Apache Hadoop

Apache Hadoop is an open source software project that enables distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with very high degree of fault tolerance. Rather than relying on high-end hardware, the resiliency of these clusters comes from the software's ability to detect and handle failures at the application layer.

Hadoop Core Components

The core of Apache Hadoop consists of a storage part (Hadoop Distributed File System (HDFS)) and a processing part (MapReduce). Hadoop splits files into large blocks and distributes them amongst the nodes in the cluster. To process the data, Hadoop MapReduce transfers packaged code for nodes to process in parallel, based on the data each node needs to process. This approach takes advantage of data locality—nodes manipulating the data that they have on hand—to allow the data to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are connected via high-speed networking

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The Hadoop ecosystem includes:

  • HBase – columnar database
  • Hive – relational style database built on HDFS
  • Oozie – job orchestration and dependency management.
  • Sqoop – RDBMS – Hadoop import, and vice versa
  • Pig – Data Transformation
  • Solr – Hadoop indexing and search tool

Estuate offers the following value added services around Hadoop Eco System

  • Hadoop Training and Enablement
  • Cluster security, infrastructure setup and administration, and application development.
  • Application Development on Hadoop environment and other flavors ( Cloudera, Hortonworks, IBM)
  • Data Ingestion from various sources.
  • Internal center of Excellence within Estuate to explore Hadoop technology and develop proofs of concept.
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