MlModelsDB

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

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

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

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

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

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

def read(mlModelOnlyInfo: MlModelOnlyInfo): TransformerWithInfo

Get the TransformerWithInfo of only metadata

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

Find the most recent TransformerWithInfo

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

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

def toString(): String

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

final def wait(arg0: Long): Unit

final def wait(): Unit

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

def write(mlModel: TransformerWithInfo): TransformerWithInfo

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

def finalize(): Unit