Ajay created FLINK-7782:
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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.
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