Complex Event Processing on top of Kafka Streams Processor API !

Apache Kafka is a high-throughput, distributed, publish-subscribe messaging system.

This repository is not stable - This library is still in progress (use at your own risk)

Demonstration

The below example is based on the research paper Efficient Pattern Matching over Event Streams.

Implementation based on https://people.cs.umass.edu/~yanlei/publications/sase-sigmod08.pdf

CEP Query :

     PATTERN SEQ(Stock+ a[ ], Stock b)
       WHERE skip_till_next_match(a[ ], b) {
           [symbol]
       and
           a[1].volume > 1000
       and
           a[i].price > avg(a[..i-1].price)
       and
           b.volume < 80%*a[a.LEN].volume }
       WITHIN 1 hour

KafkaStreams implementation:

        Pattern<Object, StockEvent> pattern = new QueryBuilder<Object, StockEvent>()
                .select()
                    .where((k, v, ts, store) -> v.volume > 1000)
                    .<Integer>fold("avg", (k, v, curr) -> v.price)
                    .then()
                .select()
                    .oneOrMore()
                    .skipTillNextMatch()
                    .where((k, v, ts, state) -> v.price > (int)state.get("avg"))
                    .<Integer>fold("avg", (k, v, curr) -> (curr + v.price) / 2)
                    .<Integer>fold("volume", (k, v, curr) -> v.volume)
                    .then()
                .select()
                    .skipTillNextMatch()
                    .where((k, v, ts, state) -> v.volume < (0.8 *  (int)state.get("volume")))
                    .within(1, TimeUnit.HOURS)
                .build();

        TopologyBuilder topologyBuilder = new TopologyBuilder();
        topologyBuilder.addSource("source", "StockEvents")
                .addProcessor("cep", () -> new CEPProcessor<>(query), "source");

        //Use the topologyBuilder and streamingConfig to start the kafka streams process
        KafkaStreams streaming = new KafkaStreams(topologyBuilder, props);
        streaming.start();

Demo

Run the demonstration class CEPStockKStreamsDemo :

• Produce the following json events StockEvents:

./bin/kafka-console-producer --topic StockEvents --broker-list localhost:9092

• Input

{"name":"e1","price":100,"volume":1010}
{"name":"e2","price":120,"volume":990}
{"name":"e3","price":120,"volume":1005}
{"name":"e4","price":121,"volume":999}
{"name":"e5","price":120,"volume":999}
{"name":"e6","price":125,"volume":750}
{"name":"e7","price":120,"volume":950}
{"name":"e8","price":120,"volume":700}

• Consume from the sink topic "matches"

./bin/kafka-console-consumer --new-consumer --topic matches --bootstrap-server localhost:9092

• Output

{"0":["e1"],"1":["e2","e3","e4","e5"],"2":["e6"]}
{"0":["e3"],"1":["e4"],"2":["e6"]}
{"0":["e1"],"1":["e2","e3","e4","e5","e6","e7"],"2":["e8"]}
{"0":["e3"],"1":["e4","e6"],"2":["e8"]}

Support for event selection strategies

• Strict contiguity
• Skip till next match
• Skip till any match

TODO

• Improve test scenarios
• Allow to define multiple pattern queries per topic.
• NFA is not currently tolerant to at-least once semantic (keep a high water mark)

###Licence Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

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