Mule concepts flows
Download as PPTX, PDF0 likes726 views
Mule applications use flows and batch jobs to process messages. Flows contain a series of message processors that accept and process messages as they flow through. Batch jobs split large messages into individual records and process them asynchronously through batch steps. The key components of flows and batch jobs are message sources that input messages, message processors that transform or route messages, and connectors that integrate with external systems.
Mule concepts flows
- 1. Mule Concepts Flows and Batch Jobs
- 2. • Based on the concept of Event Driven Architecture (EDA). • Works by responding to messages initiated by external resources (such as, events). • Mule applications accept and process events as messages through several message processors plugged together in a flow. • Large or streaming messages can be processed as records in a batch job. Mule Concepts : Intro
- 3. • Every Mule flow contains a series of message processors that accept, then process messages. • Mule applications usually contain multiple linked flows and/or batch jobs. • These applications perform the integration required for the use case. Mule Concepts : Intro
- 4. Mule Concepts : Intro • Every Mule Applications can consists of below : – Flows – Batch Jobs
- 5. Mule Concepts : Flows • A flow is the construct within which you link together several individual elements to handle the receipt, processing, and eventual routing of a message. • Flows are sequences of message-processing events. • A message that enters a flow may pass through a wide variety of processors. • Multiple flows can be connected together to build a complete application.
- 6. Mule Concepts : Flows • As shown in below diagram, each flow consists of: – Message Source – Message Processors
- 7. Mule Concepts : Batch Jobs • A top-level element in Mule that exists outside all Mule flows. • provides record I/O for Mule message processing. • Batch jobs split large messages into records which Mule processes asynchronously. • Just as flows process messages, batch jobs process records.
- 8. Mule Concepts : Batch Jobs • Contains one or more batch steps. • Each batch step contains any number of message processors that act upon records as they move through the batch job. • record-level variables (recordVars) and MEL (Mule Expression Language) expressions to enrich, route or otherwise act upon records.
- 9. Mule Concepts : Batch Jobs • A batch job is executes when : – Triggered by a batch executor in a Mule flow, or – Message source in a batch-accepting input. • When triggered, Mule creates a new batch job instance. • Once every record has passed through all batch steps, the batch job instance ends and the batch job result can be summarized in a report. • Report indicates which records succeeded and which failed.
- 10. Mule Concepts : Message Sources • Mule processes messages, also known as events, which may be transmitted from resources external to Mule. • First building block of most flows or batch jobs is a message receiver. • Receiver receives new messages and places them in the queue for processing. • These Receivers are the Message Sources. • Message Sources on receiving of the messages from one or more external sources trigger the execution of the flow or the batch job.
- 11. Mule Concepts : Message Sources • Message sources in Mule are usually Anypoint Connectors. • Anypoint Connectors elements provide connectivity to a specific external source. • The connectivity is provided via a standard protocol (such as HTTP, FTP, SMTP) or a third- party API (such as Salesforce.com, Twitter, or MongoDB.)
- 12. Mule Concepts : Message Processors • Mule processors are the elements which acts on the received messages and perform operations to modify the message or to create a new one. • In Mule, message processors are grouped together by category.
- 13. Mule Concepts : Message Processors • Message Processors are grouped in below categories: – Message Transformers : • key to exchanging data between nodes • Allow Mule to convert message payload data to a format that another application can understand. • Through Message Enrichers Mule enables to retrieve additional data during processing and attach it to the message. – Components : • To conduct backend processes for specific business logic. • Components route messages to the correct application. • Components don’t have to have any Mule-specific code. • They can simply be POJOs, Spring beans, Java beans, Groovy scripts, or web services containing the business logic for processing data. • Components can even be developed in other languages such as Python, JavaScript, Ruby, and PHP.
- 14. Mule Concepts : Message Processors • Message Processors are grouped in below categories: – Filters : • To filter out the messages based on the set criteria. – Scopes : • To "wrap" around several message processors together as a single unit. E.g. Cache the result of the processing they perform – Routers : • To send messages down different paths in your application depending on the content of the message payload. – Mainly Mule Expression Language is used to extract information about the message or its environment and instruct Mule to make processing decisions based on that information.