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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、从redis中获取上次查询的时间戳
* 2、将当前时间戳放入到redis中，以便 下次按这个时间查询
* 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
*/
@Scheduled(cron = "0/30 * * * * ?")
public void start(){
logger.info("FetchConfirmOrdersFromErpJob start................."+ new Date());
StopWatch watch=new StopWatch();
watch.start();
//上次查询的时间
String preQueryTimeStr=this.readRedisService.get(Constans.CACHE_PREQUERYORDERTIME); Date now=new Date();
if(StringUtils.isBlank(preQueryTimeStr)){
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
// preQueryTimeStr="2015-05-07 10:00:00";//本地测试的时候使用
}
//设置当前时间为上次查询的时间
this.writeRedisService.set(Constans.CACHE_PREQUERYORDERTIME, DateFormatUtils.format(now, Constans.DATEFORMAT_PATTERN_YYYYMMDDHHMMSS)); List<Map<String, Object>> confirmOrderIds = this.erpOrderService.selectOrderIdbyConfirmtime(preQueryTimeStr);
if(confirmOrderIds==null){
logger.info("query confirmOrderIds is null,without order data need dealth..........");
return;
}
for (Map<String, Object> map : confirmOrderIds) {
//将订单编号放入队列中
this.writeRedisService.lpush(Constans.CACHE_ORDERIDS, map.get("channel_orderid").toString());
logger.info("=======lpush orderid:"+map.get("channel_orderid").toString());
} watch.stop();
logger.info("FetchConfirmOrdersFromErpJob end................."+ new Date()+" total cost time:"+watch.getTime()+" dealth data count:"+confirmOrderIds.size());
}
OrderCalculate.java 队列获取订单线程
public class OrderCalculate {
private static final Log logger = LogFactory.getLog(OrderCalculate.class);
@Autowired
private static WriteRedisService writeRedisService;
private static ExecutorService threadPool=Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors()*4
,new TjThreadFactory("CalculateAmount"));
static{
Runtime.getRuntime().addShutdownHook(new Thread(new Runnable() {
@Override
public void run() {
QueuePop.stop();
threadPool.shutdown();
}
}));
}
public void init(){
if(writeRedisService==null){
writeRedisService=SpringContext.getBean(WriteRedisService.class);
}
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
}
static class QueuePop implements Runnable{
volatile static boolean stop=false;
@Override
public void run() {
while(!stop){
//不断循环从队列里取出订单id
String orderId=null;
try {
orderId = writeRedisService.rpop(Constans.CACHE_ORDERIDS);
if(orderId!=null){
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
threadPool.submit(new CalculateAmount(Integer.parseInt(orderId),new Date()));
}
} catch (Exception e1) {
logger.error("",e1);
}
//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
try {
Thread.sleep(10);
} catch (InterruptedException e) {
logger.error("",e);
// Thread.currentThread().interrupt();
//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
}
}
}
public static void stop(){
stop=true;
}
}
}
CalculateAmoiunt.java 订单任务处理
public class CalculateAmount implements Runnable {
private static final Log logger = LogFactory.getLog(CalculateAmount.class);
private int orderId;
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
private OrderService orderServices;
private OrdHaveProductService ordHaveProductService;
private OrdPayByCashbackService ordPayByCashbackService;
