Packages

class DocumentTokenSplitter extends AnnotatorModel[DocumentTokenSplitter] with HasSimpleAnnotate[DocumentTokenSplitter]

Annotator that splits large documents into smaller documents based on the number of tokens in the text.

Currently, DocumentTokenSplitter splits the text by whitespaces to create the tokens. The number of these tokens will then be used as a measure of the text length. In the future, other tokenization techniques will be supported.

For example, given 3 tokens and overlap 1:

He was, I take it, the most perfect reasoning and observing machine that the world has seen.

["He was, I", "I take it,", "it, the most", "most perfect reasoning", "reasoning and observing", "observing machine that", "that the world", "world has seen."]

Additionally, you can set

For extended examples of usage, see the DocumentTokenSplitterTest.

Example

import com.johnsnowlabs.nlp.annotator._
import com.johnsnowlabs.nlp.DocumentAssembler
import org.apache.spark.ml.Pipeline

val textDF =
  spark.read
    .option("wholetext", "true")
    .text("src/test/resources/spell/sherlockholmes.txt")
    .toDF("text")

val documentAssembler = new DocumentAssembler().setInputCol("text")
val textSplitter = new DocumentTokenSplitter()
  .setInputCols("document")
  .setOutputCol("splits")
  .setNumTokens(512)
  .setTokenOverlap(10)
  .setExplodeSplits(true)

val pipeline = new Pipeline().setStages(Array(documentAssembler, textSplitter))
val result = pipeline.fit(textDF).transform(textDF)

result
  .selectExpr(
    "splits.result as result",
    "splits[0].begin as begin",
    "splits[0].end as end",
    "splits[0].end - splits[0].begin as length",
    "splits[0].metadata.numTokens as tokens")
  .show(8, truncate = 80)
+--------------------------------------------------------------------------------+-----+-----+------+------+
|                                                                          result|begin|  end|length|tokens|
+--------------------------------------------------------------------------------+-----+-----+------+------+
|[ Project Gutenberg's The Adventures of Sherlock Holmes, by Arthur Conan Doyl...|    0| 3018|  3018|   512|
|[study of crime, and occupied his\nimmense faculties and extraordinary powers...| 2950| 5707|  2757|   512|
|[but as I have changed my clothes I can't imagine how you\ndeduce it. As to M...| 5659| 8483|  2824|   512|
|[quarters received. Be in your chamber then at that hour, and do\nnot take it...| 8427|11241|  2814|   512|
|[a pity\nto miss it."\n\n"But your client--"\n\n"Never mind him. I may want y...|11188|13970|  2782|   512|
|[person who employs me wishes his agent to be unknown to\nyou, and I may conf...|13918|16898|  2980|   512|
|[letters back."\n\n"Precisely so. But how--"\n\n"Was there a secret marriage?...|16836|19744|  2908|   512|
|[seven hundred in\nnotes," he said.\n\nHolmes scribbled a receipt upon a shee...|19683|22551|  2868|   512|
+--------------------------------------------------------------------------------+-----+-----+------+------+
Linear Supertypes
HasSimpleAnnotate[DocumentTokenSplitter], AnnotatorModel[DocumentTokenSplitter], CanBeLazy, RawAnnotator[DocumentTokenSplitter], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[DocumentTokenSplitter], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. DocumentTokenSplitter
  2. HasSimpleAnnotate
  3. AnnotatorModel
  4. CanBeLazy
  5. RawAnnotator
  6. HasOutputAnnotationCol
  7. HasInputAnnotationCols
  8. HasOutputAnnotatorType
  9. ParamsAndFeaturesWritable
  10. HasFeatures
  11. DefaultParamsWritable
  12. MLWritable
  13. Model
  14. Transformer
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DocumentTokenSplitter()
  2. new DocumentTokenSplitter(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. 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
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    DocumentTokenSplitter → AnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    Takes a Document and produces document splits based on a Tokenizers

