Hadoop Binary Streaming and PDF File Inclusion

  • Articolo

In a previous post I talked about Hadoop Binary Streaming for the processing of Microsoft Office Word documents. However, due to there popularity, I thought inclusion for support of Adobe PDF documents would  be beneficial. To this end I have updated the source code to support processing of both “.docx” and “.pdf” documents.

iTextSharp

To support reading PDFs I have used the open source library provided by iText (https://itextpdf.com/). iText is a library that allows you to read, create and manipulate PDF documents (https://itextpdf.com/download.php). The original code was written in Java but a port for .Net is also available (https://sourceforge.net/projects/itextsharp/files/).

In using these libraries I only use the PdfReader class, from the Core library. This class allows one to derive the page count, and the Author from an Info property.

To use the library in Hadoop one just has to specify a file property for the iTextSharp core library:

-file "C:\Reference Assemblies\itextsharp.dll"

This assumes the downloaded and extracted DLL has been copied to and referenced from the “Reference Assemblies” folder.

Source Code Changes

To support the PDF document inclusion only two changes were necessary to the code.

Firstly, a new Mapper was defined that supports the processing of a PdfReader type and returns the author and pages for the document:

namespace FSharp.Hadoop.MapReduce

open System

open iTextSharp.text
open iTextSharp.text.pdf

// Calculates the pages per author for a Pdf document
module OfficePdfPageMapper =

    let authorKey = "Author"
    let unknownAuthor = "unknown author"

    let getAuthors (document:PdfReader) =          
        // For PDF documents perform the split on a ","
        if document.Info.ContainsKey(authorKey) then
            let creators = document.Info.[authorKey]
            if String.IsNullOrWhiteSpace(creators) then
                [| unknownAuthor |]
            else
                creators.Split(',')
        else
            [| unknownAuthor |]

    let getPages (document:PdfReader) =
        // return page count
        document.NumberOfPages

    // Map the data from input name/value to output name/value
    let Map (document:PdfReader) =
        let pages = getPages document
        (getAuthors document)
        |> Seq.map (fun author -> (author, pages))

Secondly one has to call the correct mapper based on the document type; namely the file extension:

let (|WordDocument|PdfDocument|UnsupportedDocument|) extension =
    if String.Equals(extension, ".docx", StringComparison.InvariantCultureIgnoreCase) then
        WordDocument
    else if String.Equals(extension, ".pdf", StringComparison.InvariantCultureIgnoreCase) then
        PdfDocument
    else
        UnsupportedDocument

// Check we do not have a null document
if (reader.Length > 0L) then
    try
        match Path.GetExtension(filename) with
        | WordDocument ->
            // Get access to the word processing document from the input stream
            use document = WordprocessingDocument.Open(reader, false)
            // Process the word document with the mapper
            OfficeWordPageMapper.Map document
            |> Seq.iter (fun value -> outputCollector value)        
            // close document
            document.Close()
        | PdfDocument ->
            // Get access to the pdf processing document from the input stream
            let document = new PdfReader(reader)
            // Process the word document with the mapper
            OfficePdfPageMapper.Map document
            |> Seq.iter (fun value -> outputCollector value)        
            // close document
            document.Close()
        | UnsupportedDocument ->
            ()
    with
    | :? System.IO.FileFormatException ->
        // Ignore invalid files formats
        ()

And that is it.

Conclusion

In Microsoft Word, if one needs to process the actual text/words of a document, this is relatively straight-forward:

 document.MainDocumentPart.Document.Body.InnerText

Using iText the text/word extraction code is a little more complex but relativity easy. An example can be found here:

https://itextpdf.com/examples/iia.php?id=275

Enjoy!

Comments

  • Anonymous
    March 20, 2013
    Sir,Your idea is great,as I want same with some modification.The theme is,I have thousand of  files pdf,txt,docx in a folder.I want to extracts most occuring top 10 words for each file using Hadoop/any software which gives quick resultsI totally don't know C# & .NET,I try to understand the code,but I can't.I know little bit of Java.Can u tell me how to modify it into Java Program?I will be thankful,if u convert it completely into MapReduce form as many peoples are using Java for Hadoop programmingYou can mail me also - sagarnikam123@gmail.com
  • Anonymous
    March 24, 2013
    Hi Sagar you can use Hadoop for document processing in this fashion, provided you have sufficient volume. If you know Java you can use the Java binary reader that comes with this code as the reader for submitting a MR job written just in Java.
  • Anonymous
    May 08, 2014
    HI Sir -I want to load pdf, word format data in the Hadoop systems. whats the best way to load the data in HDFS.