private OrdPayByCouponService ordPayByCouponService;
private OrdPayByGiftCardService ordPayByGiftCardService;
private StatisticsService statisticsService;
private WriteRedisService writeRedisService;
private ReadRedisService readRedisService;
private ErpOrderGoodsService erpOrderGoodsService;
private ErpOrderService erpOrderService;
public CalculateAmount(int orderId,Date now) {
super();
this.orderId = orderId;
this.now=now;
orderServices=SpringContext.getBean(OrderService.class);
ordHaveProductService=SpringContext.getBean(OrdHaveProductService.class);
ordPayByCashbackService=SpringContext.getBean(OrdPayByCashbackService.class);
ordPayByCouponService=SpringContext.getBean(OrdPayByCouponService.class);
ordPayByGiftCardService=SpringContext.getBean(OrdPayByGiftCardService.class);
statisticsService=SpringContext.getBean(StatisticsService.class);
writeRedisService=SpringContext.getBean(WriteRedisService.class);
readRedisService=SpringContext.getBean(ReadRedisService.class);
erpOrderGoodsService=SpringContext.getBean(ErpOrderGoodsService.class);
erpOrderService=SpringContext.getBean(ErpOrderService.class);
}
@Override
public void run() {
logger.info("CalculateAmount task run start........orderId:"+orderId);
StopWatch watch=new StopWatch();
watch.start();
/**
* 取出订单相关的所有数据同步到统计的库中
*/
//TODO 考虑要不要将下面所有操作放到一个事务里面
List<Map<String, Object>> orders = this.orderServices.selectOrderById(orderId);
if(orders!=null&&orders.size()>0){
Map<String, Object> order = orders.get(0);
String orderSN=U.nvl(order.get("OrderSN"));//订单编号
Integer userId=U.nvlInt(order.get("usr_UserID"),null);//用户d
Integer status=U.nvlInt(order.get("Status"),null);//状态
Date createTime=now;//(Date)order.get("CreateTime");//创建时间
Date modifyTime=now;//(Date)order.get("ModifyTime");// 更新时间
BigDecimal discountPrice=U.nvlDecimal(order.get("DiscountPrice"),null);//优惠总额 满减金额
BigDecimal payPrice=U.nvlDecimal(order.get("PayPrice"), null);//实付金额
BigDecimal totalPrice=U.nvlDecimal(order.get("TotalPrice"), null);//总金额
//从erp里查询出订单的确认时间
int dbConfirmTime=0;
try {
dbConfirmTime = this.erpOrderService.selectConfirmTimeByOrderId(orderId);
} catch (Exception e2) {
logger.error("",e2);
}
Date ct=new Date(dbConfirmTime*1000L);
int[] dates=U.getYearMonthDayHour(ct);//
if(modifyTime!=null){
dates=U.getYearMonthDayHour(modifyTime);//
}
int year=dates[0];//年
int month=dates[1];//月
int day=dates[2];//日
int hour=dates[3];//小时
String ordersId=orderId+"";//生成订单id
//查询订单的来源和搜索引擎关键字
String source="";
String seKeyWords="";
List<OrdersData> orderDataList=this.statisticsService.selectOrdersDataByOrdersId(orderSN);
if(orderDataList!=null&&!orderDataList.isEmpty()){
OrdersData ordersData = orderDataList.get(0);
source=ordersData.getSource();
seKeyWords=ordersData.getSeKeyWords();
}
//TODO 将订单入库
ArrayList<RelOrders> relOrdersList = Lists.newArrayList();
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);
relOrdersList.add(relOrders);
try {
relOrders.setConfirmTime(ct);
//查询RelOrders是否存在
RelOrders dbOrders=this.statisticsService.selectByPrimaryKey(orderSN);
if(dbOrders!=null){
//更新
dbOrders.setStatus(Byte.valueOf(status+""));
dbOrders.setConfirmTime(ct);
dbOrders.setModifyTime(modifyTime);
this.statisticsService.updateByPrimaryKeySelective(dbOrders);
return;
}else{
