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From "Ananda Verma (JIRA)" <j...@apache.org>
Subject [jira] [Created] (AMBARI-18622) Integrate PredictionIO (Machine Learning Engine) With Ambari
Date Tue, 18 Oct 2016 05:50:58 GMT
Ananda Verma created AMBARI-18622:
-------------------------------------

             Summary: Integrate PredictionIO (Machine Learning Engine) With Ambari
                 Key: AMBARI-18622
                 URL: https://issues.apache.org/jira/browse/AMBARI-18622
             Project: Ambari
          Issue Type: New Feature
          Components: ambari-server
    Affects Versions: 2.1.0
            Reporter: Ananda Verma


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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