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Spring Complex Event Forecasting Engine

Synopsis​

This operator deploys the Spring Complex Event Forecasting Engine (CEF) on the provided Flink cluster and uses it to perform complex event forecasting on financial, streamed data events in a streaming analytic workflow.

Description​

This operators first deploys the Spring CEF Engine to the Flink cluster provided at the flink-connection input port. During start of the engine the required parameters are provided to the CEF by the operator. In addition, the required topics (input and output) on the kafka cluster for communication with the engine are created as well.

The operator pushes the data events received at the input stream port to the input kafka topic. The Spring CEF Engine performs the complex event forecasting

The operator reads from the output topic of the kafka cluster and pushes the detected complex events further downstream (to the output stream port).

This is a streaming operator and needs to be placed inside a Streaming Nest or a Streaming Optimization operator. The operator defines the logical functionality and can be used in all streaming analytic workflow for any supported streaming platform (currently Flink and Spark). The actual implementation used depends on the type of connection connected to the Streaming Nest operator in which this operator is placed.

Input​

kafka-connection​

The connection to the Kafka Cluster which is used by the CEF Engine for communication.

The connection to the Flink Cluster which on which the CEF Engine shall be deployed.

input stream​

The input of this streaming operation. It needs to receive the output of a preceding streaming operator, to define the flow of data events in the streaming analytic workflow.

Output​

output stream​

The output of this streaming operation. Connect it to the next streaming operator to define the flow of the data events in the designed streaming analytic workflow.

Parameters​

Pattern length​

Length of the estimated pattern.

Step length​

Step length that is used in historical data. Usually: 1

Forecast horizon​

The length of the projection into the future.

Precision​

The minimum correlation value to detect patterns.

Length​

Training example size (i.e. first N stocks will be used for initialisation).

Input topic​

Name of the Kafka topic used by the Spring CEF Engine to receive input data events

Output topic​

Name of the Kafka topic used by the Spring CEF Engine to push output data events to.

Job jar​

Path to the .jar file of the Spring CEF Engine.

Parallelism​

Parallelism of the Spring CEF Flink job.