class DocumentNormalizer extends AnnotatorModel[DocumentNormalizer] with HasSimpleAnnotate[DocumentNormalizer]
Annotator which normalizes raw text from tagged text, e.g. scraped web pages or xml documents, from document type columns into Sentence. Removes all dirty characters from text following one or more input regex patterns. Can apply not wanted character removal with a specific policy. Can apply lower case normalization.
For extended examples of usage, see the Examples.
Example
import spark.implicits._ import com.johnsnowlabs.nlp.DocumentAssembler import com.johnsnowlabs.nlp.annotator.DocumentNormalizer import org.apache.spark.ml.Pipeline val documentAssembler = new DocumentAssembler() .setInputCol("text") .setOutputCol("document") val cleanUpPatterns = Array("<[^>]*>") val documentNormalizer = new DocumentNormalizer() .setInputCols("document") .setOutputCol("normalizedDocument") .setAction("clean") .setPatterns(cleanUpPatterns) .setReplacement(" ") .setPolicy("pretty_all") .setLowercase(true) val pipeline = new Pipeline().setStages(Array( documentAssembler, documentNormalizer )) val text = """ THE WORLD'S LARGEST WEB DEVELOPER SITE = THE WORLD'S LARGEST WEB DEVELOPER SITE = Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.. """ val data = Seq(text).toDF("text") val pipelineModel = pipeline.fit(data) val result = pipelineModel.transform(data) result.selectExpr("normalizedDocument.result").show(truncate=false) +--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ |result | +--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ |[ the world's largest web developer site the world's largest web developer site lorem ipsum is simply dummy text of the printing and typesetting industry. lorem ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. it has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. it was popularised in the 1960s with the release of letraset sheets containing lorem ipsum passages, and more recently with desktop publishing software like aldus pagemaker including versions of lorem ipsum..]| +--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
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- DocumentNormalizer
- HasSimpleAnnotate
- AnnotatorModel
- CanBeLazy
- RawAnnotator
- HasOutputAnnotationCol
- HasInputAnnotationCols
- HasOutputAnnotatorType
- ParamsAndFeaturesWritable
- HasFeatures
- DefaultParamsWritable
- MLWritable
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- Transformer
- PipelineStage
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Type Members
- type AnnotationContent = Seq[Row]
internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI
internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI
- Attributes
- protected
- Definition Classes
- AnnotatorModel
- type AnnotatorType = String
- Definition Classes
- HasOutputAnnotatorType
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def $[T](param: Param[T]): T
- Attributes
- protected
- Definition Classes
- Params
- def $$[T](feature: StructFeature[T]): T
- Attributes
- protected
- Definition Classes
- HasFeatures
- def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
- Attributes
- protected
- Definition Classes
- HasFeatures
- def $$[T](feature: SetFeature[T]): Set[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
- def $$[T](feature: ArrayFeature[T]): Array[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
- Attributes
- protected
- Definition Classes
- AnnotatorModel
- val action: Param[String]
Action to perform applying regex patterns on text
- def afterAnnotate(dataset: DataFrame): DataFrame
- Attributes
- protected
- Definition Classes
- AnnotatorModel
- def annotate(annotations: Seq[Annotation]): Seq[Annotation]
takes a document and annotations and produces new annotations of this annotator's annotation type
takes a document and annotations and produces new annotations of this annotator's annotation type
- annotations
Annotations that correspond to inputAnnotationCols generated by previous annotators if any
- returns
any number of annotations processed for every input annotation. Not necessary one to one relationship
- Definition Classes
- DocumentNormalizer → HasSimpleAnnotate
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- val autoMode: Param[String]
- def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
- Attributes
- protected
- Definition Classes
- AnnotatorModel
- final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
- final def clear(param: Param[_]): DocumentNormalizer.this.type
- Definition Classes
- Params
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @HotSpotIntrinsicCandidate() @native()
- def copy(extra: ParamMap): DocumentNormalizer
requirement for annotators copies
requirement for annotators copies
- Definition Classes
- RawAnnotator → Model → Transformer → PipelineStage → Params
- def copyValues[T <: Params](to: T, extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
- final def defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
- def dfAnnotate: UserDefinedFunction
Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column
Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column
- returns
udf function to be applied to inputCols using this annotator's annotate function as part of ML transformation
- Definition Classes
- HasSimpleAnnotate
- val encoding: Param[String]
File encoding to apply on normalized documents (Default:
"disable") - final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def explainParam(param: Param[_]): String
- Definition Classes
- Params
- def explainParams(): String
- Definition Classes
- Params
- def extraValidate(structType: StructType): Boolean
- Attributes
- protected
- Definition Classes
- RawAnnotator
- def extraValidateMsg: String
Override for additional custom schema checks
Override for additional custom schema checks
- Attributes
- protected
- Definition Classes
- RawAnnotator
- final def extractParamMap(): ParamMap
- Definition Classes
- Params
- final def extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
- val features: ArrayBuffer[Feature[_, _, _]]
- Definition Classes
- HasFeatures
- def get[T](feature: StructFeature[T]): Option[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
- def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
- Attributes
- protected
- Definition Classes
- HasFeatures
- def get[T](feature: SetFeature[T]): Option[Set[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
- def get[T](feature: ArrayFeature[T]): Option[Array[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
- def getAction: String
Action to perform on text.
