Object/Class

com.microsoft.ml.spark

CheckpointData

Related Docs: class CheckpointData | package spark

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object CheckpointData extends DefaultParamsReadable[CheckpointData] with Serializable

Cache the dataset to memory or memory and disk.

Linear Supertypes
Serializable, Serializable, DefaultParamsReadable[CheckpointData], MLReadable[CheckpointData], AnyRef, Any
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Inherited
  1. CheckpointData
  2. Serializable
  3. Serializable
  4. DefaultParamsReadable
  5. MLReadable
  6. AnyRef
  7. Any
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Visibility
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Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  5. def cache(ds: Dataset[_], disk: Boolean, serialized: Boolean): DataFrame

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    Cache the dataset

    Cache the dataset

    ds

    dataset to be cahced

    disk

    save to disk as well as memory when true

    serialized

    serialize data

  6. def clearCache(ds: Dataset[_], blocking: Boolean): DataFrame

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    Clear (Unpersist) the cached dataset

    Clear (Unpersist) the cached dataset

    ds

    The dataset to be unpersisted

    blocking

    True if this operation should be a blocking operation

  7. def clone(): AnyRef

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

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    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  12. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  13. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  14. def load(path: String): CheckpointData

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    Definition Classes
    MLReadable
    Annotations
    @Since( "1.6.0" )
  15. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  16. final def notify(): Unit

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    Definition Classes
    AnyRef
  17. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  18. def persistToHive(ds: Dataset[_], dbName: String, tableName: String): DataFrame

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    Cache to Hive

    Cache to Hive

    ds

    dataset to be cached

    dbName

    Hive db name

    tableName

    Hive table name

  19. def read: MLReader[CheckpointData]

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    Definition Classes
    DefaultParamsReadable → MLReadable
  20. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  21. def toString(): String

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    Definition Classes
    AnyRef → Any
  22. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from DefaultParamsReadable[CheckpointData]

Inherited from MLReadable[CheckpointData]

Inherited from AnyRef

Inherited from Any

Members