Integer relResult=this.statisticsService.insertRelOrdersBatch(relOrdersList);
}
} catch (Exception e) {
logger.error("insertRelOrdersBatch error",e);
}
/**
* 查这个订单的返现、优惠券、礼品卡 的金额
*/
List<Map<String, Object>> cashs = this.ordPayByCashbackService.selectDecutionPriceByOrderId(orderId);
List<Map<String, Object>> coupons = this.ordPayByCouponService.selectDecutionPriceByOrderId(orderId);
BigDecimal cashAmount=U.getValueByKey(cashs, "DeductionPrice", BigDecimal.class, BigDecimal.ZERO);//返现金额
BigDecimal couponAmont=U.getValueByKey(coupons, "DeductionPrice", BigDecimal.class, BigDecimal.ZERO);//红包金额
/**
* 查询出这个订单的所有商品
*/
List<Map<String, Object>> products=null;
Map<String,Object> productToKeyWordMap=Maps.newHashMap();
try {
products = this.ordHaveProductService.selectByOrderId(orderId);
List<OrdersItemData> ordersItemDataList=this.statisticsService.selectOrdersItemDataByOrdersId(orderSN);
if(ordersItemDataList!=null){
for (OrdersItemData ordersItemData : ordersItemDataList) {
productToKeyWordMap.put(ordersItemData.getItemId(), ordersItemData.getKeyWords());
}
}
} catch (Exception e1) {
logger.error("",e1);
}
if(products!=null){
ArrayList<RelOrdersItem> relOrdersItemList = Lists.newArrayList();
for (Map<String, Object> product : products) {
Integer productId=U.nvlInt(product.get("pro_ProductID"), null);//商品Id
Integer buyNo=U.nvlInt(product.get("BuyNo"), 0);//购买数量
String SN=U.nvl(product.get("SN"),"");
BigDecimal buyPrice=U.nvlDecimal(product.get("BuyPrice"), BigDecimal.ZERO);//购买价格
BigDecimal buyTotalPrice=U.nvlDecimal(product.get("BuyTotalPrice"), null);//购买总价格
BigDecimal productPayPrice=U.nvlDecimal(product.get("PayPrice"), null);//单品实付金额
BigDecimal cost=null;//商品成本 TODO 调别人的接口
BigDecimal realtimeAmount=null;//实付金额
BigDecimal pdCashAmount=BigDecimal.ZERO;//每个商品的返现
BigDecimal pdcouponAmont=BigDecimal.ZERO;//每个商品的优惠券
//商品价格所占订单比例
if(buyTotalPrice!=null&&totalPrice!=null&&totalPrice.doubleValue()!=0){
pdCashAmount=buyTotalPrice.divide(totalPrice,8,BigDecimal.ROUND_HALF_UP).multiply(cashAmount).setScale(2,BigDecimal.ROUND_HALF_UP);
pdcouponAmont=buyTotalPrice.divide(totalPrice,8,BigDecimal.ROUND_HALF_UP).multiply(couponAmont).setScale(2,BigDecimal.ROUND_HALF_UP);
discountPrice=buyTotalPrice.divide(totalPrice,8,BigDecimal.ROUND_HALF_UP).multiply(discountPrice).setScale(2,BigDecimal.ROUND_HALF_UP);
}
realtimeAmount=buyTotalPrice.subtract((pdCashAmount.add(pdcouponAmont).add(discountPrice))).setScale(2,BigDecimal.ROUND_HALF_UP);
RelOrdersItem item=new RelOrdersItem(U.randomUUID(),orderSN,productId,SN,buyNo,realtimeAmount,U.nvl(productToKeyWordMap.get(productId)));
relOrdersItemList.add(item);
//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
if((status==1||status==5||status==6||status==7||status==11)&&DateUtils.isSameDay(new Date(), ct)){
//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
dates=U.getYearMonthDayHour(ct);//
int days=dates[2];
//某一个商品某一天的实付金额
BigDecimal itemRelAmount=BigDecimal.ZERO;
//从redis里取出这个商品的实付金额，然后累加
String itemRelAmountStr=readRedisService.get(Constans.CACHE_PERITEMRELAMOUNTSS_KEY_PREFIX+productId+Constans.CACHE_KEY_SEPARATOR+days);
if(StringUtils.isNotBlank(itemRelAmountStr)){
itemRelAmount=new BigDecimal(itemRelAmountStr);
}
