workflow

Type Members

1. case class BatchPredictConfig(inputFilePath: String = "batchpredict-input.json", outputFilePath: String = "batchpredict-output.json", queryPartitions: Option[Int] = None, engineInstanceId: String = "", engineId: Option[String] = None, engineVersion: Option[String] = None, engineVariant: String = "", env: Option[String] = None, verbose: Boolean = false, debug: Boolean = false, jsonExtractor: JsonExtractorOption.JsonExtractorOption = JsonExtractorOption.Both) extends Product with Serializable

   

2. case class BindServer() extends Product with Serializable

   

3. trait EngineServerPlugin extends AnyRef

   

4. class EngineServerPluginContext extends AnyRef

   

5. trait FakeRun extends EngineFactory with Evaluation with EngineParamsGenerator

   

   FakeRun allows user to implement custom function under the exact environment as other PredictionIO workflow.

   FakeRun allows user to implement custom function under the exact environment as other PredictionIO workflow.

   Useful for developing new features. Only need to extend this trait and implement a function: (SparkContext => Unit). For example, the code below can be run with pio eval HelloWorld.

   object HelloWorld extends FakeRun {
     // func defines the function pio runs, must have signature (SparkContext => Unit).
     func = f
   
     def f(sc: SparkContext): Unit {
       val logger = Logger[this.type]
       logger.info("HelloWorld")
     }
   }

   Annotations

   @Experimental()

6. class KryoInstantiator extends ScalaKryoInstantiator

   

7. class MasterActor extends Actor with KeyAuthentication with SSLConfiguration

   

8. case class NameParams(name: String, params: Option[JValue]) extends Product with Serializable

   

9. class NameParamsSerializer extends CustomSerializer[NameParams]

   

10. case class PersistentModelManifest(className: String) extends Product with Serializable

    

11. class PluginsActor extends Actor

    

12. class PredictionServer[Q, P] extends KeyAuthentication

    

13. case class ReloadServer() extends Product with Serializable

    

14. case class ServerConfig(batch: String = "", engineInstanceId: String = "", engineId: Option[String] = None, engineVersion: Option[String] = None, engineVariant: String = "", env: Option[String] = None, ip: String = "0.0.0.0", port: Int = 8000, feedback: Boolean = false, eventServerIp: String = "0.0.0.0", eventServerPort: Int = 7070, accessKey: Option[String] = None, logUrl: Option[String] = None, logPrefix: Option[String] = None, logFile: Option[String] = None, verbose: Boolean = false, debug: Boolean = false, jsonExtractor: JsonExtractorOption.JsonExtractorOption = JsonExtractorOption.Both) extends Product with Serializable

    

15. case class StartServer() extends Product with Serializable

    

16. case class StopAfterPrepareInterruption() extends WorkflowInterruption with Product with Serializable

    

17. case class StopAfterReadInterruption() extends WorkflowInterruption with Product with Serializable

    

18. case class StopServer() extends Product with Serializable

    

19. class WorkflowInterruption extends Exception

    

20. case class WorkflowParams(batch: String = "", verbose: Int = 2, saveModel: Boolean = true, sparkEnv: Map[String, String] = ..., skipSanityCheck: Boolean = false, stopAfterRead: Boolean = false, stopAfterPrepare: Boolean = false) extends Product with Serializable

    

    Workflow parameters.

    Workflow parameters.

    batch

    Batch label of the run.

    verbose

    Verbosity level.

    saveModel

    Controls whether trained models are persisted.

    sparkEnv

    Spark properties that will be set in SparkConf.setAll().

    skipSanityCheck

    Skips all data sanity check.

    stopAfterRead

    Stops workflow after reading from data source.

    stopAfterPrepare

    Stops workflow after data preparation.