    Takes a Document and produces document splits based on a Tokenizers

    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
    DocumentTokenSplitter → HasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  14. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  15. final def clear(param: Param[_]): DocumentTokenSplitter.this.type
    Definition Classes
    Params
  16. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  17. def copy(extra: ParamMap): DocumentTokenSplitter

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  18. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  19. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. 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
  21. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  23. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  24. def explainParams(): String
    Definition Classes
    Params
  25. val explodeSplits: BooleanParam

    Whether to explode split chunks to separate rows

  26. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  27. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  28. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  29. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  30. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  31. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  32. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  33. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  34. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  35. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  36. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  37. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  38. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  39. def getExplodeSplits: Boolean

  40. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  41. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  42. def getNumTokens: Int

  43. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  44. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  45. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  46. def getTokenOverlap: Int

  47. def getTrimWhitespace: Boolean

  48. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  49. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  50. def hasParent: Boolean
    Definition Classes
    Model
  51. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  52. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  53. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. val inputAnnotatorTypes: Array[AnnotatorType]

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

    Definition Classes
    DocumentTokenSplitter → HasInputAnnotationCols
  55. 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
  56. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  57. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  58. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  59. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  60. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  61. def lengthFromTokens(text: String): Int
  62. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  63. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  70. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  75. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  76. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  77. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  78. val numTokens: IntParam

    Limit of the number of tokens in a text

  79. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  80. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  81. val outputAnnotatorType: AnnotatorType
    Definition Classes
    DocumentTokenSplitter → HasOutputAnnotatorType
  82. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  83. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  84. var parent: Estimator[DocumentTokenSplitter]
    Definition Classes
    Model
  85. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  86. def set[T](feature: StructFeature[T], value: T): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  87. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  88. def set[T](feature: SetFeature[T], value: Set[T]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  89. def set[T](feature: ArrayFeature[T], value: Array[T]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  90. final def set(paramPair: ParamPair[_]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    Params
  91. final def set(param: String, value: Any): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    Params
  92. final def set[T](param: Param[T], value: T): DocumentTokenSplitter.this.type
    Definition Classes
    Params
  93. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  94. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  95. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  96. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  97. final def setDefault(paramPairs: ParamPair[_]*): DocumentTokenSplitter.this.type
    Attributes
    protected
    Definition Classes
    Params
  98. final def setDefault[T](param: Param[T], value: T): DocumentTokenSplitter.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  99. def setExplodeSplits(value: Boolean): DocumentTokenSplitter.this.type

  100. final def setInputCols(value: String*): DocumentTokenSplitter.this.type
    Definition Classes
    HasInputAnnotationCols
  101. def setInputCols(value: Array[String]): DocumentTokenSplitter.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  102. def setLazyAnnotator(value: Boolean): DocumentTokenSplitter.this.type
    Definition Classes
    CanBeLazy
  103. def setNumTokens(value: Int): DocumentTokenSplitter.this.type

  104. final def setOutputCol(value: String): DocumentTokenSplitter.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  105. def setParent(parent: Estimator[DocumentTokenSplitter]): DocumentTokenSplitter
    Definition Classes
    Model
  106. def setTokenOverlap(value: Int): DocumentTokenSplitter.this.type

  107. def setTrimWhitespace(value: Boolean): DocumentTokenSplitter.this.type

  108. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  109. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  110. val tokenOverlap: IntParam

    Length of the token overlap between text chunks (Default: 0)

  111. 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
  112. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  113. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  114. 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
  115. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  116. val trimWhitespace: BooleanParam

    Whether to trim whitespaces of extracted chunks (Default: true)

  117. val uid: String
    Definition Classes
    DocumentTokenSplitter → Identifiable
  118. 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
  119. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  120. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  121. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  122. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  123. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from HasSimpleAnnotate[DocumentTokenSplitter]

Inherited from AnnotatorModel[DocumentTokenSplitter]

Inherited from CanBeLazy

Inherited from RawAnnotator[DocumentTokenSplitter]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[DocumentTokenSplitter]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

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.

Members

Parameter setters

Parameter getters