com.johnsnowlabs.nlp.annotators
DocumentCharacterTextSplitter
Companion object DocumentCharacterTextSplitter
class DocumentCharacterTextSplitter extends AnnotatorModel[DocumentCharacterTextSplitter] with HasSimpleAnnotate[DocumentCharacterTextSplitter]
Annotator which splits large documents into chunks of roughly given size.
DocumentCharacterTextSplitter takes a list of separators. It takes the separators in order and splits subtexts if they are over the chunk length, considering optional overlap of the chunks.
For example, given chunk size 20 and overlap 5:
He was, I take it, the most perfect reasoning and observing machine that the world has seen. ["He was, I take it,", "it, the most", "most perfect", "reasoning and", "and observing", "machine that the", "the world has seen."]
Additionally, you can set
- custom patterns with setSplitPatterns
- whether patterns should be interpreted as regex with setPatternsAreRegex
- whether to keep the separators with setKeepSeparators
- whether to trim whitespaces with setTrimWhitespace
- whether to explode the splits to individual rows with setExplodeSplits
For extended examples of usage, see the DocumentCharacterTextSplitterTest.
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 DocumentCharacterTextSplitter() .setInputCols("document") .setOutputCol("splits") .setChunkSize(20000) .setChunkOverlap(200) .setExplodeSplits(true) val pipeline = new Pipeline().setStages(Array(documentAssembler, textSplitter)) val result = pipeline.fit(textDF).transform(textDF) result .selectExpr( "splits.result", "splits[0].begin", "splits[0].end", "splits[0].end - splits[0].begin as length") .show(8, truncate = 80) +--------------------------------------------------------------------------------+---------------+-------------+------+ | result|splits[0].begin|splits[0].end|length| +--------------------------------------------------------------------------------+---------------+-------------+------+ |[ Project Gutenberg's The Adventures of Sherlock Holmes, by Arthur Conan Doyl...| 0| 19994| 19994| |["And Mademoiselle's address?" he asked.\n\n"Is Briony Lodge, Serpentine Aven...| 19798| 39395| 19597| |["How did that help you?"\n\n"It was all-important. When a woman thinks that ...| 39371| 59242| 19871| |["'But,' said I, 'there would be millions of red-headed men who\nwould apply....| 59166| 77833| 18667| |[My friend was an enthusiastic musician, being himself not only a\nvery capab...| 77835| 97769| 19934| |["And yet I am not convinced of it," I answered. "The cases which\ncome to li...| 97771| 117248| 19477| |["Well, she had a slate-coloured, broad-brimmed straw hat, with a\nfeather of...| 117250| 137242| 19992| |["That sounds a little paradoxical."\n\n"But it is profoundly true. Singulari...| 137244| 157171| 19927| +--------------------------------------------------------------------------------+---------------+-------------+------+
- Grouped
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- DocumentCharacterTextSplitter
- HasSimpleAnnotate
- AnnotatorModel
- CanBeLazy
- RawAnnotator
- HasOutputAnnotationCol
- HasInputAnnotationCols
- HasOutputAnnotatorType
- ParamsAndFeaturesWritable
- HasFeatures
- DefaultParamsWritable
- MLWritable
- Model
- Transformer
- PipelineStage
- Logging
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Instance Constructors
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
- def afterAnnotate(dataset: DataFrame): DataFrame
- Attributes
- protected
- Definition Classes
- DocumentCharacterTextSplitter → 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
- DocumentCharacterTextSplitter → HasSimpleAnnotate
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
- Attributes
- protected
- Definition Classes
- AnnotatorModel
- final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
- val chunkOverlap: IntParam
Length of the overlap between text chunks (Default:
0) - val chunkSize: IntParam
Size of each chunk of text
- final def clear(param: Param[_]): DocumentCharacterTextSplitter.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): DocumentCharacterTextSplitter
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
- 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
- val explodeSplits: BooleanParam
Whether to explode split chunks to separate rows (Default:
false) - 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 getChunkOverlap: Int
- def getChunkSize: Int
- 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 getExplodeSplits: Boolean
- def getInputCols: Array[String]
- returns
input annotations columns currently used
- Definition Classes
- HasInputAnnotationCols
- def getKeepSeparators: Boolean
- def getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
- 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 getPatternsAreRegex: Boolean
- def getSplitPatterns: Array[String]
- def getTrimWhitespace: Boolean
- 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]
Annotator reference id.
