Module datarush.analytics
Package com.pervasive.datarush.analytics.text

Class DictionaryFilter

  • All Implemented Interfaces:
    LogicalOperator, PipelineOperator<RecordPort>, RecordPipelineOperator
    public class DictionaryFilter
extends ExecutableOperator
implements RecordPipelineOperator
    Filters a tokenized text field using a dictionary. This operator can be used to filter a tokenized text field based on a dictionary. The DictionaryFilter operator has four properties: input field, output field, dictionary input field, and whether the filter should be inverted. The input field must be a tokenized text object. The tokenized text object will be filtered of all words that are specified in the dictionary input. This will produce a new tokenized text object that will be encoded into the output field. This object can then be used for further text processing tasks.

    • Constructor Detail

      • DictionaryFilter

        public DictionaryFilter​(String textField)
        Constructor specifying the tokenized text field to filter.
        Parameters:
        textField - name of the field to filter

      • DictionaryFilter

        public DictionaryFilter​(String textField,
                        String dictionaryField)
        Constructor specifying the tokenized text field to filter and the dictionary field in the dictionary input.
        Parameters:
        textField - name of the field to filter
        dictionaryField - name of the dicitonary field

    • Method Detail

      • setInputField

        public void setInputField​(String textField)
        Set the field to filter.

        If this field does not exist in the input, or is not of type TokenizedText, an exception will be thrown at composition time.

        Parameters:
        textField - the name of the field to filter

      • getInputField

        public String getInputField()
        Get the tokenized text field to filter.
        Returns:
        The name of the field to filter

      • setOutputField

        public void setOutputField​(String tokenField)
        Set the name of the filtered output field.
        Parameters:
        tokenField - name of the token output field

      • getOutputField

        public String getOutputField()
        Get the name of the filtered output field.
        Returns:
        The name of the filtered output field

      • setDictionaryField

        public void setDictionaryField​(String dictionaryField)
        Set the dictionary field in the dictionary input.
        Parameters:
        dictionaryField - name of the dictionary field

      • getDictionaryField

        public String getDictionaryField()
        Get the dictionary field in the dictionary input.
        Returns:
        name of the dictionary field

      • setInverted

        public void setInverted​(boolean inverted)
        Set whether the filter should be inverted.
        Parameters:
        inverted - if true invert filter

      • getInverted

        public boolean getInverted()
        Get whether the filter should be inverted
        Returns:
        true if filter inverted

      • getDictionaryInput

        public RecordPort getDictionaryInput()
        Get the optional dictionary input port of this operator.
        Returns:
        dictionary port

      • computeMetadata

        protected void computeMetadata​(StreamingMetadataContext ctx)
        Description copied from class: StreamingOperator
        Implementations must adhere to the following contracts

        General

        Regardless of input ports/output port types, all implementations must do the following:

        1. Validation. Validation of configuration should always be performed first.
        2. Declare parallelizability.. Implementations must declare parallelizability by calling StreamingMetadataContext.parallelize(ParallelismStrategy).

        Input record ports

        Implementations with input record ports must declare the following:
        1. Required data ordering:
          2. Implementations that have data ordering requirements must declare them by calling RecordPort#setRequiredDataOrdering, otherwise data may arrive in any order.
        2. Required data distribution (only applies to parallelizable operators):
          3. Implementations that have data distribution requirements must declare them by calling RecordPort#setRequiredDataDistribution, otherwise data will arrive in an unspecified partial distribution.
        Note that if the upstream operator's output distribution/ordering is compatible with those required, we avoid a re-sort/re-distribution which is generally a very large savings from a performance standpoint. In addition, some operators may chose to query the upstream output distribution/ordering by calling RecordPort#getSourceDataDistribution and RecordPort#getSourceDataOrdering. These should be viewed as a hints to help chose a more efficient algorithm. In such cases, though, operators must still declare data ordering and data distribution requirements; otherwise there is no guarantee that data will arrive sorted/distributed as required.

        Output record ports

        Implementations with output record ports must declare the following:
        1. Type: Implementations must declare their output type by calling RecordPort#setType.
        Implementations with output record ports may declare the following:
        1. Output data ordering: Implementations that can make guarantees as to their output ordering may do so by calling RecordPort#setOutputDataOrdering
        2. Output data distribution (only applies to parallelizable operators): Implementations that can make guarantees as to their output distribution may do so by calling RecordPort#setOutputDataDistribution
        Note that both of these properties are optional; if unspecified, performance may suffer since the framework may unnecessarily re-sort/re-distributed the data.

        Input model ports

        In general, there is nothing special to declare for input model ports. Models are implicitly duplicated to all partitions when going from non-parallel to parallel operators. The case of a model going from a parallel to a non-parallel node is a special case of a "model reducer" operator. In the case of a model reducer, the downstream operator, must declare the following:
        1. Merge handler: Model reducers must declare a merge handler by calling AbstractModelPort#setMergeHandler.
        Note that MergeModel is a convenient, re-usable model reducer, parameterized with a merge-handler.

        Output model ports

        SimpleModelPort's have no associated metadata and therefore there is never any output metadata to declare. PMMLPort's, on the other hand, do have associated metadata. For all PMMLPorts, implementations must declare the following:
        1. pmmlModelSpec: Implementations must declare the PMML model spec by calling PMMLPort.setPMMLModelSpec.
        Specified by:
        computeMetadata in class StreamingOperator
        Parameters:
        ctx - the context

      • execute

        protected void execute​(ExecutionContext ctx)
        Description copied from class: ExecutableOperator
        Executes the operator. Implementations should adhere to the following contracts:
        1. Following execution, all input ports must be at end-of-data.
        2. Following execution, all output ports must be at end-of-data.
        Specified by:
        execute in class ExecutableOperator
        Parameters:
        ctx - context in which to lookup physical ports bound to logical ports