Action to perform on text. (Default
"clean"). - final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @HotSpotIntrinsicCandidate() @native()
- final def getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
- def getEncoding: String
Encoding to apply to normalized documents (Default:
"disable") - def getInputCols: Array[String]
- returns
input annotations columns currently used
- Definition Classes
- HasInputAnnotationCols
- def getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
- def getLowercase: Boolean
Lowercase tokens (Default:
false) - final def getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
- 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]
- Definition Classes
- Params
- def getPatterns: Array[String]
Regular expressions list for normalization.
- def getPolicy: String
Policy to remove patterns from text (Default:
"pretty_all") - def getReplacement: String
Replacement string to apply when regexes match (Default:
" ") - final def hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
- def hasParam(paramName: String): Boolean
- Definition Classes
- Params
- def hasParent: Boolean
- Definition Classes
- Model
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @HotSpotIntrinsicCandidate() @native()
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
- protected
- Definition Classes
- Logging
- val inputAnnotatorTypes: Array[AnnotatorType]
Input annotator type : DOCUMENT
Input annotator type : DOCUMENT
- Definition Classes
- DocumentNormalizer → HasInputAnnotationCols
- final val inputCols: StringArrayParam
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
- final def isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def isSet(param: Param[_]): Boolean
- Definition Classes
- Params
- def isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- val lazyAnnotator: BooleanParam
- Definition Classes
- CanBeLazy
- def log: Logger
- Attributes
- protected
- Definition Classes
- Logging
- def logDebug(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logDebug(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logError(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logError(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logInfo(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logInfo(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logName: String
- Attributes
- protected
- Definition Classes
- Logging
- def logTrace(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logTrace(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logWarning(msg: => String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def logWarning(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- val lowercase: BooleanParam
Whether to convert strings to lowercase (Default:
false) - def msgHelper(schema: StructType): String
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @HotSpotIntrinsicCandidate() @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @HotSpotIntrinsicCandidate() @native()
- def onWrite(path: String, spark: SparkSession): Unit
- Attributes
- protected
- Definition Classes
- ParamsAndFeaturesWritable
- val optionalInputAnnotatorTypes: Array[String]
- Definition Classes
- HasInputAnnotationCols
- val outputAnnotatorType: AnnotatorType
Output annotator type : DOCUMENT
Output annotator type : DOCUMENT
- Definition Classes
- DocumentNormalizer → HasOutputAnnotatorType
- final val outputCol: Param[String]
- Attributes
- protected
- Definition Classes
- HasOutputAnnotationCol
- lazy val params: Array[Param[_]]
- Definition Classes
- Params
- var parent: Estimator[DocumentNormalizer]
- Definition Classes
- Model
- val patterns: StringArrayParam
Normalization regex patterns which match will be removed from document (Default:
Array("<[^>]*>")) - val policy: Param[String]
RemovalPolicy to remove patterns from text with a given policy (Default:
"pretty_all").RemovalPolicy to remove patterns from text with a given policy (Default:
"pretty_all"). Possible values are"all", "pretty_all", "first", "pretty_first" - val presetPattern: Param[String]
- val replacement: Param[String]
Replacement string to apply when regexes match (Default:
" ") - def save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @throws("If the input path already exists but overwrite is not enabled.") @Since("1.6.0")
- def set[T](feature: StructFeature[T], value: T): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[T](feature: SetFeature[T], value: Set[T]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[T](feature: ArrayFeature[T], value: Array[T]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def set(paramPair: ParamPair[_]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def set(param: String, value: Any): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def set[T](param: Param[T], value: T): DocumentNormalizer.this.type
- Definition Classes
- Params
- def setAction(value: String): DocumentNormalizer.this.type
Action to perform on text.
