class DocumentAssembler extends Transformer with DefaultParamsWritable with HasOutputAnnotatorType with HasOutputAnnotationCol
Prepares data into a format that is processable by Spark NLP. This is the entry point for
every Spark NLP pipeline. The DocumentAssembler reads String columns. Additionally,
setCleanupMode can be used to pre-process the text (Default: disabled). For possible
options please refer to the parameters section.
For more extended examples on document pre-processing see the Examples.
Example
import spark.implicits._ import com.johnsnowlabs.nlp.DocumentAssembler val data = Seq("Spark NLP is an open-source text processing library.").toDF("text") val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("document") val result = documentAssembler.transform(data) result.select("document").show(false) +----------------------------------------------------------------------------------------------+ |document | +----------------------------------------------------------------------------------------------+ |[[document, 0, 51, Spark NLP is an open-source text processing library., [sentence -> 0], []]]| +----------------------------------------------------------------------------------------------+ result.select("document").printSchema root |-- document: array (nullable = true) | |-- element: struct (containsNull = true) | | |-- annotatorType: string (nullable = true) | | |-- begin: integer (nullable = false) | | |-- end: integer (nullable = false) | | |-- result: string (nullable = true) | | |-- metadata: map (nullable = true) | | | |-- key: string | | | |-- value: string (valueContainsNull = true) | | |-- embeddings: array (nullable = true) | | | |-- element: float (containsNull = false)
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- type AnnotatorType = String
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- HasOutputAnnotatorType
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- val EMPTY_STR: String
- final def asInstanceOf[T0]: T0
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- val cleanupMode: Param[String]
cleanupMode can take the following values:
cleanupMode can take the following values:
disabled: keep original. Useful if need to head back to source laterinplace: newlines and tabs into whitespaces, not stringified ones, don't triminplace_full: newlines and tabs into whitespaces, including stringified, don't trimshrink: all whitespaces, newlines and tabs to a single whitespace, but not stringified, do trimshrink_full: all whitespaces, newlines and tabs to a single whitespace, stringified ones too, trim alleach: newlines and tabs to one whitespace eacheach_full: newlines and tabs, stringified ones too, to one whitespace eachdelete_full: remove stringified newlines and tabs (replace with nothing)
- final def clear(param: Param[_]): DocumentAssembler.this.type
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- def clone(): AnyRef
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- protected[lang]
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- @throws(classOf[java.lang.CloneNotSupportedException]) @HotSpotIntrinsicCandidate() @native()
- def copy(extra: ParamMap): Transformer
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- DocumentAssembler → Transformer → PipelineStage → Params
- def copyValues[T <: Params](to: T, extra: ParamMap): T
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- final def defaultCopy[T <: Params](extra: ParamMap): T
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- def explainParam(param: Param[_]): String
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- def explainParams(): String
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- final def extractParamMap(): ParamMap
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- final def extractParamMap(extra: ParamMap): ParamMap
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- final def get[T](param: Param[T]): Option[T]
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- final def getClass(): Class[_ <: AnyRef]
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- @HotSpotIntrinsicCandidate() @native()
- def getCleanupMode: String
cleanupMode to pre-process text
- final def getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
- def getIdCol: String
Id column for row reference
- def getInputCol: String
Input text column for processing
- def getMetadataCol: String
Metadata for document column
- final def getOrDefault[T](param: Param[T]): T
- Definition Classes
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- final def getOutputCol: String
Gets annotation column name going to generate
Gets annotation column name going to generate
- Definition Classes
- HasOutputAnnotationCol
- def getParam(paramName: String): Param[Any]
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- final def hasDefault[T](param: Param[T]): Boolean
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- def hasParam(paramName: String): Boolean
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- def hashCode(): Int
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- val idCol: Param[String]
Id column for row reference
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
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- val inputCol: Param[String]
Input text column for processing
- final def isDefined(param: Param[_]): Boolean
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- final def isSet(param: Param[_]): Boolean
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- def log: Logger
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- def logName: String
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- def logWarning(msg: => String, throwable: Throwable): Unit
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- def logWarning(msg: => String): Unit
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- val metadataCol: Param[String]
Metadata for document column
- final def ne(arg0: AnyRef): Boolean
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- @HotSpotIntrinsicCandidate() @native()
- final def notifyAll(): Unit
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- @HotSpotIntrinsicCandidate() @native()
- val outputAnnotatorType: AnnotatorType
Output Annotator Type: DOCUMENT
Output Annotator Type: DOCUMENT
- Definition Classes
- DocumentAssembler → HasOutputAnnotatorType
- final val outputCol: Param[String]
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- HasOutputAnnotationCol
- lazy val params: Array[Param[_]]
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- Params
- def save(path: String): Unit
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- MLWritable
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- @throws("If the input path already exists but overwrite is not enabled.") @Since("1.6.0")
- final def set(paramPair: ParamPair[_]): DocumentAssembler.this.type
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- final def set(param: String, value: Any): DocumentAssembler.this.type
- Attributes
- protected
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- Params
- final def set[T](param: Param[T], value: T): DocumentAssembler.this.type
- Definition Classes
- Params
- def setCleanupMode(v: String): DocumentAssembler.this.type
cleanupMode to pre-process text
- final def setDefault(paramPairs: ParamPair[_]*): DocumentAssembler.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def setDefault[T](param: Param[T], value: T): DocumentAssembler.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
- def setIdCol(value: String): DocumentAssembler.this.type
Id column for row reference
- def setInputCol(value: String): DocumentAssembler.this.type
Input text column for processing
- def setMetadataCol(value: String): DocumentAssembler.this.type
Metadata for document column
- final def setOutputCol(value: String): DocumentAssembler.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming
- Definition Classes
- HasOutputAnnotationCol
- final def synchronized[T0](arg0: => T0): T0
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- AnyRef
- def toString(): String
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- Identifiable → AnyRef → Any
- def transform(dataset: Dataset[_]): DataFrame
- Definition Classes
- DocumentAssembler → Transformer
- def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
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- Transformer
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- @Since("2.0.0")
- def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
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- @varargs() @Since("2.0.0")
- final def transformSchema(schema: StructType): StructType
requirement for pipeline transformation validation.
requirement for pipeline transformation validation. It is called on fit()
- Definition Classes
- DocumentAssembler → PipelineStage
- def transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
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- PipelineStage
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- @DeveloperApi()
- val uid: String
- Definition Classes
- DocumentAssembler → Identifiable
- final def wait(arg0: Long, arg1: Int): Unit
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
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- final def wait(): Unit
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- def write: MLWriter
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Deprecated Value Members
- def finalize(): Unit
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- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)
Inherited from HasOutputAnnotationCol
Inherited from HasOutputAnnotatorType
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from Transformer
Inherited from PipelineStage
Inherited from Logging
Inherited from Params
Inherited from Serializable
Inherited from Identifiable
Inherited from AnyRef
Inherited from Any
Parameters
A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.
Annotator types
Required input and expected output annotator types