This repository contains different examples for deploying Driverless AI (DAI) scorers.
The goal of the examples in this repo is to easily convey the necessary steps.
To this end, we aim to have the examples:
- self-contained
- simple
In production deployments, the following points should be considered:
- test coverage
- code reuse
- error handling
- monitoring
In other words, here we prioritize simple to follow steps over production readiness. See https://github.com/h2oai/dai-deployment-templates for production ready deployment templates.
- UDF for Running the MOJO in Database
- This example walks through how to use the MOJO as a UDF within in SQL database that has a JDBC type 4 driver.
- UDF for Running the MOJO in Hive
- This example will walk through how to use the MOJO as a UDF within a HIVE, a database that does not have a JDBC type 4 driver.
- Python Scoring Pipeline Examples
- These examples are based off of the README.txt that comes with the Python Scoring Pipeline and details the many ways it could be used. Here, each example is standalone and has step-by-step instructions for preparing your environment and testing that the setup with successful.
- Available Examples:
- Flink Custom RichMapFunction for Running the MOJO in Flink Data Pipeline
- This example will walk through how to use a Flink custom RichMapFunction to execute the MOJO Scoring Pipeline within a Flink Data Pipeline to do batch scoring and real-time scoring.
- Deploy Driverless AI MOJO Scoring Pipeline within a NiFi Data Flow
- This example will walk through how to use a NiFi custom processor to execute the MOJO Scoring Pipeline within a NiFi Data Flow to do batch scoring and real-time scoring.
- Deploy Driverless AI MOJO Scoring Pipeline in a MiNiFi C++ Data Flow with CEM
- This example will walk through how to install Cloudera Edge Management, which includes Edge Flow Manager, NiFi Registry and one MiNiFi C++ Agent and Driverless AI MOJO2 Python Runtime on an EC2 instance. It will then go through how to use EFM to build a data flow with Driverless AI MOJO Scoring Pipeline for a MiNiFi C++ Agent and publish that data flow to that agent. With Cloudera Ege Management and Driverless AI MOJO Scoring Pipeline integration, pushing ML models to an edge device is much easier.