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| <h1>predictionio</h1><span class="permalink"> |
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| <div id="comment" class="fullcommenttop"><div class="comment cmt"><p>PredictionIO Scala API</p></div><div class="toggleContainer block"> |
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| <p class="shortcomment cmt">Provides building blocks for writing a complete prediction engine |
| consisting of DataSource, Preparator, Algorithm, Serving, and Evaluation.</p><div class="fullcomment"><div class="comment cmt"><p>Provides building blocks for writing a complete prediction engine |
| consisting of DataSource, Preparator, Algorithm, Serving, and Evaluation.</p><h4> Start Building an Engine </h4><p>The starting point of a prediction engine is the <a href="controller/Engine.html" class="extype" name="org.apache.predictionio.controller.Engine">Engine</a> class.</p><h4> The DASE Paradigm </h4><p>The building blocks together form the DASE paradigm. Learn more about DASE |
| <a href="http://predictionio.apache.org/customize/" target="_blank">here</a>.</p><h4> Types of Building Blocks </h4><p>Depending on the problem you are solving, you would need to pick appropriate |
| flavors of building blocks.</p><h5> Engines </h5><p>There are 3 typical engine configurations:</p><ol class="decimal"><li><a href="controller/PDataSource.html" class="extype" name="org.apache.predictionio.controller.PDataSource">PDataSource</a>, <a href="controller/PPreparator.html" class="extype" name="org.apache.predictionio.controller.PPreparator">PPreparator</a>, <a href="controller/P2LAlgorithm.html" class="extype" name="org.apache.predictionio.controller.P2LAlgorithm">P2LAlgorithm</a>, <a href="controller/LServing.html" class="extype" name="org.apache.predictionio.controller.LServing">LServing</a> |
| 2. <a href="controller/PDataSource.html" class="extype" name="org.apache.predictionio.controller.PDataSource">PDataSource</a>, <a href="controller/PPreparator.html" class="extype" name="org.apache.predictionio.controller.PPreparator">PPreparator</a>, <a href="controller/PAlgorithm.html" class="extype" name="org.apache.predictionio.controller.PAlgorithm">PAlgorithm</a>, <a href="controller/LServing.html" class="extype" name="org.apache.predictionio.controller.LServing">LServing</a> |
| 3. <a href="controller/LDataSource.html" class="extype" name="org.apache.predictionio.controller.LDataSource">LDataSource</a>, <a href="controller/LPreparator.html" class="extype" name="org.apache.predictionio.controller.LPreparator">LPreparator</a>, <a href="controller/LAlgorithm.html" class="extype" name="org.apache.predictionio.controller.LAlgorithm">LAlgorithm</a>, <a href="controller/LServing.html" class="extype" name="org.apache.predictionio.controller.LServing">LServing</a></li></ol><p>In both configurations 1 and 2, data is sourced and prepared in a |
| parallelized fashion, with data type as RDD.</p><p>The difference between configurations 1 and 2 come at the algorithm stage. |
| In configuration 1, the algorithm operates on potentially large data as RDDs |
| in the Spark cluster, and eventually outputs a model that is small enough to |
| fit in a single machine.</p><p>On the other hand, configuration 2 outputs a model that is potentially too |
| large to fit in a single machine, and must reside in the Spark cluster as |
| RDD(s).</p><p>With configuration 1 (<a href="controller/P2LAlgorithm.html" class="extype" name="org.apache.predictionio.controller.P2LAlgorithm">P2LAlgorithm</a>), PredictionIO will automatically |
| try to persist the model to local disk or HDFS if the model is serializable.</p><p>With configuration 2 (<a href="controller/PAlgorithm.html" class="extype" name="org.apache.predictionio.controller.PAlgorithm">PAlgorithm</a>), PredictionIO will not automatically |
| try to persist the model, unless the model implements the <a href="controller/PersistentModel.html" class="extype" name="org.apache.predictionio.controller.PersistentModel">PersistentModel</a> |
| trait.</p><p>In special circumstances where both the data and the model are small, |
| configuration 3 may be used. Beware that RDDs cannot be used with |
| configuration 3.</p><h5> Data Source </h5><p><a href="controller/PDataSource.html" class="extype" name="org.apache.predictionio.controller.PDataSource">PDataSource</a> is probably the most used data source base class with the |
| ability to process RDD-based data. <a href="controller/LDataSource.html" class="extype" name="org.apache.predictionio.controller.LDataSource">LDataSource</a> <b>cannot</b> handle |
| RDD-based data. Use only when you have a special requirement.</p><h5> Preparator </h5><p>With <a href="controller/PDataSource.html" class="extype" name="org.apache.predictionio.controller.PDataSource">PDataSource</a>, you must pick <a href="controller/PPreparator.html" class="extype" name="org.apache.predictionio.controller.PPreparator">PPreparator</a>. The same applies to |
