Chapter 1. Learning reactive machine learning
Listing 1.1. A simple model
Listing 1.2. A Pooch Predictor model
Chapter 2. Using reactive tools
Listing 2.1. A map of votes
Listing 2.2. Handling no votes using pattern matching
Listing 2.3. Setting default values on maps
Listing 2.4. A remote “database”
Listing 2.5. Futures-based remote calls
Listing 2.6. Futures-based timeouts
Listing 2.7. An unreliable database
Listing 2.8. A vote case class
Listing 2.9. A vote-writing actor
Listing 2.10. A supervisory actor
Listing 2.11. Full voting app
Listing 2.12. Basic Spark setup
Listing 2.13. Handling the data path
Listing 2.14. Loading training and testing data
Listing 2.15. Training a model
Listing 2.16. Testing a model
Listing 2.17. Model metrics
Listing 2.18. Saving a model
Chapter 3. Collecting data
Listing 3.1. Calculating location densities
Listing 3.2. Aggregating regional densities
Listing 3.3. Concurrently accessible densities
Listing 3.4. In-order updates
Listing 3.5. Out-of-order updates
Listing 3.6. Sensor-readings case class
Listing 3.7. Creating sensor-reading documents
Listing 3.8. Creating a sensor ID view
Listing 3.9. All records for a sensor
Listing 3.10. Inserting many random records
Listing 3.11. A time-based view of sensor readings