ModelBackend

abstract def runModelInference(runModelInferenceRequest: RunModelInferenceRequest): Future[RunModelInferenceResponse]

Run online model inference which returns the model output directly.

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

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 runModelInferenceBatchJob(sparkSession: SparkSession, join: Join, startPartition: String, endPartition: String, modelTransform: Option[ModelTransform] = None, jobContextJson: Option[String] = None): Option[DataFrame]

Run batch model inference job which will be executed asynchronously in batch.

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 finalize(): Unit