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HParser

Easily process any file format in an optimized, consistent way with Hadoop parsing.

Reduce the Time and Cost of Hadoop Parsing

HParser is a data transformation (data handler) environment optimized for Hadoop. This easy-to-use, codeless parsing software enables processing of any file format inside Hadoop with scale and efficiency. It provides Hadoop developers with out-of-the-box Hadoop parsing capabilities to address the variety and complexity of data sources, including logs, industry standards, documents, and binary or hierarchical data.

  • Easily access complex data sources and develop data transformations for Hadoop parsing, with broadest support for data formats
  • Eliminate the time-consuming and tedious process of developing and testing data transformations in Java and PERL

HParser Key Features

Data Transformation Studio

  • Purpose-built, highly visual, and productive environment with simple point-and-click, mark-and-map process to define parsing
  • Binary view and document preprocessors for Hadoop parsing to extract data locked in binary formats, including packed data, PDF files, Microsoft Word documents, and Microsoft Excel documents

Data Format Transformation Libraries

Embedded Data Transformation Engine

  • Advanced, native streaming and splitting capabilities  allow effective handling of files in any size regardless of format
  • Integrated HParser enables MapReduce tasks to address different data formats through a single data abstraction layer

Available in three editions

  • HParser for Logs, Omniture, XML and JSON (Community Edition) – Available free of charge, with Informatica support and add-on features available for purchase
  • HParser for Industry Standards (Commercial Edition)
  • HParser for Documents (Commercial Edition)

Services & Training

Informatica offers a full range of services and training to help you maximize the value of the Informatica Platform in your environment.

Learn More About Services

HParser Buzz

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Big Data Innovation in Analytics (Hadoop) and Hand-coding (Informatica)
... on Hadoop. We are already seeing great examples of enter

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