class ColToTensor extends RowTransformSchema
A schema which specialize on transforming single column to size(1) Tensor.
Types of selected columns will be identified according to their DataType.
And type conversions will be done automatically from DataType to TensorDataType.
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new
ColToTensor(schemaKey: String, index: Int, fieldName: String = "")
- schemaKey
key of the schema
- index
index of selected column, overridden by non empty
fieldName- fieldName
field name of selected column, default is empty
Value Members
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eq(arg0: AnyRef): Boolean
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equals(arg0: Any): Boolean
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val
fieldNames: Seq[String]
This property will override
indiceswhen it is not empty.FieldNamesof Selected ColumnsThis property will override
indiceswhen it is not empty.- Definition Classes
- ColToTensor → RowTransformSchema
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def
finalize(): Unit
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val
indices: Seq[Int]
It will work on only when
fieldNamesis empty, otherwiseRowTransformerwill select columns accord tofieldNames.Indicesof Selected ColumnsIt will work on only when
fieldNamesis empty, otherwiseRowTransformerwill select columns accord tofieldNames. If bothindicesandfieldNamesare empty,RowTransformerwill select all columns by default.- Definition Classes
- ColToTensor → RowTransformSchema
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val
schemaKey: String
Key of the schema, which will be the key of
Tensorin resultTable.Key of the schema, which will be the key of
Tensorin resultTable. So, it should beuniquein singleRowTransformer.- Definition Classes
- ColToTensor → RowTransformSchema
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
transform(input: Seq[Any], fields: Seq[StructField]): Tensor[NumericWildcard]
Transforming Logic of the Schema
Transforming Logic of the Schema
- fields
StructFields of selected columns
- returns
a result
Tensor
- Definition Classes
- ColToTensor → RowTransformSchema
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