Joule
  • Welcome to Joule's Docs
  • Why Joule?
    • Joule capabilities
  • What is Joule?
    • Key features
    • The tech stack
  • Use case enablement
    • Use case building framework
  • Concepts
    • Core concepts
    • Low code development
    • Unified execution engine
    • Batch and stream processing
    • Continuous metrics
    • Key Joule data types
      • StreamEvent object
      • Contextual data
      • GeoNode
  • Tutorials
    • Getting started
    • Build your first use case
    • Stream sliding window quote analytics
    • Advanced tutorials
      • Custom missing value processor
      • Stateless Bollinger band analytics
      • IoT device control
  • FAQ
  • Glossary
  • Components
    • Pipelines
      • Use case anatomy
      • Data priming
        • Types of import
      • Processing unit
      • Group by
      • Emit computed events
      • Telemetry auditing
    • Processors
      • Common attributes
      • Filters
        • By type
        • By expression
        • Send on delta
        • Remove attributes
        • Drop all events
      • Enrichment
        • Key concepts
          • Anatomy of enrichment DSL
          • Banking example
        • Metrics
        • Dynamic contextual data
          • Caching architecture
        • Static contextual data
      • Transformation
        • Field Tokeniser
        • Obfuscation
          • Encryption
          • Masking
          • Bucketing
          • Redaction
      • Triggers
        • Change Data Capture
        • Business rules
      • Stream join
        • Inner stream joins
        • Outer stream joins
        • Join attributes & policy
      • Event tap
        • Anatomy of a Tap
        • SQL Queries
    • Analytics
      • Analytic tools
        • User defined analytics
          • Streaming analytics example
          • User defined analytics
          • User defined scripts
          • User defined functions
            • Average function library
        • Window analytics
          • Tumbling window
          • Sliding window
          • Aggregate functions
        • Analytic functions
          • Stateful
            • Exponential moving average
            • Rolling Sum
          • Stateless
            • Normalisation
              • Absolute max
              • Min max
              • Standardisation
              • Mean
              • Log
              • Z-Score
            • Scaling
              • Unit scale
              • Robust Scale
            • Statistics
              • Statistic summaries
              • Weighted moving average
              • Simple moving average
              • Count
            • General
              • Euclidean
        • Advanced analytics
          • Geospatial
            • Entity geo tracker
            • Geofence occupancy trigger
            • Geo search
            • IP address resolver
            • Reverse geocoding
            • Spatial Index
          • HyperLogLog
          • Distinct counter
      • ML inferencing
        • Feature engineering
          • Scripting
          • Scaling
          • Transform
        • Online predictive analytics
        • Model audit
        • Model management
      • Metrics engine
        • Create metrics
        • Apply metrics
        • Manage metrics
        • Priming metrics
    • Contextual data
      • Architecture
      • Configuration
      • MinIO S3
      • Apache Geode
    • Connectors
      • Sources
        • Kafka
          • Ingestion
        • RabbitMQ
          • Further RabbitMQ configurations
        • MQTT
          • Topic wildcards
          • Session management
          • Last Will and Testament
        • Rest endpoints
        • MinIO S3
        • File watcher
      • Sinks
        • Kafka
        • RabbitMQ
          • Further configurations
        • MQTT
          • Persistent messaging
          • Last Will and Testament
        • SQL databases
        • InfluxDB
        • MongoDB
        • Geode
        • WebSocket endpoint
        • MinIO S3
        • File transport
        • Slack
        • Email
      • Serialisers
        • Serialisation
          • Custom transform example
          • Formatters
        • Deserialisers
          • Custom parsing example
    • Observability
      • Enabling JMX for Joule
      • Meters
      • Metrics API
  • DEVELOPER GUIDES
    • Setting up developer environment
      • Environment setup
      • Build and deploy
      • Install Joule
        • Install Docker demo environment
        • Install with Docker
        • Install from source
        • Install Joule examples
    • Joulectl CLI
    • API Endpoints
      • Mangement API
        • Use case
        • Pipelines
        • Data connectors
        • Contextual data
      • Data access API
        • Query
        • Upload
        • WebSocket
      • SQL support
    • Builder SDK
      • Connector API
        • Sources
          • StreamEventParser API
        • Sinks
          • CustomTransformer API
      • Processor API
      • Analytics API
        • Create custom metrics
        • Define analytics
        • Windows API
        • SQL queries
      • Transformation API
        • Obfuscation API
        • FieldTokenizer API
      • File processing
      • Data types
        • StreamEvent
        • ReferenceDataObject
        • GeoNode
    • System configuration
      • System properties
  • Deployment strategies
    • Deployment Overview
    • Single Node
    • Cluster
    • GuardianDB
    • Packaging
      • Containers
      • Bare metal
  • Product updates
    • Public Roadmap
    • Release Notes
      • v1.2.0 Join Streams with stateful analytics
      • v1.1.0 Streaming analytics enhancements
      • v1.0.4 Predictive stream processing
      • v1.0.3 Contextual SQL based metrics
    • Change history
Powered by GitBook
On this page
  • Objective
  • Uses
  • Example & DSL attributes
  • Attributes schema

Was this helpful?

  1. Components
  2. Processors
  3. Triggers

Change Data Capture

Distribute delta records for key attribute changes

Objective

Change Data Capture (CDC) processor identifies and processes only data that has changed and then makes this changed data available for further use as a delta event.

Uses

The CDC process determines change based upon the previous values held for the tracking fields. This presents various uses for this processor such as:

  1. In financial services Provide a configurable inform on update consumer pattern. Implement a system where traders receive notifications only for changes in stock prices or account balances, rather than the entire transaction details, allowing for quicker decision-making.

  2. In healthcare Optimised delta processing for event consumers and receive updates only on specific tracking fields vs the full event. Enable healthcare providers to receive alerts about changes in patient data, such as medication dosages or vital signs, without needing the entire medical record, ensuring focused and timely responses.

  3. In retail Allow inventory management systems to inform staff only when stock levels change for specific items, rather than sending complete inventory reports, streamlining operations and improving response times.

Example & DSL attributes

This will emit changed StreamEvents keyed on symbol when either, OR function, the broker, bid or ask values change.

change data capture:
  key field: symbol
  tracking fields:
    - broker
    - bid
    - ask
  emit only changes: true
  drop duplicates: true

Attributes schema

Attribute
Description
Data Type
Required

key field

Key field to

String

fields

List of fields to track and determine changes

List<String>

emit only changes

A flag to emit only a delta event for the changes seen on the record. If set to false changes found will be will be added, as a map, to the CDC_FIELD event along with a CDC field being set to true to signify record availability

Boolean

Default: true

drop duplicates

Control flag which can be set to validate processor functionality at runtime. Use a JMX console to set

Boolean

Default: true

PreviousTriggersNextBusiness rules

Last updated 6 months ago

Was this helpful?