我必须收集在3个卡夫卡采购流3个事件具有在给定的时间相同的correlationID,并能够收集这些事件的全部或部分,如果他们迟到。为什么可以将PatternStream的相同事件发送到PatternSelectFunction和PatternTimeoutFunction?
我用在3的数据流中和CEP图案联合。但是我注意到与模式匹配的事件因此在select函数中收集的事件也会在超时函数中发送到超时函数。
我不知道我做错了什么在我的例子,或者什么,我听不懂,但我期待的是那是正匹配的事件是不是也处于超时。
我得到的印象是不相交的时间快照存储。
我'使用1.3.0版本弗林克。
谢谢你的帮助。
控制台输出,在这里我们可以看到,3个相关的事件2被选择和timeouted:
匹配事件:
关键--- 0b3c116e-0703-43cb-8b3e-54b0b5e93948
密钥 - --f969dd4d-47ff-445℃,9182-0f95a569febb
关键--- 2ecbb89d-1463-4669-a657-555f73b6fb1d
超时事件:
第一次调用超时功能:
关键--- f969dd4d-47ff-445℃,9182-0f95a569febb
关键--- 0b3c116e-0703-43cb-8b3e-54b0b5e93948
第二个电话:
关键--- f969dd4d-47ff-445℃,9182- 0f95a569febb
11:01:44,677 INFO com.bnpp.pe.cep.Main - Matching events:
11:01:44,678 INFO com.bnpp.pe.cep.Main - SctRequestProcessStep2Event(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---0b3c116e-0703-43cb-8b3e-54b0b5e93948, debtorIban=BE42063929068055, creditorIban=BE42063929068056, amount=100.0, communication=test), succeeded=false)
11:01:44,678 INFO com.bnpp.pe.cep.Main - SctRequestProcessStep1Event(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---2ecbb89d-1463-4669-a657-555f73b6fb1d, debtorIban=BE42063929068055, creditorIban=BE42063929068056, amount=100.0, communication=test), succeeded=false)
11:01:44,678 INFO com.bnpp.pe.cep.Main - SctRequestProcessStep3Event(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---f969dd4d-47ff-445c-9182-0f95a569febb, debtorIban=BE42063929068055, creditorIban=BE42063929068056, amount=100.0, communication=test), succeeded=false)
Right(SctRequestFinalEvent(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---2196fdb0-01e8-4cc6-af4b-04bcf9dc67a2, debtorIban=null, creditorIban=null, amount=null, communication=null), state=SUCCESS))
11:01:49,635 INFO com.bnpp.pe.cep.Main - Timed out events:
11:01:49,636 INFO com.bnpp.pe.cep.Main - SctRequestProcessStep3Event(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---f969dd4d-47ff-445c-9182-0f95a569febb, debtorIban=BE42063929068055, creditorIban=BE42063929068056, amount=100.0, communication=test), succeeded=false)
11:01:49,636 INFO com.bnpp.pe.cep.Main - SctRequestProcessStep2Event(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---0b3c116e-0703-43cb-8b3e-54b0b5e93948, debtorIban=BE42063929068055, creditorIban=BE42063929068056, amount=100.0, communication=test), succeeded=false)
11:01:49,636 INFO com.bnpp.pe.cep.Main - Timed out events:
11:01:49,636 INFO com.bnpp.pe.cep.Main - SctRequestProcessStep3Event(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---f969dd4d-47ff-445c-9182-0f95a569febb, debtorIban=BE42063929068055, creditorIban=BE42063929068056, amount=100.0, communication=test), succeeded=false)
Left(SctRequestFinalEvent(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---aa437bcf-ecaa-4561-9f4e-08a902f0e248, debtorIban=null, creditorIban=null, amount=null, communication=null), state=FAILED))
Left(SctRequestFinalEvent(super=SctRequestEvent(correlationId=cId---a14a4e23-56c5-4242-9c43-d465d2b84454, key=Key---5420eb41-2723-42ac-83fd-d203d6bf2526, debtorIban=null, creditorIban=null, amount=null, communication=null), state=FAILED))
我的测试代码:
package com.bnpp.pe.cep;
import com.bnpp.pe.event.Event;
import com.bnpp.pe.event.SctRequestFinalEvent;
import com.bnpp.pe.util.EventHelper;
import lombok.extern.slf4j.Slf4j;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.cep.CEP;
import org.apache.flink.cep.PatternSelectFunction;
import org.apache.flink.cep.PatternStream;
import org.apache.flink.cep.PatternTimeoutFunction;
import org.apache.flink.cep.pattern.Pattern;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010;
import org.apache.flink.streaming.util.serialization.DeserializationSchema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import java.util.Properties;
/**
* Created by Laurent Bauchau on 2/08/2017.
