BigTextMatcher

Instance Constructors

new BigTextMatcher()
new BigTextMatcher(uid: String)

Type Members

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 _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): BigTextMatcherModel

Attributes
protected
Definition Classes
AnnotatorApproach
final def asInstanceOf[T0]: T0

Definition Classes
Any
def beforeTraining(spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
val caseSensitive: BooleanParam

Definition Classes
HasCaseSensitiveProperties
final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def clear(param: Param[_]): BigTextMatcher.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def copy(extra: ParamMap): Estimator[BigTextMatcherModel]

Definition Classes
AnnotatorApproach → Estimator → 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 createWriter(database: Name, connection: RocksDBConnection): StorageWriter[_]

Attributes
protected
Definition Classes
BigTextMatcher → HasStorage
val databases: Array[Name]

Attributes
protected
Definition Classes
BigTextMatcher → HasStorage
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
val description: String

Definition Classes
BigTextMatcher → AnnotatorApproach
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
val features: ArrayBuffer[Feature[_, _, _]]

Definition Classes
HasFeatures
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def fit(dataset: Dataset[_]): BigTextMatcherModel

Definition Classes
AnnotatorApproach → Estimator
def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[BigTextMatcherModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): BigTextMatcherModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BigTextMatcherModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
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[_]

Definition Classes
AnyRef → Any
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
def getIncludeStorage: Boolean

Definition Classes
HasExcludableStorage
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 getStoragePath: Option[ExternalResource]

Definition Classes
HasStorage
def getStorageRef: String

Definition Classes
HasStorageRef
def getTokenizer: TokenizerModel
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hashCode(): Int

Definition Classes
AnyRef → Any
val includeStorage: BooleanParam

Definition Classes
HasExcludableStorage
def index(fitDataset: Dataset[_], storageSourcePath: Option[String], readAs: Option[util.io.ReadAs.Value], writers: Map[Name, StorageWriter[_]], readOptions: Option[Map[String, String]]): Unit

Attributes
protected
Definition Classes
BigTextMatcher → HasStorage
def indexStorage(fitDataset: Dataset[_], resource: Option[ExternalResource]): Unit

Definition Classes
HasStorage
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[String]

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

Definition Classes
BigTextMatcher → 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 mergeOverlapping: BooleanParam
val missingRefMsg: String

Attributes
protected
Definition Classes
HasStorage
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
final def notifyAll(): Unit

Definition Classes
AnyRef
def onTrained(model: BigTextMatcherModel, spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
def onWrite(path: String, spark: SparkSession): Unit

Attributes
protected
Definition Classes
ParamsAndFeaturesWritable
val outputAnnotatorType: AnnotatorType

Definition Classes
BigTextMatcher → HasOutputAnnotatorType
final val outputCol: Param[String]

Attributes
protected
Definition Classes
HasOutputAnnotationCol
lazy val params: Array[Param[_]]

Definition Classes
Params
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
def set[T](feature: StructFeature[T], value: T): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[T](feature: SetFeature[T], value: Set[T]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[T](feature: ArrayFeature[T], value: Array[T]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
final def set(paramPair: ParamPair[_]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): BigTextMatcher.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): BigTextMatcher.this.type

Definition Classes
Params
def setCaseSensitive(value: Boolean): BigTextMatcher.this.type

Definition Classes
HasCaseSensitiveProperties
def setDefault[T](feature: StructFeature[T], value: () ⇒ T): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): BigTextMatcher.this.type

Attributes
protected
Definition Classes
HasFeatures
final def setDefault(paramPairs: ParamPair[_]*): BigTextMatcher.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): BigTextMatcher.this.type

Attributes
protected
Definition Classes
Params
def setIncludeStorage(value: Boolean): BigTextMatcher.this.type

Definition Classes
HasExcludableStorage
final def setInputCols(value: String*): BigTextMatcher.this.type

Definition Classes
HasInputAnnotationCols
final def setInputCols(value: Array[String]): BigTextMatcher.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): BigTextMatcher.this.type

