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Hadoop Ecosystem

 

The Hadoop ecosystem refers to the various components of the Apache Hadoop software library, as well as to the accessories and tools provided by the Apache Software Foundation for these types of software projects, and to the ways that they work together.

 

Hadoop is a Java-based framework that is extremely popular for handling and analyzing very large sets of data. The combination of HDFS and MapReduce provides a software framework for processing vast amounts of data in parallel on large clusters of commodity hardware (potentially scaling to thousands of nodes) in a reliable, fault-tolerant manner. Hadoop is a generic processing framework designed to execute queries and other batch read operations against massive datasets that can scale from tens of terabytes to petabytes in size.

 

 

 

 

The Hadoop platform consists of two key services: a reliable, distributed file system called Hadoop Distributed File System (HDFS) and the high-performance parallel data processing engine called Hadoop MapReduce. 

 

Hadoop was created by Doug Cutting and named after his son’s toy elephant. Vendors that provide Hadoop-based platforms include Cloudera, Hortonworks, MapR, Greenplum, IBM, and Amazon.

 

 

Hadoop has been particularly useful in environments where massive server farms are used to collect data from a variety of sources. Hadoop is able to process parallel queries as big, background batch jobs on the same server farm. This saves the user from having to acquire additional hardware for a traditional database system to process the data (assume such a system can scale to the required size). Hadoop also reduces the effort and time required to load data into another system; you can process it directly within Hadoop. This overhead becomes impractical in very large data sets.

 

Both the core Hadoop package and its accessories are mostly open-source projects licensed by Apache. The idea of a Hadoop ecosystem involves the use of different parts of the core Hadoop set such as MapReduce, a framework for handling vast amounts of data, and the Hadoop Distributed File System (HDFS), a sophisticated file-handling system.  With Hadoop 2.0 comes YARN, a Hadoop resource manager.

 

In addition to these core elements of Hadoop, Apache has also delivered other kinds of accessories or complementary tools for developers. These include Apache Hive, a data analysis tool; Apache Spark, a general engine for processing big data; Apache Pig, a data flow language; HBase, a database tool; and also Ambarl, which can be considered as a Hadoop ecosystem manager, as it helps to administer the use of these various Apache resources together.  Zookeeper is used for federating services and Oozie is a scheduling system.

 

 

The above information was excerpted from:

 

https://www.techopedia.com/definition/31255/hadoop-ecosystem

https://www.thinkbiganalytics.com/leading_big_data_technologies/hadoop/

 

To learn more about Hadoop Ecosystem, please visit https://hadoopecosystemtable.github.io/

 

With Hadoop becoming the de facto standard for data collection and becoming ubiquitous in many organizations, managers and development leaders are learning all about the Hadoop ecosystem and what kinds of things are involved in a general Hadoop setup.

 

Contact Us today to discuss how we can use Hadoop Ecosystem to help your business discover important insights and seek strategic answers that will give you a competitive advantage!