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From "Ananda Verma (JIRA)" <>
Subject [jira] [Updated] (AMBARI-18622) Integrate PredictionIO (Machine Learning Engine) With Ambari
Date Fri, 31 Mar 2017 17:42:41 GMT


Ananda Verma updated AMBARI-18622:
    Issue Type: Epic  (was: New Feature)

> Integrate PredictionIO (Machine Learning Engine) With Ambari
> ------------------------------------------------------------
>                 Key: AMBARI-18622
>                 URL:
>             Project: Ambari
>          Issue Type: Epic
>          Components: ambari-server
>    Affects Versions: 2.4.1
>            Reporter: Ananda Verma
> It makes sense to integrate PredictionIO with Ambari since it is now part of apache group
and also heavily depends on current amabri/hdp stack.  
> Feature includes adding support for apache predictionIO cluster provisioning via Ambari.
> In general, pio can be defined as a service in HDP which has following components - 
> 1) Event Server  - stores events (data)
> 2) Engine - Engine is responsible for making prediction. It contains one or more machine
learning algorithms. An engine reads training data and build predictive model(s). It is then
deployed as a web service. A deployed engine responds to prediction queries from your application
through REST API in real-time.
> PredictionIO also has external dependencies on following  - 
> 1. HBase: Event Server uses Apache HBase as the data store. It stores imported events.
If you are not using the PredictionIO Event Server, you do not need to install HBase.
> 2. Apache Spark: Spark is a large-scale data processing engine that powers the algorithm,
training, and serving processing.
> 3. HDFS: The output of training has two parts: a model and its meta-data. The model is
then stored in HDFS or a local file system.
> 4. Elasticsearch: It stores metadata such as model versions, engine versions, access
key and app id mappings, evaluation results, etc.

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