I want to read the PDF file using hadoop, how it is possible?
I only know that hadoop can process only txt files, so is there anyway to parse the PDF files to txt.
Give me some suggestion.
An easy way would be to create a SequenceFile to contain the PDF files. SequenceFile is a binary file format. You could make each record in the SequenceFile a PDF. To do this you would create a class derived from Writable which would contain the PDF and any metadata that you needed. Then you could use any java PDF library such as PDFBox to manipulate the PDFs.
Processing PDF files in Hadoop can be done by extending FileInputFormat Class. Let the class extending it be WholeFileInputFormat. In the WholeFileInputFormat class you override the getRecordReader() method. Now each pdf will be received as an Individual Input Split. Then these individual splits can be parsed to extract the text. This link gives a clear example of understanding how to extend FileInputFormat.
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This is my first time using Ruby. I'm writing an application that parses data and performs some calculations based on it, the source of which is a JSON file. I'm aware I can use JSON.parse() here but I'm trying to write my program so that it will work with other sources of data. Is there a clear cut way of doing this? Thank you.
When your source file is JSON then use JSON.parse. Do not implement a JSON parser on your own. If the source file is a CSV, then use the CSV class.
When your application should be able to read multiple different formats then just add one Reader class for each data type, like JSONReader, CSVReader, etc. And then decide depending on the file extension which reader to use to read the file.
With the Autoloader feature, As per the documentation the configuration cloudFiles.format supports json, csv, text, parquet, binary and so on. Wanted to know if there is support for XML ?
For streaming file data sources supported file formats are text, CSV, JSON, ORC, Parquet. My assumption is that only streaming file formats are supported.
Not sure if you got a chance to go through https://github.com/databricks/spark-xml for more complex xml-files with the spark-xml library . If you want to make use of this, auto loader won' t help.
I have large numbers PDF document, from which I need to extract text. The extracted text I use for further processing. I did this for a small subset of documents using Tesseract API in a linear approach and I get the required output. However, this takes a very long time when I have a large number of documents.
I tried to use the Hadoop environment processing capabilities (Map-Reduce) and storage (HDFS) for solving this issue. However, I am facing problem to implement Tesseract API into the Hadoop (Map-Reduce) approach. As Teserract converts the files into intermediate image files, I am confused as to how intermediate result Image files of Tesseract-API-process can be handled inside HDFS.
I have searched and unsuccesfully tried a few options earlier like:
I have extracted text from PDF by extending FileInputFormat class into my own PdfInputFormat class using Hadoop-Map-Reduce, for this i used Apache PDFBox to extract text from pdf, but when it comes to scanned-pdf's which contains image, this solution does not give me the required results.
I found few answers on the same topic stating to use -Fuse and that will help or one should generate image files locally and than upload those into hdfs for further processing. Not sure if this is the correct approach.
Would like to know approaches around this.
This is an approach found to process multiple pdf's to extract text using the power of the Hadoop Framework, and then use this text for further processing:
Put all the PDFs to be converted to text in one folder.
Create one text file per pdf to contain the path to the pdf. e.g. if I have 10 pdfs to convert, then I have 10 text files generated, each containing the unique path to the respective pdf.
These text files are given as input in the map-reduce program
Because input file size is very small only 1 input split is generated by framework for 1 input. e.g if I have 10 pdfs as input, then framework will generate 10 input-split.
From each Input-split one line(record) is read by Record-Reader and passed to one mapper as a value. So if there are 10 records(line==File Path) in input text file , 10 times mapper will run. As I have one record per input-split so one mapper-reducer is assigned to do task for that input-split.
As I have 10 input-split 10 mapper will run, parallel.
Inside the Mapper ghost-script generates images, passing the file name from Mapper value attribute. The image is converted to text using Tesseract inside the mapper itself to get the text of each pdf. This is the output.
This is passed to the reducer to do other analytics work as required.
This is the current solution. Would like feedback on this.
If the input files in XML format, I shouldn't be using TextInputFormat because TextInputFormat assumes each record is in each line of the input file and the Mapper class is called for each line to get a Key Value pair for that record/line.
So I think we need a custom input format to scan the XML datasets.
Being new to Hadoop mapreduce, is there any article/link/video that shows the steps to build a custom input format?
thanks
nath
Problem
Working on a single XML file in parallel in MapReduce is tricky because XML does not contain a synchronization marker in its data format. Therefore, how do we work with a file format that’s not inherently splittable like XML?
Solution
MapReduce doesn’t contain built-in support for XML, so we have to turn to another Apache project, Mahout, a machine learning system, which provides an XML InputFormat.
So I mean no need to have custom input format since Mahout library present.
I am not sure, whether you are going to read or write but both were described in above link.
Pls have a look at XmlInputFormat implementation details here.
Furthermore, XmlInputFormat extends TextInputFormat
I can't load Microsoft Word documents (.doc or .docx) with pig. Indeed, when i try to do so, by using TextLoader(), PigStorage() or no loader at all, it doesn't work. The output is some weird symbols.
I heard that I could write a custom loader in JAVA but it seems really difficult and I don't underdstand how we can program one of these at the moment.
I would like to put all the .doc file content in a single chararray bag so I could later use a filter function to process it.
How could I do ?
Thanks
They are right. Since .doc and .docx are binary formats, simple text loaders won't work. You can either write the UDF to be able to load the files directly into Pig, or you can do some preprocessing to convert all .doc and .docx files into .txt files so that Pig will be loading those .txt files instead. This link may help you get started in finding a way to convert the files.
However, I'd still recommend learning to write the UDF. Preprocessing the files is going to add significant overhead that can be avoided.
Update: Here are a couple of resources I've used for writing my java (Load) UDFs in the past. One, Two.