realtimeAmount=itemRelAmount.add(realtimeAmount);
writeRedisService.set(Constans.CACHE_PERITEMRELAMOUNTSS_KEY_PREFIX+productId+Constans.CACHE_KEY_SEPARATOR+days, realtimeAmount.toPlainString());
writeRedisService.lpush(Constans.CACHE_DELKEYS_KEY_PRDFIX+days, Constans.CACHE_PERITEMRELAMOUNTSS_KEY_PREFIX+productId+Constans.CACHE_KEY_SEPARATOR+days);
writeRedisService.zadd(Constans.CACHE_ITEMREALAMOUNTSS_KEY+days, realtimeAmount.doubleValue(), productId+"");
//确认的销量
Long itemCount= writeRedisService.incrBy(Constans.CACHE_ITEMSALES_KEY_PRDFIX+productId+Constans.CACHE_KEY_SEPARATOR+days,buyNo);
writeRedisService.zadd(Constans.CACHE_ITEMSALES_SS_KEY_PRDFIX+days, itemCount, productId+"");
String itemType="";
Map<String, String> pMap = this.readRedisService.hmget(Constans.CACHE_PRODUCT_KEY+productId);
itemType=pMap.get("categoryId");
if(StringUtils.isNotBlank(itemType)){
if(ProductCategory.isGuanBai(itemType)){
//如果是白酒 官白的访客数排行
this.writeRedisService.zadd(Constans.CACHE_ITEMREALAMOUNTWHITESS_KEY+days, realtimeAmount.doubleValue(), productId+"");//
//确认的销量排行
this.writeRedisService.zadd(Constans.CACHE_ITEMSALESWHITE_SS_KEY_PRDFIX+days, itemCount, productId+"");//
}else if(ProductCategory.isGuanHong(itemType)){
//官红的访客数排行
this.writeRedisService.zadd(Constans.CACHE_ITEMREALAMOUNTREDSS_KEY+days, realtimeAmount.doubleValue(), productId+"");//
//确认的销量排行
this.writeRedisService.zadd(Constans.CACHE_ITEMSALESRED_SS_KEY_PRDFIX+days, itemCount, productId+"");//
}
}
//某一个商品的销量加入删除列表
writeRedisService.lpush(Constans.CACHE_DELKEYS_KEY_PRDFIX+days, Constans.CACHE_ITEMSALES_KEY_PRDFIX+productId+Constans.CACHE_KEY_SEPARATOR+days);
}
}
try {
//TODO 将订单商品明细入库
this.statisticsService.insertRelOrdersItemBatch(relOrdersItemList);
//再将订单的状态改为已计算
this.statisticsService.updateIsCal(orderSN,IsCal.已计算.getFlag());//将是否计算改成已计算
//该订单的所有商品的成本同步到现在的库中。
this.calOrderProductCostSync(orderId,orderSN,products);
} catch (Exception e) {
logger.error("insertRelOrdersItemBatch or updateIsCal error",e);
}
}
}
watch.stop();
logger.info("CalculateAmount task run end........total cost time:"+watch.getTime()+" orderId:"+orderId);
}
private void calOrderProductCostSync(int orderId,String orderSN,List<Map<String, Object>> products){
List<Map<String, Object>> ordersList = this.erpOrderGoodsService.selectProductCostByOrderSN(orderSN);
if(ordersList==null||ordersList.isEmpty()){
logger.error("according orderId to query some data from erp return is null.........");
return;
}
Map<String, String> itemIdToItemSnMap = U.convertToMapByList(products, "pro_ProductID", "SN");
List<RelItemCosts> list=Lists.newArrayList();
for (Map<String, Object> map : ordersList) {
RelItemCosts itemCost=new RelItemCosts();
if(map==null){
continue;
}
Integer itemId=U.nvlInt(map.get("goods_id"),-99);
BigDecimal costs=U.nvlDecimal(map.get("Dynamic_price"), BigDecimal.ZERO);
itemCost.setId(U.randomUUID());
itemCost.setOrdersId(orderId+"");
itemCost.setOrdersNo(orderSN);
itemCost.setItemId(itemId);
itemCost.setItemNo(itemIdToItemSnMap.get(itemId+""));
itemCost.setCosts(costs);
itemCost.setCreateTime(new Date());
itemCost.setModifyTime(new Date());
list.add(itemCost);
}
this.statisticsService.insertRelItemCostsBatch(list);
}
}
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。