RowTransformer

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. def apply(schemas: Seq[RowTransformSchema], rowSize: Int = 0): RowTransformer

   

5. final def asInstanceOf[T0]: T0

   

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6. def atomic(indices: Seq[Int], rowSize: Int): RowTransformer

   

   A RowTransformer which transform each selected columns to a size(1) Tensor.

   A RowTransformer which transform each selected columns to a size(1) Tensor. The keys of output Table are indices of selected columns.

   indices

   indices of selected columns

   rowSize

   size of Row transformed by this transformer

7. def atomic(fieldNames: Seq[String]): RowTransformer

   

   A RowTransformer which transform each selected columns to a size(1) Tensor.

   A RowTransformer which transform each selected columns to a size(1) Tensor. The keys of output Table are fieldNames of selected columns.

   fieldNames

   field names of selected columns

8. def atomicWithNumeric[T](atomicFields: Seq[String], numericFields: Map[String, Seq[String]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): RowTransformer

   

   A RowTransformer which contains both atomic schemas and numeric schemas.

   A RowTransformer which contains both atomic schemas and numeric schemas.

   atomicFields

   field names of selected columns

   numericFields

   Map<schemaKey, fieldNames of selected columns> of numeric fields

9. def clone(): AnyRef

   

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

    

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11. def equals(arg0: Any): Boolean

    

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12. def finalize(): Unit

    

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

    

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14. def hashCode(): Int

    

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15. final def isInstanceOf[T0]: Boolean

    

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

    

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17. final def notify(): Unit

    

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18. final def notifyAll(): Unit

    

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19. def numeric[T](numericFields: Map[String, Seq[String]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): RowTransformer

    

    A RowTransformer which concat values of selected columns to one Tensor.

    A RowTransformer which concat values of selected columns to one Tensor. It means you will get a Table with keys of numericFields. Values of Table are Tensors concatenated by selected columns of the keys.

    numericFields

    Map<schemaKey, fieldNames of selected columns> of numeric fields

20. def numeric[T](schemaKey: String = "all")(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): RowTransformer

    

    A RowTransformer which concat values of all columns to one Tensor.

    A RowTransformer which concat values of all columns to one Tensor. It means you will get a Table with single key-value pair after transformation. The unique key is schemaKey. The unique value is a size(length of Row) Tensor.

    schemaKey

    key of the schema, default value is "all"

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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