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
  • API
  • Reference example

Was this helpful?

  1. DEVELOPER GUIDES
  2. Builder SDK
  3. Transformation API

Obfuscation API

Use the Obfuscation API to meet your requirements

API

To extend beyond the available obfuscation implementations the below interface is provided for developers to build and deploy new types.

The key method to be implemented is obfuscate.

/**
 * Base obfuscationType class type
 */
public interface ObfuscationType<T> extends CustomUserType {
    T obfuscate(Object value) throws ObfuscationException;

    default void validate() throws InvalidSpecificationException{}
}

Reference example

Below is a reference implementation of the date bucketing feature.

package com.fractalworks.streams.processors.obfuscation.types;

import com.fasterxml.jackson.annotation.JsonIgnore;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonRootName;
import com.fractalworks.streams.core.exceptions.InvalidSpecificationException;
import com.fractalworks.streams.processors.obfuscation.ObfuscationException;
import com.fractalworks.streams.processors.obfuscation.ObfuscationType;
import com.google.common.base.Objects;
import org.joda.time.DateTime;

import java.security.SecureRandom;

@JsonRootName(value = "date bucketing")
public class DateVarianceObfuscationType implements ObfuscationType<DateTime> {

    @JsonIgnore
    private final SecureRandom randomGenerator = new SecureRandom();

    private int variance = 120;

    public CustomVarianceObfuscationType() {
        // Required default constructor
    }

    @Override
    public DateTime obfuscate(Object value) throws ObfuscationException {
        if(value instanceof DateTime dateTimeValue){
            int days;
            do {
                days = (randomGenerator.nextInt() % variance);
            } while (days == 0);
            return (randomGenerator.nextBoolean() ? dateTimeValue.plusDays(days).plusMinutes(randomGenerator.nextInt() % variance) : dateTimeValue.minusDays(days).minusMinutes(randomGenerator.nextInt() % variance));
        } else
            throw new ObfuscationException("Passed data type is not supported for this function.");
    }

    public int getVariance() {
        return variance;
    }

    @JsonProperty(value = "variance")
    public void setVariance(int variance) {
        this.variance = variance;
    }

    @Override
    public boolean equals(Object o) {
        if (this == o) return true;
        if (o == null || getClass() != o.getClass()) return false;
        DateVarianceObfuscationType that = (DateVarianceObfuscationType) o;
        return variance == that.variance && Objects.equal(randomGenerator, that.randomGenerator);
    }

    @Override
    public void validate() throws InvalidSpecificationException {
        if( variance <=0){
            throw new InvalidSpecificationException("Invalid variance. Must be greater than zero");
        }
    }

    @Override
    public int hashCode() {
        return Objects.hashCode(randomGenerator, variance);
    }
}
PreviousTransformation APINextFieldTokenizer API

Last updated 6 months ago

Was this helpful?