Ajay created FLINK-7782: --------------------------- Summary: Flink CEP not recognizing pattern Key: FLINK-7782 URL: https://issues.apache.org/jira/browse/FLINK-7782 Project: Flink Issue Type: Bug Reporter: Ajay
I am using flink version 1.3.2. Flink has a kafka source. I am using KafkaSource9. I am running Flink on a 3 node AWS cluster with 8G of RAM running Ubuntu 16.04. From the flink dashboard, I see that I have 2 Taskmanagers & 4 Task slots What I observe is the following. The input to Kafka is a json string and when parsed on the flink side, it looks like this {code:java} (101,Sun Sep 24 23:18:53 UTC 2017,complex event,High,37.75142,-122.39458,12.0,20.0) {code} I use a Tuple8 to capture the parsed data. The first field is home_id. The time characteristic is set to EventTime and I have an AscendingTimestampExtractor using the timestamp field. I have parallelism for the execution environment is set to 4. I have a rather simple event that I am trying to capture {code:java} DataStream<Tuple8<Integer,Date,String,String,Float,Float,Float, Float>> cepMapByHomeId = cepMap.keyBy(0); //cepMapByHomeId.print(); Pattern<Tuple8<Integer,Date,String,String,Float,Float,Float,Float>, ?> cep1 = Pattern.<Tuple8<Integer,Date,String,String,Float,Float,Float,Float>>begin("start") .where(new OverLowThreshold()) .followedBy("end") .where(new OverHighThreshold()); PatternStream<Tuple8<Integer, Date, String, String, Float, Float, Float, Float>> patternStream = CEP.pattern(cepMapByHomeId, cep1); DataStream<Tuple7<Integer, Date, Date, String, String, Float, Float>> alerts = patternStream.select(new PackageCapturedEvents()); {code} The pattern checks if the 7th field in the tuple8 goes over 12 and then over 16. The output of the pattern is like this {code:java} (201,Tue Sep 26 14:56:09 UTC 2017,Tue Sep 26 15:11:59 UTC 2017,complex event,Non-event,37.75837,-122.41467) {code} On the Kafka producer side, I am trying send simulated data for around 100 homes, so the home_id would go from 0-100 and the input is keyed by home_id. I have about 10 partitions in kafka. The producer just loops going through a csv file with a delay of about 100 ms between 2 rows of the csv file. The data is exactly the same for all 100 of the csv files except for home_id and the lat & long information. The timestamp is incremented by a step of 1 sec. I start multiple processes to simulate data form different homes. THE PROBLEM: Flink completely misses capturing events for a large subset of the input data. I barely see the events for about 4-5 of the home_id values. I do a print before applying the pattern and after and I see all home_ids before and only a tiny subset after. Since the data is exactly the same, I expect all homeid to be captured and written to my sink. -- This message was sent by Atlassian JIRA (v6.4.14#64029)