付金额放入到redis排行榜中
161 if((status==1||status==5||status==6||status==7||status==11)&&DateUtils.isSameDay(new Date(), ct)){
162 //如果订单的状态是这几种，刚将该商品加入到实付金额的排行 榜中
163 dates=U.getYearMonthDayHour(ct);//
164 int days=dates[2];
165 //某一个商品某一天的实付金额
166 BigDecimal itemRelAmount=BigDecimal.ZERO;
167 //从redis里取出这个商品的实付金额，然后累加
168 String itemRelAmountStr=readRedisService.get(Constans.CACHE_PERITEMRELAMOUNTSS_KEY_PREFIX+productId+Constans.CACHE_KEY_SEPARATOR+days);
169 if(StringUtils.isNotBlank(itemRelAmountStr)){
170 itemRelAmount=new BigDecimal(itemRelAmountStr);
171 }
172 realtimeAmount=itemRelAmount.add(realtimeAmount);
173 writeRedisService.set(Constans.CACHE_PERITEMRELAMOUNTSS_KEY_PREFIX+productId+Constans.CACHE_KEY_SEPARATOR+days, realtimeAmount.toPlainString());
174 writeRedisService.lpush(Constans.CACHE_DELKEYS_KEY_PRDFIX+days, Constans.CACHE_PERITEMRELAMOUNTSS_KEY_PREFIX+productId+Constans.CACHE_KEY_SEPARATOR+days);
175 writeRedisService.zadd(Constans.CACHE_ITEMREALAMOUNTSS_KEY+days, realtimeAmount.doubleValue(), productId+"");
176 //确认的销量
177 Long itemCount= writeRedisService.incrBy(Constans.CACHE_ITEMSALES_KEY_PRDFIX+productId+Constans.CACHE_KEY_SEPARATOR+days,buyNo);
178 writeRedisService.zadd(Constans.CACHE_ITEMSALES_SS_KEY_PRDFIX+days, itemCount, productId+"");
179
180 String itemType="";
181 Map<String, String> pMap = this.readRedisService.hmget(Constans.CACHE_PRODUCT_KEY+productId);
182 itemType=pMap.get("categoryId");
183 if(StringUtils.isNotBlank(itemType)){
184 if(ProductCategory.isGuanBai(itemType)){
185 //如果是白酒 官白的访客数排行
186 this.writeRedisService.zadd(Constans.CACHE_ITEMREALAMOUNTWHITESS_KEY+days, realtimeAmount.doubleValue(), productId+"");//
187 //确认的销量排行
188 this.writeRedisService.zadd(Constans.CACHE_ITEMSALESWHITE_SS_KEY_PRDFIX+days, itemCount, productId+"");//
189 }else if(ProductCategory.isGuanHong(itemType)){
190 //官红的访客数排行
191 this.writeRedisService.zadd(Constans.CACHE_ITEMREALAMOUNTREDSS_KEY+days, realtimeAmount.doubleValue(), productId+"");//
192 //确认的销量排行
193 this.writeRedisService.zadd(Constans.CACHE_ITEMSALESRED_SS_KEY_PRDFIX+days, itemCount, productId+"");//
194 }
195 }
196
197 //某一个商品的销量加入删除列表
198 writeRedisService.lpush(Constans.CACHE_DELKEYS_KEY_PRDFIX+days, Constans.CACHE_ITEMSALES_KEY_PRDFIX+productId+Constans.CACHE_KEY_SEPARATOR+days);
199 }
200 }
201 try {
202 //TODO 将订单商品明细入库
203 this.statisticsService.insertRelOrdersItemBatch(relOrdersItemList);
204 //再将订单的状态改为已计算
205 this.statisticsService.updateIsCal(orderSN,IsCal.已计算.getFlag());//将是否计算改成已计算
206 //该订单的所有商品的成本同步到现在的库中。
207 this.calOrderProductCostSync(orderId,orderSN,products);
208 } catch (Exception e) {
209 logger.error("insertRelOrdersItemBatch or updateIsCal error",e);
210 }
211 }
212 }
213 watch.stop();
214 logger.info("CalculateAmount task run end........total cost time:"+watch.getTime()+" orderId:"+orderId);
215 }
216
217 private void calOrderProductCostSync(int orderId,String orderSN,List<Map<String, Object>> products){
218 List<Map<String, Object>> ordersList = this.erpOrderGoodsService.selectProductCostByOrderSN(orderSN);
219 if(ordersList==null||ordersList.isEmpty()){
220 logger.error("according orderId to query some data from erp return is null.........");
221 return;
222 }
223 Map<String, String> itemIdToItemSnMap = U.convertToMapByList(products, "pro_ProductID", "SN");
224
225 List<RelItemCosts> list=Lists.newArrayList();
226 for (Map<String, Object> map : ordersList) {
227 RelItemCosts itemCost=new RelItemCosts();
228 if(map==null){
229 continue;
230 }
231 Integer itemId=U.nvlInt(map.get("goods_id"),-99);
232 BigDecimal costs=U.nvlDecimal(map.get("Dynamic_price"), BigDecimal.ZERO);
233 itemCost.setId(U.randomUUID());
234 itemCost.setOrdersId(orderId+"");
235 itemCost.setOrdersNo(orderSN);
236 itemCost.setItemId(itemId);
237 itemCost.setItemNo(itemIdToItemSnMap.get(itemId+""));
238 itemCost.setCosts(costs);
239 itemCost.setCreateTime(new Date());
240 itemCost.setModifyTime(new Date());
241 list.add(itemCost);
242 }
243
244 this.statisticsService.insertRelItemCostsBatch(list);
245
246 }
247
248 }
注意：
1、redis2.6版本使用lpush、rpop出列的时候会丢失数据。换成2.8及以上的版本运行正常。
2、由于应用会部署到多个结点，所以无法直接采用java的BlockingQueue阻塞队列，帮采用redis提供的队列支持。
3、如果要做到统计的绝对实时，最好采用大数据的实时计算的解决方案：kafka+storm 来实现
以上为队列结合线程的实践案例，供大家一起探讨。
转载请注明出处 ，请大家尊重作者的劳动成果。
时间： 2024-11-11 12:29:21