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

Class CalculateNGramFrequency

  • All Implemented Interfaces:
    LogicalOperator, PipelineOperator<RecordPort>, RecordPipelineOperator
    public class CalculateNGramFrequency
extends ExecutableOperator
implements RecordPipelineOperator
    Calculates the n-gram frequencies for a tokenized text field. This operator can be used to determine the frequencies of each n-gram in the original text. The CalculateNGramFrequency operator has three properties: input field, output field, and the n to use. By default will calculate frequencies for an n of 2. The operator will output an NGramMap object that contains the n-grams and their associated frequencies. This object can then be used by other operators such as TextFrequencyFilter or ExpandTextFrequency that operate on a frequency model.

    • Constructor Detail

      • CalculateNGramFrequency

        public CalculateNGramFrequency()
        Default constructor. Use setInputField(String), #setNGramFreqOutputField(String) to set the name of the text field to count and the output field.

      • CalculateNGramFrequency

        public CalculateNGramFrequency​(String textField)
        Constructor specifying the tokenized text field to determine the n-gram frequencies for.
        Parameters:
        textField - name of the tokenized text field in the input

      • CalculateNGramFrequency

        public CalculateNGramFrequency​(String textField,
                               int n)
        Constructor specifying the tokenized text field to determine the n-gram frequencies for and the n to use.
        Parameters:
        textField - name of the tokenized text field in the input
        n - the number of words per n-gram

    • Method Detail

      • setInputField

        public void setInputField​(String textField)
        Set the field to calculate the n-gram frequencies for.

        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 - name of the tokenized text field in the input

      • getInputField

        public String getInputField()
        Get the field to calculate the n-gram frequencies for.
        Returns:
        name of the tokenized text field in the input

      • setNgramFreqOutputField

        public void setNgramFreqOutputField​(String ngramFreqOutputField)
        Set the field that will contain the n-gram frequency map.
        Parameters:
        ngramFreqOutputField - name of the n-gram field in the output

      • getNgramFreqOutputField

        public String getNgramFreqOutputField()
        Get the field that will contain the n-gram frequncy map.
        Returns:
        name of the n-gram field in the output

      • setN

        public void setN​(int n)
        Set the N for the n-grams. Defaults to 2.
        Parameters:
        n - the number of words per n-gram

      • getN

        public int getN()
        Get the N for the n-grams.
        Returns:
        the number of words per n-gram

      • 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