| /** Copyright 2015 TappingStone, Inc. |
| * |
| * Licensed under the Apache License, Version 2.0 (the "License"); |
| * you may not use this file except in compliance with the License. |
| * You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| package io.prediction.controller |
| |
| import org.apache.spark.SparkContext |
| |
| /** Mix in and implement this trait if your model cannot be persisted by |
| * PredictionIO automatically. A companion object extending |
| * IPersistentModelLoader is required for PredictionIO to load the persisted |
| * model automatically during deployment. |
| * |
| * {{{ |
| * class MyModel extends IPersistentModel[MyParams] { |
| * def save(id: String, params: MyParams, sc: SparkContext): Boolean = { |
| * ... |
| * } |
| * } |
| * |
| * object MyModel extends IPersistentModelLoader[MyParams, MyModel] { |
| * def apply(id: String, params: MyParams, sc: Option[SparkContext]): MyModel = { |
| * ... |
| * } |
| * } |
| * }}} |
| * |
| * In Java, all you need to do is to implement this interface, and add a static |
| * method with 3 arguments of type String, [[Params]], and SparkContext. |
| * |
| * {{{ |
| * public class MyModel implements IPersistentModel<MyParams>, Serializable { |
| * ... |
| * public boolean save(String id, MyParams params, SparkContext sc) { |
| * ... |
| * } |
| * |
| * public static MyModel load(String id, Params params, SparkContext sc) { |
| * ... |
| * } |
| * ... |
| * } |
| * }}} |
| * |
| * @tparam AP Algorithm parameters class. |
| * @see [[IPersistentModelLoader]] |
| * @group Algorithm |
| */ |
| trait IPersistentModel[AP <: Params] { |
| /** Save the model to some persistent storage. |
| * |
| * This method should return true if the model has been saved successfully so |
| * that PredictionIO knows that it can be restored later during deployment. |
| * This method should return false if the model cannot be saved (or should |
| * not be saved due to configuration) so that PredictionIO will re-train the |
| * model during deployment. All arguments of this method are provided by |
| * automatically by PredictionIO. |
| * |
| * @param id ID of the run that trained this model. |
| * @param params Algorithm parameters that were used to train this model. |
| * @param sc An Apache Spark context. |
| */ |
| def save(id: String, params: AP, sc: SparkContext): Boolean |
| } |
| |
| /** Implement an object that extends this trait for PredictionIO to support |
| * loading a persisted model during serving deployment. |
| * |
| * @tparam AP Algorithm parameters class. |
| * @tparam M Model class. |
| * @see [[IPersistentModel]] |
| * @group Algorithm |
| */ |
| trait IPersistentModelLoader[AP <: Params, M] { |
| /** Implement this method to restore a persisted model that extends the |
| * [[IPersistentModel]] trait. All arguments of this method are provided |
| * automatically by PredictionIO. |
| * |
| * @param id ID of the run that trained this model. |
| * @param params Algorithm parameters that were used to train this model. |
| * @param sc An optional Apache Spark context. This will be injected if the |
| * model was generated by a [[PAlgorithm]]. |
| */ |
| def apply(id: String, params: AP, sc: Option[SparkContext]): M |
| } |
| |
| /** Mix in this trait if your model cannot be persisted to PredictionIO's |
| * metadata store for any reason and want to have it persisted to local |
| * filesystem instead. These traits contain concrete implementation and need |
| * not be implemented. |
| * |
| * {{{ |
| * class MyModel extends IFSPersistentModel[MyParams] { |
| * ... |
| * } |
| * |
| * object MyModel extends IFSPersistentModelLoader[MyParams, MyModel] { |
| * ... |
| * } |
| * }}} |
| * |
| * @tparam AP Algorithm parameters class. |
| * @see [[IFSPersistentModelLoader]] |
| * @group Algorithm |
| */ |
| trait IFSPersistentModel[AP <: Params] extends IPersistentModel[AP] { |
| def save(id: String, params: AP, sc: SparkContext): Boolean = { |
| Utils.save(id, this) |
| true |
| } |
| } |
| |
| /** Implement an object that extends this trait for PredictionIO to support |
| * loading a persisted model from local filesystem during serving deployment. |
| * |
| * @tparam AP Algorithm parameters class. |
| * @tparam M Model class. |
| * @see [[IFSPersistentModel]] |
| * @group Algorithm |
| */ |
| trait IFSPersistentModelLoader[AP <: Params, M] |
| extends IPersistentModelLoader[AP, M] { |
| def apply(id: String, params: AP, sc: Option[SparkContext]): M = { |
| Utils.load(id).asInstanceOf[M] |
| } |
| } |