*/
@Slf4j
public class Main implements Serializable {
public static void main(String... args) {
new Main();
}
public static final String step1Topic = "sctinst-step1";
public static final String step2Topic = "sctinst-step2";
public static final String step3Topic = "sctinst-step3";
private static final String PATTERN_NAME = "the_3_correlated_events_pattern";
private final FlinkKafkaConsumer010<Event> kafkaSource1;
private final DeserializationSchema<Event> deserializationSchema1;
private final FlinkKafkaConsumer010<Event> kafkaSource2;
private final DeserializationSchema<Event> deserializationSchema2;
private final FlinkKafkaConsumer010<Event> kafkaSource3;
private final DeserializationSchema<Event> deserializationSchema3;
private Main() {
// Kafka init
Properties kafkaProperties = new Properties();
kafkaProperties.setProperty("bootstrap.servers", "localhost:9092");
kafkaProperties.setProperty("zookeeper.connect", "localhost:2180");
kafkaProperties.setProperty("group.id", "sct-validation-cgroup1");
deserializationSchema1 = new SctRequestProcessStep1EventDeserializer();
kafkaSource1 = new FlinkKafkaConsumer010<>(step1Topic, deserializationSchema1, kafkaProperties);
deserializationSchema2 = new SctRequestProcessStep2EventDeserializer();
kafkaSource2 = new FlinkKafkaConsumer010<>(step2Topic, deserializationSchema2, kafkaProperties);
deserializationSchema3 = new SctRequestProcessStep3EventDeserializer();
kafkaSource3 = new FlinkKafkaConsumer010<>(step3Topic, deserializationSchema3, kafkaProperties);
try {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
DataStream<Event> s1 = env.addSource(kafkaSource1);
DataStream<Event> s2 = env.addSource(kafkaSource2);
DataStream<Event> s3 = env.addSource(kafkaSource3);
DataStream<Event> unionStream = s1.union(s2, s3);
Pattern successPattern = Pattern.<Event>begin(PATTERN_NAME)
.times(3)
.within(Time.seconds(5));
PatternStream<Event> matchingStream = CEP.pattern(
unionStream.keyBy(new CIDKeySelector()),
successPattern);
matchingStream.select(new MyPatternTimeoutFunction(), new MyPatternSelectFunction())
.print()
.setParallelism(1);
env.execute();
} catch (Exception e) {
log.error(e.getMessage(), e);
}
}
private static class MyPatternTimeoutFunction implements PatternTimeoutFunction<Event, SctRequestFinalEvent> {
@Override
public SctRequestFinalEvent timeout(Map<String, List<Event>> pattern, long timeoutTimestamp) throws Exception {
List<Event> events = pattern.get(PATTERN_NAME);
log.info("Timed out events:");
events.forEach(e -> log.info(e.toString()));
// Resulting event creation
SctRequestFinalEvent event = new SctRequestFinalEvent();
EventHelper.correlate(events.get(0), event);
EventHelper.injectKey(event);
event.setState(SctRequestFinalEvent.State.FAILED);
return event;
}
}
private static class MyPatternSelectFunction
implements PatternSelectFunction<Event, SctRequestFinalEvent> {
@Override
public SctRequestFinalEvent select(Map<String, List<Event>> pattern) throws Exception {
List<Event> events = pattern.get(PATTERN_NAME);
log.info("Matching events:");
events.forEach(e -> log.info(e.toString()));
// Resulting event creation
SctRequestFinalEvent event = new SctRequestFinalEvent();
EventHelper.correlate(events.get(0), event);
EventHelper.injectKey(event);
event.setState(SctRequestFinalEvent.State.SUCCESS);
return event;
}
}
private static class CIDKeySelector implements KeySelector<Event, String> {
@Override
public String getKey(Event event) throws Exception {
return event.getCorrelationId();
}
}
}
我明白你的意思,但在KeyedStream我的模式工作,仅包含3相关事件的时间和从未更多,和我在卡夫卡只发送3相关事件上运行我的测试: 刚(A ,B,C)和(A,B,C)匹配,在这种情况下,我不明白为什么我收到(A,C)和(C)作为部分匹配事件的超时? –
了解!谢谢。 –