Hadoop is an open-source framework designed for distributed storage and processing of large datasets using a cluster of commodity hardware. It utilizes the Hadoop Distributed File System (HDFS) for scalable and reliable data storage, and MapReduce for parallel data processing across nodes in a cluster.
About Hadoop
Hadoop was created in 2006 by Doug Cutting and Mike Cafarella. It was developed to support the Nutch search engine project, addressing the need for a system capable of handling vast amounts of data efficiently. Yahoo! played a significant role in its development, contributing resources and support to help evolve Hadoop into a robust platform for big data processing.
Hadoop's strengths included its scalability, cost-effectiveness, and ability to handle large volumes of structured and unstructured data. Weaknesses involved complex setup, maintenance challenges, and slower performance with small datasets. Competitors included Apache Spark, Google BigQuery, and Amazon Redshift.
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How to hire a Hadoop expert
A Hadoop expert must have skills in HDFS, MapReduce programming, and knowledge of the Hadoop ecosystem tools like Hive, Pig, and HBase. Proficiency in Java or Python for scripting and data processing is essential. Understanding of data ingestion tools like Sqoop and Flume, as well as experience with cluster management using tools like Ambari or Cloudera Manager, is also important.
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