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 Introduction


       An n-gram is a sequence of n tokens (typically words) for some integer n.

      NGramTransform plugin would be used to transform input features into n-grams. 

Use-Case

  • A bio data scientist wants to  study the sequence of the nucleotides using the input stream of DNA sequencing to identify the bonds.
    The input Stream contains the DNA sequence eg AGCTTCGA. The output contains the bigram sequence AG, GC, CT, TT, TC, CG, GA

  •  

    Input source:

     

    DNASequence
    AGCTTCGA

     

    Mandatory inputs from user:NGramTransform:

     

    • Field to be used to transform input features into n-grams:”DNASequence”
    • Number of terms in each n-gram:”2”
    • Transformed field for sequence of n-gram:”bigram”

     

    Output:

     

    bigram

    [AG, GC, CT, TT, TC, CG, GA]

     


User Stories

  • As a Hydrator user,I want to transfom input features data in a column from source schema into output schema which will have a single column having n-gram data.
  • As a Hydrator user I want to have configuration for specifying the column name from input schema on which transformation has to be performed.
  • As a Hydrator user I want to have configuration to specify the no of terms which would be used for transformation of input features into n-grams.
  • As a Hydrator user I want to have configuration to specify output column name wherein ngrams will be emitted.

Conditions

  • Source field ,to be transformed,can be of only type string array.
  • User can transform single field only from the source schema.
  • Output schema will have a single field of type string array.
  • If the input sequence contains fewer than n strings, no output is produced.

Example

Input source:

DNASequence
AGCTTCGA

Mandatory inputs from user:NGramTransform:

  • Field to be used to transform input features into n-grams:”DNASequence
  • Number of terms in each n-gram:”2”
  • Transformed field for sequence of n-gram:”bigram”

Output:

bigram

[AG, GC, CT, TT, TC, CG, GA]

 


End to End Example pipeline:
         

StreamTokenizerNGramTransformTPFSAvro

 

Input source:

 

topicsentence
javahi i heard about spark
HDFShdfs is a file system
Sparkspark is an engine


Tokenizer:

Mandatory inputs from user:

    • Column on which tokenization to be done:”sentence”
    • Delimiter for tokenization:” ”
    • Output column name for tokenized data:”tokens”

NGramTransform:

Mandatory inputs from user:

    • Field to be used to transform input features into n-grams:”tokens”
    • Number of terms in each n-gram:”2”
    • Transformed field for sequence of n-gram:”ngrams”


TPFSAvro Output

ngrams

[hi i,i heard,heard about,about spark]

[hdfs is,is a,a file,file system]

[spark is,is an,an engine]

 

Design

This is a sparkcompute type of plugin and is meant to work with Spark only.

Properties:

  • **fieldToBeTransformed:** Column to be used to transform input features into n-grams.
  • **numberOfTerms:** Number of terms in each n-gram.
  • **outputField:** Transformed column for sequence of n-gram.

Input JSON:

         {
           "name": "NGramTransform",
           "type": "sparkcompute",
           "properties": {
                                   "fieldToBeTransformed": "tokens",
                                   "numberOfTerms": "2",
                                   "outputField": "ngrams"
                                }
          }

Table of Contents

Table of Contents
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Checklist

  •  User stories documented 
  •  User stories reviewed 
  •  Design documented 
  •  Design reviewed 
  •  Feature merged 
  •  Examples and guides 
  •  Integration tests 
  •  Documentation for feature 
  •  Short video demonstrating the feature

...