Annotator reference id. Used to identify elements in metadata or to refer to this annotator type
- Definition Classes
- DocumentCharacterTextSplitter → 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 keepSeparators: BooleanParam
Whether to keep the separators in the final result (Default:
false) - 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
- 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
- Definition Classes
- DocumentCharacterTextSplitter → HasOutputAnnotatorType
- final val outputCol: Param[String]
- Attributes
- protected
- Definition Classes
- HasOutputAnnotationCol
- lazy val params: Array[Param[_]]
- Definition Classes
- Params
- var parent: Estimator[DocumentCharacterTextSplitter]
- Definition Classes
- Model
- val patternsAreRegex: BooleanParam
Whether to interpret the split patterns as regular expressions (Default:
false) - 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): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[T](feature: SetFeature[T], value: Set[T]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[T](feature: ArrayFeature[T], value: Array[T]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def set(paramPair: ParamPair[_]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def set(param: String, value: Any): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def set[T](param: Param[T], value: T): DocumentCharacterTextSplitter.this.type
- Definition Classes
- Params
- def setChunkOverlap(value: Int): DocumentCharacterTextSplitter.this.type
- def setChunkSize(value: Int): DocumentCharacterTextSplitter.this.type
- def setDefault[T](feature: StructFeature[T], value: () => T): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[K, V](feature: MapFeature[K, V], value: () => Map[K, V]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[T](feature: SetFeature[T], value: () => Set[T]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[T](feature: ArrayFeature[T], value: () => Array[T]): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def setDefault(paramPairs: ParamPair[_]*): DocumentCharacterTextSplitter.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def setDefault[T](param: Param[T], value: T): DocumentCharacterTextSplitter.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
- def setExplodeSplits(value: Boolean): DocumentCharacterTextSplitter.this.type
- final def setInputCols(value: String*): DocumentCharacterTextSplitter.this.type
- Definition Classes
- HasInputAnnotationCols
- def setInputCols(value: Array[String]): DocumentCharacterTextSplitter.this.type
Overrides required annotators column if different than default
Overrides required annotators column if different than default
- Definition Classes
- HasInputAnnotationCols
- def setKeepSeparators(value: Boolean): DocumentCharacterTextSplitter.this.type
- def setLazyAnnotator(value: Boolean): DocumentCharacterTextSplitter.this.type
- Definition Classes
- CanBeLazy
- final def setOutputCol(value: String): DocumentCharacterTextSplitter.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming
- Definition Classes
- HasOutputAnnotationCol
- def setParent(parent: Estimator[DocumentCharacterTextSplitter]): DocumentCharacterTextSplitter
- Definition Classes
- Model
- def setPatternsAreRegex(value: Boolean): DocumentCharacterTextSplitter.this.type
- def setSplitPatterns(value: Array[String]): DocumentCharacterTextSplitter.this.type
- def setTrimWhitespace(value: Boolean): DocumentCharacterTextSplitter.this.type
- val splitPatterns: StringArrayParam
Patterns to separate the text by in decreasing priority (Default:
Array("\n\n", "\n", " ", ""))Patterns to separate the text by in decreasing priority (Default:
Array("\n\n", "\n", " ", ""))Can be interpreted as regular expressions, if
patternsAreRegexis set to true. - 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 trimWhitespace: BooleanParam
Whether to trim whitespaces of extracted chunks (Default:
true) - val uid: String
- Definition Classes
- DocumentCharacterTextSplitter → 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[DocumentCharacterTextSplitter]
Inherited from AnnotatorModel[DocumentCharacterTextSplitter]
Inherited from CanBeLazy
Inherited from RawAnnotator[DocumentCharacterTextSplitter]
Inherited from HasOutputAnnotationCol
Inherited from HasInputAnnotationCols
Inherited from HasOutputAnnotatorType
Inherited from ParamsAndFeaturesWritable
Inherited from HasFeatures
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from Model[DocumentCharacterTextSplitter]
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.