class BigTextMatcherModel extends AnnotatorModel[BigTextMatcherModel] with HasSimpleAnnotate[BigTextMatcherModel] with HasStorageModel
Instantiated model of the BigTextMatcher. For usage and examples see the documentation of the main class.
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- BigTextMatcherModel
- HasStorageModel
- HasStorageOptions
- HasStorageReader
- HasCaseSensitiveProperties
- HasStorageRef
- HasSimpleAnnotate
- AnnotatorModel
- CanBeLazy
- RawAnnotator
- HasOutputAnnotationCol
- HasInputAnnotationCols
- HasOutputAnnotatorType
- ParamsAndFeaturesWritable
- HasFeatures
- DefaultParamsWritable
- MLWritable
- Model
- Transformer
- PipelineStage
- Logging
- Params
- Serializable
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- 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
- AnnotatorModel
- def annotate(annotations: Seq[Annotation]): Seq[Annotation]
Defines annotator phrase matching depending on whether we are using SBD or not
Defines annotator phrase matching depending on whether we are using SBD or not
- 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
- BigTextMatcherModel → HasSimpleAnnotate
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
- Attributes
- protected
- Definition Classes
- AnnotatorModel
- val caseSensitive: BooleanParam
Whether to ignore case in index lookups (Default depends on model)
Whether to ignore case in index lookups (Default depends on model)
- Definition Classes
- HasCaseSensitiveProperties
- final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
- final def clear(param: Param[_]): BigTextMatcherModel.this.type
- Definition Classes
- Params
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @HotSpotIntrinsicCandidate() @native()
- final def collapse(rs: List[(Int, Int)], sep: List[(Int, Int)] = Nil): List[(Int, Int)]
- Attributes
- protected
- Annotations
- @tailrec()
- def copy(extra: ParamMap): BigTextMatcherModel
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
- def createDatabaseConnection(database: Name): RocksDBConnection
- Definition Classes
- HasStorageRef
- def createReader(database: Name, connection: RocksDBConnection): StorageReader[_]
- Attributes
- protected
- Definition Classes
- BigTextMatcherModel → HasStorageReader
- val databases: Array[Name]
- Attributes
- protected
- Definition Classes
- BigTextMatcherModel → HasStorageModel
- final def defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
- def deserializeStorage(path: String, spark: SparkSession): Unit
- Definition Classes
- HasStorageModel
- 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 enableInMemoryStorage: BooleanParam
- Definition Classes
- HasStorageOptions
- 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 getCaseSensitive: Boolean
- Definition Classes
- HasCaseSensitiveProperties
- 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 getEnableInMemoryStorage: Boolean
- Definition Classes
- HasStorageOptions
- def getIncludeStorage: Boolean
- Definition Classes
- HasStorageOptions
- def getInputCols: Array[String]
- returns
input annotations columns currently used
- Definition Classes
- HasInputAnnotationCols
- def getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
- def getMergeOverlapping: Boolean
- 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 getReader[A](database: Name): StorageReader[A]
- Attributes
- protected
- Definition Classes
- HasStorageReader
- def getStorageRef: String
- Definition Classes
- HasStorageRef
- 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()
- val includeStorage: BooleanParam
- Definition Classes
- HasStorageOptions
- 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 Types: DOCUMENT, TOKEN
Input Annotator Types: DOCUMENT, TOKEN
- Definition Classes
- BigTextMatcherModel → 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
- def merge(rs: List[(Int, Int)]): List[(Int, Int)]
- Attributes
- protected
- val mergeOverlapping: BooleanParam
Whether to merge overlapping matched chunks (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
- HasStorageModel → ParamsAndFeaturesWritable
- val optionalInputAnnotatorTypes: Array[String]
- Definition Classes
- HasInputAnnotationCols
- val outputAnnotatorType: AnnotatorType
Output Annotator Types: CHUNK
Output Annotator Types: CHUNK
- Definition Classes
- BigTextMatcherModel → HasOutputAnnotatorType
- final val outputCol: Param[String]
- Attributes
- protected
- Definition Classes
- HasOutputAnnotationCol
- lazy val params: Array[Param[_]]
- Definition Classes
- Params
- var parent: Estimator[BigTextMatcherModel]
- Definition Classes
- Model
- val readers: Map[Name, StorageReader[_]]
- Attributes
- protected
- Definition Classes
- HasStorageReader
- Annotations
- @transient()
- 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 saveStorage(path: String, spark: SparkSession, withinStorage: Boolean = false): Unit
- Definition Classes
- HasStorageModel
- def serializeStorage(path: String, spark: SparkSession): Unit
- Definition Classes
- HasStorageModel
- def set[T](feature: StructFeature[T], value: T): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[T](feature: SetFeature[T], value: Set[T]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def set[T](feature: ArrayFeature[T], value: Array[T]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def set(paramPair: ParamPair[_]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def set(param: String, value: Any): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def set[T](param: Param[T], value: T): BigTextMatcherModel.this.type
- Definition Classes
- Params
- def setCaseSensitive(value: Boolean): BigTextMatcherModel.this.type
- Definition Classes
- HasCaseSensitiveProperties
- def setDefault[T](feature: StructFeature[T], value: () => T): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[K, V](feature: MapFeature[K, V], value: () => Map[K, V]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[T](feature: SetFeature[T], value: () => Set[T]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- def setDefault[T](feature: ArrayFeature[T], value: () => Array[T]): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
- final def setDefault(paramPairs: ParamPair[_]*): BigTextMatcherModel.this.type
- Attributes
- protected
- Definition Classes
- Params
- final def setDefault[T](param: Param[T], value: T): BigTextMatcherModel.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
- def setEnableInMemoryStorage(value: Boolean): BigTextMatcherModel.this.type
- Definition Classes
- HasStorageOptions
- def setIncludeStorage(value: Boolean): BigTextMatcherModel.this.type
- Definition Classes
- HasStorageOptions
- final def setInputCols(value: String*): BigTextMatcherModel.this.type
- Definition Classes
- HasInputAnnotationCols
- def setInputCols(value: Array[String]): BigTextMatcherModel.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): BigTextMatcherModel.this.type
- Definition Classes
- CanBeLazy
- def setMergeOverlapping(v: Boolean): BigTextMatcherModel.this.type
- final def setOutputCol(value: String): BigTextMatcherModel.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming
- Definition Classes
- HasOutputAnnotationCol
- def setParent(parent: Estimator[BigTextMatcherModel]): BigTextMatcherModel
- Definition Classes
- Model
- def setStorageRef(value: String): BigTextMatcherModel.this.type
- Definition Classes
- HasStorageRef
- val storageRef: Param[String]
Unique identifier for storage (Default:
this.uid)Unique identifier for storage (Default:
this.uid)- Definition Classes
- HasStorageRef
- 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
- BigTextMatcherModel → 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
- def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
- Definition Classes
- HasStorageRef
- 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)