Definition Classes
CanBeLazy
def setMergeOverlapping(v: Boolean): BigTextMatcher.this.type
final def setOutputCol(value: String): BigTextMatcher.this.type

Overrides annotation column name when transforming
Overrides annotation column name when transforming

Definition Classes
HasOutputAnnotationCol
def setStoragePath(path: String, readAs: util.io.ReadAs.Value): BigTextMatcher.this.type

Definition Classes
HasStorage
def setStoragePath(path: String, readAs: String): BigTextMatcher.this.type

Definition Classes
HasStorage
def setStorageRef(value: String): BigTextMatcher.this.type

Definition Classes
HasStorageRef
def setTokenizer(tokenizer: TokenizerModel): BigTextMatcher.this.type
val storagePath: ExternalResourceParam

Definition Classes
HasStorage
val storageRef: Param[String]

Definition Classes
HasStorageRef
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
val tokenizer: StructFeature[TokenizerModel]
def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): BigTextMatcherModel

Definition Classes
BigTextMatcher → AnnotatorApproach
final def transformSchema(schema: StructType): StructType

requirement for pipeline transformation validation.
requirement for pipeline transformation validation. It is called on fit()

Definition Classes
AnnotatorApproach → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

Definition Classes
BigTextMatcher → 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
AnnotatorApproach
def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit

Definition Classes
HasStorageRef
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
def write: MLWriter

Definition Classes
ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Related Docs: object BigTextMatcher | package btm

class BigTextMatcher extends AnnotatorApproach[BigTextMatcherModel] with HasStorage

Instance Constructors

new BigTextMatcher()

new BigTextMatcher(uid: String)

Type Members

type AnnotatorType = String

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

def $$[T](feature: StructFeature[T]): T

def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

def $$[T](feature: SetFeature[T]): Set[T]

def $$[T](feature: ArrayFeature[T]): Array[T]

final def ==(arg0: Any): Boolean

def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): BigTextMatcherModel

final def asInstanceOf[T0]: T0

def beforeTraining(spark: SparkSession): Unit

val caseSensitive: BooleanParam

final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

final def clear(param: Param[_]): BigTextMatcher.this.type

def clone(): AnyRef

final def copy(extra: ParamMap): Estimator[BigTextMatcherModel]

def copyValues[T <: Params](to: T, extra: ParamMap): T

def createDatabaseConnection(database: Name): RocksDBConnection

def createWriter(database: Name, connection: RocksDBConnection): StorageWriter[_]

val databases: Array[Name]

final def defaultCopy[T <: Params](extra: ParamMap): T

val description: String

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

val features: ArrayBuffer[Feature[_, _, _]]

def finalize(): Unit

final def fit(dataset: Dataset[_]): BigTextMatcherModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[BigTextMatcherModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): BigTextMatcherModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BigTextMatcherModel

def get[T](feature: StructFeature[T]): Option[T]

def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

def get[T](feature: SetFeature[T]): Option[Set[T]]

def get[T](feature: ArrayFeature[T]): Option[Array[T]]

final def get[T](param: Param[T]): Option[T]

def getCaseSensitive: Boolean

final def getClass(): Class[_]

final def getDefault[T](param: Param[T]): Option[T]

def getIncludeStorage: Boolean

def getInputCols: Array[String]

def getLazyAnnotator: Boolean

def getMergeOverlapping: Boolean

final def getOrDefault[T](param: Param[T]): T

final def getOutputCol: String

def getParam(paramName: String): Param[Any]

def getStoragePath: Option[ExternalResource]

def getStorageRef: String

def getTokenizer: TokenizerModel

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hashCode(): Int

val includeStorage: BooleanParam

def index(fitDataset: Dataset[_], storageSourcePath: Option[String], readAs: Option[util.io.ReadAs.Value], writers: Map[Name, StorageWriter[_]], readOptions: Option[Map[String, String]]): Unit

def indexStorage(fitDataset: Dataset[_], resource: Option[ExternalResource]): Unit

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

val inputAnnotatorTypes: Array[String]

final val inputCols: StringArrayParam

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

val lazyAnnotator: BooleanParam

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit