MlModelsDB

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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6. def createModelsBroadcast(mlModelsOnlyInfo: List[MlModelOnlyInfo])(implicit sc: SparkContext): MlModelsBroadcastDB

   

   It build a MlModelsBroadcastDB where all the model with info are broadcasted The param can be incomplete so it read the complete model with info from MongoDB

7. def delete(name: String, version: String, timestamp: Long): Unit

   

8. final def eq(arg0: AnyRef): Boolean

   

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9. def equals(arg0: Any): Boolean

   

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10. def finalize(): Unit

    

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11. final def getClass(): Class[_]

    

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12. def hashCode(): Int

    

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13. final def isInstanceOf[T0]: Boolean

    

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14. final def ne(arg0: AnyRef): Boolean

    

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15. final def notify(): Unit

    

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16. final def notifyAll(): Unit

    

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17. def read(name: String, version: String, timestampOpt: Option[Long]): TransformerWithInfo

    

    This method can be use to retrieve a complete model with own info, if there isn't a timestamp it will take the most recent

    This method can be use to retrieve a complete model with own info, if there isn't a timestamp it will take the most recent

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18. def read(mlModelOnlyInfo: MlModelOnlyInfo): TransformerWithInfo

    

    Get the TransformerWithInfo of only metadata

    Get the TransformerWithInfo of only metadata

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19. def read(name: String, version: String): TransformerWithInfo

    

    Find the most recent TransformerWithInfo

    Find the most recent TransformerWithInfo

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20. def readOnlyInfo(name: String, version: String, timestampOpt: Option[Long]): Option[MlModelOnlyInfo]

    

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

    

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22. def toString(): String

    

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23. final def wait(): Unit

    

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

    

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25. final def wait(arg0: Long): Unit

    

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26. def write(mlModels: List[TransformerWithInfo]): List[TransformerWithInfo]

    

27. def write(mlModel: TransformerWithInfo): TransformerWithInfo

    

    It save the info on the own collection and the transformer model in gridFS

    It save the info on the own collection and the transformer model in gridFS

    returns

    an error if something was wrong and the saved model with all the ids initialized