Action to perform on text. (Default
"clean"). - def setAutoMode(value: String): DocumentNormalizer.this.type
- def setDefault[T](feature: StructFeature[T], value: () => T): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[K, V](feature: MapFeature[K, V], value: () => Map[K, V]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[T](feature: SetFeature[T], value: () => Set[T]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[T](feature: ArrayFeature[T], value: () => Array[T]): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def setDefault(paramPairs: ParamPair[_]*): DocumentNormalizer.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def setDefault[T](param: Param[T], value: T): DocumentNormalizer.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
- def setEncoding(value: String): DocumentNormalizer.this.type
Encoding to apply.
Encoding to apply. Default is
"UTF-8". Valid encoding are values are: UTF_8, UTF_16, US_ASCII, ISO-8859-1, UTF-16BE, UTF-16LE - final def setInputCols(value: String*): DocumentNormalizer.this.type
- Definition Classes
- HasInputAnnotationCols
- def setInputCols(value: Array[String]): DocumentNormalizer.this.type
Overrides required annotators column if different than default
Overrides required annotators column if different than default
- Definition Classes
- HasInputAnnotationCols
- def setLazyAnnotator(value: Boolean): DocumentNormalizer.this.type
- Definition Classes
- CanBeLazy
- def setLowercase(value: Boolean): DocumentNormalizer.this.type
Lower case tokens default false
- final def setOutputCol(value: String): DocumentNormalizer.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming
- Definition Classes
- HasOutputAnnotationCol
- def setParent(parent: Estimator[DocumentNormalizer]): DocumentNormalizer
- Definition Classes
- Model
- def setPatterns(value: Array[String]): DocumentNormalizer.this.type
Regular expressions list for normalization (Default:
Array("<[^>]*>")) - def setPolicy(value: String): DocumentNormalizer.this.type
Removal policy to apply (Default:
"pretty_all").Removal policy to apply (Default:
"pretty_all"). Valid policy values are: "all", "pretty_all", "first", "pretty_first" - def setPresetPattern(value: String): DocumentNormalizer.this.type
- def setReplacement(value: String): DocumentNormalizer.this.type
Replacement string to apply when regexes match (Default:
" ") - final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
- final def transform(dataset: Dataset[_]): DataFrame
Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content
Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content
- dataset
Dataset[Row]
- Definition Classes
- AnnotatorModel → Transformer
- def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since("2.0.0")
- def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @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
- RawAnnotator → PipelineStage
- def transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
- val uid: String
- Definition Classes
- DocumentNormalizer → Identifiable
- def validate(schema: StructType): Boolean
takes a Dataset and checks to see if all the required annotation types are present.
takes a Dataset and checks to see if all the required annotation types are present.
- schema
to be validated
- returns
True if all the required types are present, else false
- Attributes
- protected
- Definition Classes
- RawAnnotator
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- def wrapColumnMetadata(col: Column): Column
- Attributes
- protected
- Definition Classes
- RawAnnotator
- def write: MLWriter
- Definition Classes
- ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)
Inherited from HasSimpleAnnotate[DocumentNormalizer]
Inherited from AnnotatorModel[DocumentNormalizer]
Inherited from CanBeLazy
Inherited from RawAnnotator[DocumentNormalizer]
Inherited from HasOutputAnnotationCol
Inherited from HasInputAnnotationCols
Inherited from HasOutputAnnotatorType
Inherited from ParamsAndFeaturesWritable
Inherited from HasFeatures
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from Model[DocumentNormalizer]
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