For all those aiming to harness the potential of big data, Apache Hadoop is the platform of choice. This open source software platform for distributed storage enables processing of very large data sets on computer clusters by distributing them across commodity servers. It eliminates dependency on high-end hardware and makes the entire process cost-effective for businesses to implement. Therefore, it has become an invincible framework for most of the big data enterprises today.
With increased adoption of Hadoop in traditional enterprise IT solutions along with increased number of Hadoop implementations in production environments, the need for Hadoop Operations and Administration experts is becoming vital.
Before we proceed further, let’s have some idea about the genesis of Hadoop.
Brief History of Hadoop
The origin of Hadoop can be rooted to the Google File System paper that was published in October2003. This paper generated another research paper from Google, titled “MapReduce: Simplified Data Processing on Large Clusters”. Following this, the Apache Nutch project started to develop, which was shifted to the new Hadoop subproject in January 2006. Hadoop 0.1.0 was released in April 2006, named after one of the founder’s toy elephant. Since then, the framework has evolved through the years to expand much beyond just web indexing capacity.
The flexible architecture of Hadoop allows adding new functionalities for performing diverse Big Data tasks. Several enterprises have taken advantage of the open-ended framework offered by Hadoop and tweaked its codes to change or enhance its functionalities.
Some of the common benefits of Hadoop are as follows:
- Scalability and Performance:
Distributed processing of local data in a cluster enables Hadoop to store, manage, analyze and process data on an unprecedentedly large scale.
- Reliability: Hadoop is fundamentally resilient. When a node fails, it redirects processing to the remaining nodes in the cluster and automatically re-replicates data in preparation for future node failures.
- Flexibility: Unlike traditional relational database management systems, Hadoop does not require structured schemas to be created before storing data. It allows storing data in any format, including unstructured or semi-structured formats.
- Economical: Hadoop is open source and runs on low-cost commodity hardware.
Responsibilities of a Hadoop Administrator
The roles and responsibilities of a Hadoop Administrator revolve around creating, monitoring and managing the Hadoop Cluster. However, the duties concerning cluster administration vary depending upon the choice of cluster monitoring tools and the adoption of the Hadoop distribution platform (namely, Cloudera, Hortonworks, Apache or MapR).
Typically, the daily tasks of a Hadoop administrator are:
- Installation and administration of Hadoop infrastructure
- Managing scalable Hadoop environment (creation and removal of node)
- Monitoring and logging cluster
- HDFS support and maintenance
- Design, implementation, and maintenance of security and data capacity
- Node forecasting and planning
- Extracting, loading and transforming data in and out of Hadoop.
As we know, Hadoop is an open source project and several vendors have come forward to develop their own distributions in Hadoop framework to make it enterprise ready. The convenience and flexibility of Hadoop distributions lie in the fact that they can be customized with different features to meet the requirements of various classes of users. Hadoop distributions combine all the enhancement projects present in the Apache repository and dispense them as a unified product so that businesses do not have to dedicate time on assembling the elements to form a single functional component.
Founded in 2011, Hortonworks has rapidly emerged as one of the leading vendors of Hadoop. It offers an open source platform based on Apache Hadoop for storing, analyzing and managing big data. Fellow Hadoop vendors such as Cloudera and MapR Technologies have their own versions of the open core model. Cloudera adds some proprietary capabilities to its distribution while MapR has rewritten major parts of Hadoop’s core open source code to create an enterprise software product.
However, Hortonworks is the only commercial vendor to distribute unmodified open source Apache Hadoop without additional proprietary software, straight from the Apache trunk. HortonworksÂ’ allows direct download of HDP2.0 from their website free of cost. Additionally, Hortonworks, which houses the brains behind most of Hadoop’s recent innovations including Yarn, is the only Hadoop distribution vendor that supports Windows platform.
Choosing the right Hadoop Distribution is essential for an organization to utilize and leverage the data generated meaningfully. The adoption of a particular distribution platform completely depends on the requirements of an organization and the obstacles it is facing in implementing Hadoop. When selecting a Hadoop distribution for business needs, it is imperative to consider the value offered by each Hadoop distribution by balancing the cost and the risk factors, for the Hadoop distribution to prove beneficial for the growth of the enterprise.