class DataConversion extends Transformer with Wrappable with DefaultParamsWritable with SynapseMLLogging
Converts the specified list of columns to the specified type. Returns a new DataFrame with the converted columns
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Inherited
- DataConversion
- SynapseMLLogging
- DefaultParamsWritable
- MLWritable
- Wrappable
- RWrappable
- PythonWrappable
- BaseWrappable
- Transformer
- PipelineStage
- Logging
- Params
- Serializable
- Serializable
- Identifiable
- AnyRef
- Any
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Instance Constructors
Value Members
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final
def
clear(param: Param[_]): DataConversion.this.type
- Definition Classes
- Params
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val
cols: StringArrayParam
Comma separated list of columns whose type will be converted
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val
convertTo: Param[String]
The result type
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def
copy(extra: ParamMap): DataConversion
Copy the class, with extra com.microsoft.azure.synapse.ml.core.serialize.params
Copy the class, with extra com.microsoft.azure.synapse.ml.core.serialize.params
- extra
Extra parameters
- Definition Classes
- DataConversion → Transformer → PipelineStage → Params
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val
dateTimeFormat: Param[String]
Format for DateTime when making DateTime:String conversions.
Format for DateTime when making DateTime:String conversions. The default is yyyy-MM-dd HH:mm:ss
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def
explainParam(param: Param[_]): String
- Definition Classes
- Params
-
def
explainParams(): String
- Definition Classes
- Params
-
final
def
extractParamMap(): ParamMap
- Definition Classes
- Params
-
final
def
extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
-
final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
- final def getCols: Array[String]
- final def getConvertTo: String
- final def getDateTimeFormat: String
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final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
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final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
-
def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
-
def
getParamInfo(p: Param[_]): ParamInfo[_]
- Definition Classes
- BaseWrappable
-
final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
-
def
hasParam(paramName: String): Boolean
- Definition Classes
- Params
-
final
def
isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
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final
def
isSet(param: Param[_]): Boolean
- Definition Classes
- Params
-
def
logClass(featureName: String): Unit
- Definition Classes
- SynapseMLLogging
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def
logFit[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
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def
logTransform[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
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def
logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
- Definition Classes
- SynapseMLLogging
-
def
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
- PythonWrappable
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def
makeRFile(conf: CodegenConfig): Unit
- Definition Classes
- RWrappable
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lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
def
pyAdditionalMethods: String
- Definition Classes
- PythonWrappable
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def
pyInitFunc(): String
- Definition Classes
- PythonWrappable
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def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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final
def
set[T](param: Param[T], value: T): DataConversion.this.type
- Definition Classes
- Params
- def setCols(value: Array[String]): DataConversion.this.type
- def setConvertTo(value: String): DataConversion.this.type
- def setDateTimeFormat(value: String): DataConversion.this.type
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def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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def
transform(dataset: Dataset[_]): DataFrame
Apply the
DataConversion
transform to the datasetApply the
DataConversion
transform to the dataset- dataset
The dataset to be transformed
- returns
The transformed dataset
- Definition Classes
- DataConversion → Transformer
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def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
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def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
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def
transformSchema(schema: StructType): StructType
Transform the schema
Transform the schema
- schema
The input schema
- returns
modified schema
- Definition Classes
- DataConversion → PipelineStage
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val
uid: String
- Definition Classes
- DataConversion → SynapseMLLogging → Identifiable
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def
write: MLWriter
- Definition Classes
- DefaultParamsWritable → MLWritable