Why Pig

  • MapReduce Programming Model

  • Opportunities over optimization

  • ASSERT operator

  • AvroStorage

  • IN/CASE operator

  • BigInteger/BigDecimal

  • Diagnostic operators

  • User-defined functions

  • Accumulator Interface

At present, the field of parallel computing can find varied provisions in content analysis. As companies like Google Inc. and Yahoo! Inc. have access to a large number of computers and the amount of data to be processed is also large, the search query processing computations are parallelized across a cluster of computers. In order to organize programming for a distributed environment MapReduce programming model is developed.

Apache Pig opens Hadoop to non-java programmers and provides increased productivity. At Hidden Brains, we analyze large data sets from responsive structure to significant parallelization. Compressing the results of intermediate jobs, we tune the MapReduce functionality and Pig parameters.

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What we offer

  • Performance Tuning
  • Error Handling
  • Function Overloading
  • Progress Reporting
  • Multiple clusters

Business Values

Reaching out to the right people and eventually growing their business with extensive IT services
  • Data security and sentry
  • Excellent memory management
  • Reducing your operator pipeline
  • Scaling out across many servers
  • Working with BAGs of data
  • Custom codes for rich data types

Meet Our Clients

Dawood Fard

Mr. Dawood Fard - Our flexible, accommodating approach and high caliber project delivery impressed him very much.

Joseph Blogna

Joseph Blogna - Our high quality graphics delivery and smooth gaming experience impressed him the most.

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Case Studies

We value the importance of your success by preserving the trust factor for long-term relationships with distinctive and substantial amendments for satisfactory results

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