其中用到了滑动窗口函数大小30秒，间隔15秒，且大于窗口10秒的数据，被丢弃。（实际业务这三个值 应为是 10 分钟，1分钟，5分钟）。代码先记录一下

成都创新互联一直通过网站建设和网站营销帮助企业获得更多客户资源。 以"深度挖掘，量身打造，注重实效"的一站式服务，以成都网站建设、网站制作、移动互联产品、营销型网站建设服务为核心业务。十年网站制作的经验，使用新网站建设技术，全新开发出的标准网站，不但价格便宜而且实用、灵活，特别适合中小公司网站制作。网站管理系统简单易用，维护方便，您可以完全操作网站资料，是中小公司快速网站建设的选择。

public static void main(String[] arg) throws Exception {

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.getConfig().enableSysoutLogging();//开启Sysout打日志
        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime); //设置窗口的时间单位为process time

        Properties props = new Properties();
        props.put("bootstrap.servers", "kafkaip:9092");
        props.put("group.id", "metric-group4");
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");  //key 反序列化
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("auto.offset.reset", "earliest"); //value 反序列化

        DataStreamSource dataStreamSource = env.addSource(new FlinkKafkaConsumer011<>(
                "im-message-topic3",  //kafka topic
                new SimpleStringSchema(),  // String 序列化
                props)).setParallelism(1);

        DataStream bean3DataStream = dataStreamSource.map(new MapFunction() {         
            @Override
            public Message map(String value) throws Exception {
                 logger.info("receive msg:"+value); 
                 JSONObject jsonObject =JSONObject.parseObject(value);
                 Message s= new Message(
                         jsonObject.getString("sessionId"),
                         jsonObject.getString("fromUid"), 
                         jsonObject.getString("toUid"),
                         jsonObject.getString("chatType"),

                         jsonObject.getString("type"),
                         jsonObject.getString("msgId"),
                         jsonObject.getString("msg"),
                         jsonObject.getLong("timestampSend")

                         );
                 return s;
            }
        });

        //设置水印，并过滤数据
        DataStream bean3DataStreamWithAssignTime = 
                bean3DataStream.assignTimestampsAndWatermarks(new TruckTimestamp()).timeWindowAll(Time.seconds(30),Time.seconds(15)).apply(new AllWindowFunction() {  
                    @Override
                    public void apply(TimeWindow window, Iterable values, Collector out)
                            throws Exception {
                        for (Message t: values) {
                            logger.info("window start time:"+new Date(window.getStart()).toString());
                            logger.info("real time:"+new Date(t.getTimestampSend()).toString());
                            if(t.getTimestampSend() appendStream =tableEnv.toAppendStream(tb3, Row.class);
//        appendStream.addSink(new Sink());

    //对过滤后的数据，使用正则匹配数据
        Table tb2 = tableEnv.sqlQuery(
                "SELECT " +
                        " * " +
                        "FROM myTable" +
                        " " +
                        "MATCH_RECOGNIZE ( " +
                        "PARTITION BY sessionId " +
                        "ORDER BY rowtime " +
                        "MEASURES " +
                        "e2.timestampSend as answerTime, "+
                        "LAST(e1.timestampSend) as customer_event_time, " +
                        "e2.fromUid as empUid, " +
                        "e1.timestampSend as askTime," +                      
                        "1 as total_talk " +          
                        "ONE ROW PER MATCH " +
                        "AFTER MATCH SKIP TO LAST e2 " +
                        "PATTERN (e1+ e2+?) " +
                        "DEFINE " +
                        "e1 as e1.type = 'yonghu', " +
                        "e2 as e2.type = 'guanjia' " +
                        ")"+
                        ""
                );

           DataStream appendStream2 =tableEnv.toAppendStream(tb2, Row.class);
           appendStream2.addSink(new Sink2());

           env.execute("msg v5");   

    }

    public static class TruckTimestamp extends AscendingTimestampExtractor {
        private static final long serialVersionUID = 1L;

        @Override
        public long extractAscendingTimestamp(Message element) {
            return element.getTimestampSend();
        }
    }

     public static class Sink implements SinkFunction {
            /**
         * 
         */
        private static final long serialVersionUID = 1L;

            @Override
            public void invoke(Row value) throws Exception {
                System.out.println(new Date().toString()+"orinal time:"+value.toString());
            }
        }

     public static class Sink2 implements SinkFunction {
            /**
         * 
         */
        private static final long serialVersionUID = 1L;

            @Override
            public void invoke(Row value) throws Exception {
                System.out.println(new Date().toString()+"new time:"+value.toString());
            }
        }

当前标题：利用flink统计消息回复情况
当前路径：http://chengdu.cdxwcx.cn/article/igsdsj.html