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Version 2.9.0-0

Hadoop is a Java-based open-source framework that supports distributed processing of large data quantities on clusters. This open-source framework is scalable and features high-availability capabilities. Hadoop uses the map/reduce algorithm from Google to divide applications into small working units that are then processed in parallel in nodes. When doing so, errors are detected and corrected at application level. Hadoop includes the Hadoop Common, Hadoop Distributed File System (HDFS™), Hadoop YARN and Hadoop MapReduce modules. Hadoop Common provides service programs and libraries that are required by other Hadoop modules. Hadoop Distributed File System (HDFS™) is a distributed file system that can be used to save large data quantities. This file system groups the files into data blocks with a fixed length and divides them into clusters. A feature of HDFS™ is its high data throughput. Hadoop YARN (Yet Another Resource Negotiator) is a framework that allows you to manage cluster resources and job schedules. Hadoop MapReduce is an implementation of the MapReduce algorithm developed by Google. This MapReduce framework executes user-defined map/reduce jobs in a cluster.
  • Highly scalable storage platform.
  • Fast data processing.
  • Hardware failures are automatically handled by the framework.

These applications run on Linux CentOS 7.

Minimum requirements: 1&1 Cloud Server XXL

Your contract allows you to use as many free apps as you’d like. Each app simply needs its own VM.

We recommend:

  • CPU: 4 vCore
  • RAM: 8 GB
  • SSD: 160 GB
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