Glossary
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Ability to send downstream systems an alert that is based upon a logical having expression.
Generate stream based using a suite of features such as predictive scores, time based windows, aggregates, user define functions, scripts and expressions.
Query Joule runtime internal database using API with pre-defined and registered SQL queries.
A Joule connector provides the ability to subscribe and publish events using a stream based processing paradigm. See section for more information.
Data sink provide the integration fabric to downstream event consumers using custom data formats such as AVRO, parquet, JSON and CSV.
Data sources enable Joule to consume real-time streaming events and files using pre-defined data structures.
Events are from the Joule process to connected consumers using a select based projection.
To improve throughput performance Joule applies small batches of events within a discrete processing cycle. This improves JVM memory management while optimising processing throughput.
Out Of The Box features provided by the Joule platform.
Pipelines consist of one or more processors which invoked in the sequence of which they have been defined.
Either part of or complete function of tasks that form an automatable digital business function.
Joule defines stream processing use cases using a iterative development approach coupled with a SDK that enables developers to extend platform capabilities.
Processors perform a single function of work on a single event. Functions such as analytics, filters, enrichment and transformation are examples of .
To extend the platform capabilities beyond the OOTB analytics, data connectors and processors a is provided.
The key data structure within Joule is the . This abstract data type provides the ability to provide a ubiquitous computation and development model for all platform components.