| <a href="controller/LDataSource.html" class="extype" name="org.apache.predictionio.controller.LDataSource">LDataSource</a> and <a href="controller/LPreparator.html" class="extype" name="org.apache.predictionio.controller.LPreparator">LPreparator</a>.</p><h5> Algorithm </h5><p>The workhorse of the engine comes in 3 different flavors.</p><h6> P2LAlgorithm </h6><p>Produces a model that is small enough to fit in a single machine from |
| <a href="controller/PDataSource.html" class="extype" name="org.apache.predictionio.controller.PDataSource">PDataSource</a> and <a href="controller/PPreparator.html" class="extype" name="org.apache.predictionio.controller.PPreparator">PPreparator</a>. The model <b>cannot</b> contain any RDD. |
| If the produced model is serializable, PredictionIO will try to |
| automatically persist it. In addition, P2LAlgorithm.batchPredict is |
| already implemented for <a href="controller/Evaluation.html" class="extype" name="org.apache.predictionio.controller.Evaluation">Evaluation</a> purpose.</p><h6> PAlgorithm </h6><p>Produces a model that could contain RDDs from <a href="controller/PDataSource.html" class="extype" name="org.apache.predictionio.controller.PDataSource">PDataSource</a> and |
| <a href="controller/PPreparator.html" class="extype" name="org.apache.predictionio.controller.PPreparator">PPreparator</a>. PredictionIO will not try to persist it automatically |
| unless the model implements <a href="controller/PersistentModel.html" class="extype" name="org.apache.predictionio.controller.PersistentModel">PersistentModel</a>. <a href="controller/PAlgorithm.html#batchPredict(m:M,qs:org.apache.spark.rdd.RDD[(Long,Q)]):org.apache.spark.rdd.RDD[(Long,P)]" class="extmbr" name="org.apache.predictionio.controller.PAlgorithm#batchPredict">PAlgorithm.batchPredict</a> |
| must be implemented for <a href="controller/Evaluation.html" class="extype" name="org.apache.predictionio.controller.Evaluation">Evaluation</a>.</p><h6> LAlgorithm </h6><p>Produces a model that is small enough to fit in a single machine from |
| <a href="controller/LDataSource.html" class="extype" name="org.apache.predictionio.controller.LDataSource">LDataSource</a> and <a href="controller/LPreparator.html" class="extype" name="org.apache.predictionio.controller.LPreparator">LPreparator</a>. The model <b>cannot</b> contain any RDD. |
| If the produced model is serializable, PredictionIO will try to |
| automatically persist it. In addition, LAlgorithm.batchPredict is |
| already implemented for <a href="controller/Evaluation.html" class="extype" name="org.apache.predictionio.controller.Evaluation">Evaluation</a> purpose.</p><h5> Serving </h5><p>The serving component comes with only 1 flavor--<a href="controller/LServing.html" class="extype" name="org.apache.predictionio.controller.LServing">LServing</a>. At the serving |
| stage, it is assumed that the result being served is already at a human- |
| consumable size.</p><h4> Model Persistence </h4><p>PredictionIO tries its best to persist trained models automatically. Please |
| refer to <a href="controller/LAlgorithm.html#makePersistentModel(sc:org.apache.spark.SparkContext,modelId:String,algoParams:org.apache.predictionio.controller.Params,bm:Any):Any" class="extmbr" name="org.apache.predictionio.controller.LAlgorithm#makePersistentModel">LAlgorithm.makePersistentModel</a>, |
| <a href="controller/P2LAlgorithm.html#makePersistentModel(sc:org.apache.spark.SparkContext,modelId:String,algoParams:org.apache.predictionio.controller.Params,bm:Any):Any" class="extmbr" name="org.apache.predictionio.controller.P2LAlgorithm#makePersistentModel">P2LAlgorithm.makePersistentModel</a>, and <a href="controller/PAlgorithm.html#makePersistentModel(sc:org.apache.spark.SparkContext,modelId:String,algoParams:org.apache.predictionio.controller.Params,bm:Any):Any" class="extmbr" name="org.apache.predictionio.controller.PAlgorithm#makePersistentModel">PAlgorithm.makePersistentModel</a> |
| for descriptions on different strategies. |
| </p></div></div> |
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| <p class="shortcomment cmt">Core base classes of PredictionIO controller components.</p><div class="fullcomment"><div class="comment cmt"><p>Core base classes of PredictionIO controller components. Engine developers |
| should not use these directly. |
| </p></div></div> |
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| <p class="shortcomment cmt">Provides data access for PredictionIO and any engines running on top of |
| PredictionIO |
| </p> |
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| <p class="shortcomment cmt">Independent library of code that is useful for engine development and |
| evaluation |
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