Decision CEP engine is a Complex Event Processing platform built on Spark Streaming.

It is the result of combining the power of Spark Streaming as a continuous computing framework and Siddhi CEP engine as complex event processing engine.

Complex event processing, or CEP, is event processing that combines data from multiple sources to infer events or patterns that suggest more complicated circumstances.

CEP as a technique helps discover complex events by analyzing and correlating other events

• Engine
• Api
• Shell
• Examples
• Documentation

1 Stream Definition Language (SDL)

• Create, alter or drop a stream, add new queries or remove existing queries

2 Stream Manipulation Language (SML)

• Insert events into a stream and list the existing streams in the engine.

3 Stream Action Language (SAL)

• Listen to a stream (kafka), save the stream to Cassandra or mongoDB (auto-creation of tables), index the stream to ElasticSearch or Solr… here you should find useful operations ready to use.

• Start & Stop each action on-demand

4 Built-in functions

• Auditing all the requests in the decision engine (Cassandra or MongoDB)
• Statistics (requests per operation, requests per stream…)
• Failover system (recovering windows, streams and queries from Cassandra or MongoDB)

• Java & Scala API
• Simple programming model
• Available as maven dependency

• Autocomplete & help
• Tab-completion for stream names
• Built on the API

• It was presented in Spark Summit 2014 (link)
• Up to 10 million events per minute in a single node.
• It is fully open source.

See the changelog for changes.