Getting Started with Streaming Analytics
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Contents

1. Building an End-to-End Stream Application
Understanding the Use Case
Reference Architecture
2. Prepare Your Environment
Deploying Your HDF Clusters
Registering Schemas in Schema Registry
Create the Kafka Topics
Register Schemas for the Kafka Topics
3. Creating a Dataflow Application
Data Producer Application Generates Events
NiFi: Create a Dataflow Application
NiFi Controller Services
NiFi Ingests the Raw Sensor Events
Publish Enriched Events to Kafka for Consumption by Analytics Applications
Start the NiFi Flow
4. Creating a Stream Analytics Application
Create a Service Pool and Environment
Create Your First Application
Creating and Configuring the Kafka Source Stream
Connecting Components
Joining Multiple Streams
Filtering Events in a Stream using Rules
Using Aggregate Functions over Windows
Implementing Business Rules on the Stream
Transforming Data using a Projection Processor
Creating Alerts with Notifications Sink
Streaming Alerts to an Analytics Engine for Dashboarding
Streaming Violation Events to an Analytics Engine for Descriptive Analytics
Streaming Violation Events into a Data Lake and Operational Data Store
5. Deploy an Application
Configure Deployment Settings
Deploy the App
Running the Stream Simulator
6. Stream Operations
My Applications View
Application Performance Monitoring
Troubleshooting and Debugging a Stream application
Streaming Engine Infrastructure Metrics
Changing Log Levels Dynamically and with Expiration Policies
Distributed Log Search
Exporting and Importing Stream applications
7. Advanced: Doing Predictive Analytics on the Stream
Logistical Regression Model
Export the Model into SAM's Model Registry
Enrichment and Normalization of Model Features
Setting up your Enrichment Store and Building Custom UDFs and Processors
Upload Custom Processors and UDFs for Enrichment and Normalization
Upload Custom UDFs
Upload Custom Processors
Scoring the Model in the Stream using a Streaming Split Join Pattern
Streaming Split Join Pattern
Score the Model using the PMML Processor and Alert
8. Creating Visualizations Using Superset
Creating Insight Slices
Adding Insight Slices to a Dashboard
Dashboards for the Trucking IOT App