PersistentModel

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.

Notice that models generated by PAlgorithm cannot be persisted automatically by nature and must implement these traits if model persistence is desired.

class MyModel extends PersistentModel[MyParams] {
  def save(id: String, params: MyParams, sc: SparkContext): Boolean = {
    ...
  }
}

object MyModel extends PersistentModelLoader[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 PersistentModel<MyParams>, Serializable {
...
public boolean save(String id, MyParams params, SparkContext sc) {
  ...
}

public static MyModel load(String id, Params params, SparkContext sc) {
  ...
}
...
}

AP: Algorithm parameters class.

See also: PersistentModelLoader

Linear Supertypes

AnyRef, Any

Known Subclasses

IFSPersistentModel, IPersistentModel, LocalFileSystemPersistentModel

Abstract Value Members

abstract def save(id: String, params: AP, sc: SparkContext): Boolean

Save the model to some persistent storage.
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.
id
ID of the run that trained this model.
params
Algorithm parameters that were used to train this model.
sc
An Apache Spark context.

Concrete Value Members

final def !=(arg0: AnyRef): Boolean

Definition Classes
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final def !=(arg0: Any): Boolean

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final def ##(): Int

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final def ==(arg0: AnyRef): Boolean

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final def ==(arg0: Any): Boolean

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final def asInstanceOf[T0]: T0

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def clone(): AnyRef

Attributes
protected[java.lang]
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@throws( ... )
final def eq(arg0: AnyRef): Boolean

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def equals(arg0: Any): Boolean

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def finalize(): Unit

Attributes
protected[java.lang]
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@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

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def hashCode(): Int

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final def isInstanceOf[T0]: Boolean

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final def ne(arg0: AnyRef): Boolean

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final def notify(): Unit

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final def notifyAll(): Unit

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final def synchronized[T0](arg0: ⇒ T0): T0

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def toString(): String

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final def wait(): Unit

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@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

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@throws( ... )
final def wait(arg0: Long): Unit

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trait PersistentModel[AP <: Params] extends AnyRef

Abstract Value Members

abstract def save(id: String, params: AP, sc: SparkContext): Boolean

Concrete Value Members

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from AnyRef

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