前言
使用 flink 很长一段时间了，突然发现竟然没有计算过 pv uv，这可是 flink 常见的计算场景了，面试时也是常问题之一。故自己想了一个场景来计算一下。 基于 Flink 1.12
场景
外卖员听单的信息会发到单独一个 topic 中，计算一个每天有多少个 外卖员听单以及总共的听单次数。
kafka 中消息类型
代码语言：javascript复制{"locTime":"2020-12-28 12:32:23","courierId":12,"other":"aaa"}locTime：事件发生的时间，courierId 外卖员id
计算一天有多少个外卖员听单( UV )，总共听单多少次( PV )
代码
代码语言：javascript复制FlinkKafkaConsumer<String> consumer = new FlinkKafkaConsumer<String>(topics, new SimpleStringSchema(), properties);
FlinkHelp.setOffset(parameter, consumer);
consumer.assignTimestampsAndWatermarks(
WatermarkStrategy.<String>forMonotonousTimestamps()
.withTimestampAssigner(new SerializableTimestampAssigner<String>() {
@Override
public long extractTimestamp(String element, long recordTimestamp) {
String locTime = "";
try {
Map<String, Object> map = Json2Others.json2map(element);
locTime = map.get("locTime").toString();
} catch (IOException e) {
}
LocalDateTime startDateTime =
LocalDateTime.parse(locTime, DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"));
long milli = startDateTime.toInstant(OffsetDateTime.now().getOffset()).toEpochMilli();
return milli;
}
}).withIdleness(Duration.ofSeconds(1)));
env.addSource(consumer).filter(new FilterFunction<String>() {
@Override
public boolean filter(String value) throws Exception {
return true;
}
}).windowAll(TumblingEventTimeWindows.of(Time.days(1), Time.hours(-8)))
.allowedLateness(Time.minutes(1))
// .trigger(CountTrigger.of(5))// 其实多个 trigger 就是下一个 trigger 覆盖上一个 trigger
//用 event time 可能会导致 window 延迟触发，最好的解决办法是在 processingTime 的基础上添加对窗口的判断
// watermark 不会回退,所以如果消息早到的话( 乱序了，该相对来说晚到的消息早到了)，可能会导致窗口延迟触发
// 夸张一点的话，窗口不触发了，直到有大于等于 watermark triggerTime 的消息到达
// ContinuousProcessingTimeTrigger 一样
.trigger(ContinuousEventTimeTrigger.of(Time.seconds(30)))
//追历史数据的时候会有问题，可能历史数据不足 10s 就全部消费完毕，导致窗口不会被触发而被跳过，消费同理
// .trigger(ContinuousProcessingTimeTrigger.of(Time.seconds(10)))
//处理完毕后将 window state 中的数据清除掉
// 其实完全可以通过自定义 trigger 来达到 clear windowState 的目的 (Purge)
.evictor(TimeEvictor.of(Time.seconds(0), true))
.process(new ProcessAllWindowFunction<String, String, TimeWindow>() {
private JedisCluster jedisCluster;
private MapState<String, String> courierInfoMapState;
private MapStateDescriptor<String, String> mapStateDescriptor;
private MapStateDescriptor<String, Long> mapStateUVDescriptor;
private MapState<String, Long> courierInfoUVMapState;
private MapStateDescriptor<String, Long> mapStatePVDescriptor;
private MapState<String, Long> courierInfoPVMapState;
private String beforeDay = "";
private String currentDay = "";
@Override
public void open(Configuration parameters) throws Exception {
StateTtlConfig ttlConfig = StateTtlConfig
.newBuilder(org.apache.flink.api.common.time.Time.hours(25))
//default，不支持 eventTime 1.12.0
.setTtlTimeCharacteristic(StateTtlConfig.TtlTimeCharacteristic.ProcessingTime)
.cleanupInRocksdbCompactFilter(1000)
.setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite)//default
.setStateVisibility(StateTtlConfig.StateVisibility.NeverReturnExpired)
.build();
mapStateDescriptor =
new MapStateDescriptor<String, String>("courierInfos", TypeInformation.of(String.class), TypeInformation.of(String.class));
mapStateDescriptor.enableTimeToLive(ttlConfig);
courierInfoMapState = getRuntimeContext().getMapState(mapStateDescriptor);
mapStateUVDescriptor =
new MapStateDescriptor<String, Long>("courierUVStateDesc", TypeInformation.of(String.class), TypeInformation.of(Long.class));
mapStateUVDescriptor.enableTimeToLive(ttlConfig);
courierInfoUVMapState = getRuntimeContext().getMapState(mapStateUVDescriptor);
mapStatePVDescriptor =
new MapStateDescriptor<String, Long>("courierPVStateDesc", TypeInformation.of(String.class), TypeInformation.of(Long.class));
mapStatePVDescriptor.enableTimeToLive(ttlConfig);
courierInfoPVMapState = getRuntimeContext().getMapState(mapStatePVDescriptor);
jedisCluster = RedisUtil.getJedisCluster(redisHp);
}
@Override
public void close() throws Exception {
RedisUtil.closeConn(jedisCluster);
}
@Override
public void process(Context context, Iterable<String> elements, Collector<String> out) throws Exception {
Iterator<String> iterator = elements.iterator();
TimeWindow window = context.window();
System.out.println(" window = "
DateUtils.millisecondsToDateStr(window.getStart(), "yyyy-MM-dd HH:mm:ss")
"-" DateUtils.millisecondsToDateStr(window.getEnd(), "yyyy-MM-dd HH:mm:ss"));
while (iterator.hasNext()) {
Map<String, Object> map = Json2Others.json2map(iterator.next());
String courierId = map.get("courierId").toString();
String day = map.get("locTime").toString().split(" ")[0].replace("-", "");
if (courierInfoPVMapState.contains(day)) {
courierInfoPVMapState.put(day, courierInfoPVMapState.get(day) 1);
} else {
courierInfoPVMapState.put(day, 1L);
}
if (!courierInfoMapState.contains(day "-" courierId)) {
if (courierInfoUVMapState.contains(day)) {
courierInfoUVMapState.put(day, courierInfoUVMapState.get(day) 1);
} else {
courierInfoUVMapState.put(day, 1L);
}
courierInfoMapState.put(day "-" courierId, "");
}
currentDay = day;
}
HashMap<String, String> map = new HashMap<String, String>();
if (currentDay.equals(beforeDay)) {
map.put(currentDay "-pv", courierInfoPVMapState.get(currentDay).toString());
map.put(currentDay "-uv", courierInfoUVMapState.get(currentDay).toString());
} else {
map.put(currentDay "-pv", courierInfoPVMapState.get(currentDay).toString());
map.put(currentDay "-uv", courierInfoUVMapState.get(currentDay).toString());
//超过25个小时，昨天的数据就不对了
if (!beforeDay.isEmpty()) {
map.put(beforeDay "-pv", courierInfoPVMapState.get(beforeDay).toString());
map.put(beforeDay "-uv", courierInfoUVMapState.get(beforeDay).toString());
}
}
map.forEach((k, v) -> {
System.out.println(k ":" v);
});
jedisCluster.hmset("test_courier_puv:", map);
jedisCluster.expire("test_courier_puv:", 3 * 24 * 60 * 60);
beforeDay = currentDay;
}
});结果样例
