How much Java is required for Hadoop?
Apache Hadoop is one of the most commonly adopted enterprise solution by big IT giants making it one of the top 10 IT job trends for 2015. Thus, it is mandatory for intelligent technologists to pick up Hadoop quickly with Hadoop ecosystem getting bigger day by day. The outpouring demand for big data analytics is landing many IT professionals to switch their careers to Hadoop technology. Professionals need to consider the skills before they begin to learn Hadoop.
Skills to Learn Hadoop-
Java Knowledge Required for Hadoop-
Hadoop is written in Java, thus knowledge of Java basics is essential to learn Hadoop.
Linux Knowledge Required for Hadoop-
Hadoop runs on Linux, thus knowing some basic Linux commands will take you long way in pursuing successful career in Hadoop.
According to Dice, Java-Hadoop combined skill is in great demand in the IT industry with increasing Hadoop jobs.
Career counsellors at DeZyre frequently answer the question posed by many of the prospective students or professionals who want to switch their career to big data or Hadoop- “How much Java is required for Hadoop”?
Most of the prospective students exhibit some kind of disappointment when they ask this question –they feel not knowing Java to be a limitation and they might have to miss on a great career opportunity. It is one of the biggest myth that- a person from any other programming background other than Java cannot learn Hadoop. (Click here to Tweet)
There are several organizations who are adopting Apache Hadoop as an enterprise solution with changing business requirements and demands. The demand for Hadoop professionals in the market is varying remarkably. Professionals with any of the diversified tech skills like – Mainframes, Java, .NET , PHP or any other programming language expert can learn Hadoop.
If an organization runs an application built on mainframes then they might be looking for candidates who possess Mainframe +Hadoop skills whereas an organization that has its main application built on Java would demand a Hadoop professional with expertise in Java+Hadoop skills.
Let’s consider this analogy with an example-
The job description clearly states that any candidate who knows Hadoop and has strong experience in ETL Informatica can apply for this job to build a career in Hadoop technology without expertise knowledge in Java.The mandatory skills for the job have been highlighted in red which include Hadoop, Informatica,Vertica, Netezza, SQL, Pig, Hive. The skill MapReduce in Java is an additional plus but not required.
Here is another image which shows a job posting on Dice.com for the designation of a Big Data Engineer-
The job description clearly underlines the minimum required skills for this role as Java, Linux and Hadoop. Candidates who have expertise knowledge in Java, Linux and Hadoop can only apply for this job and anybody with Java basics would not be the best fit for this job.
Some of the job roles require the professional to have explicit in-depth knowledge of Java programming whereas few other job roles can be excelled even by professionals who are well-versed with Java basics.
To learn Hadoop and build an excellent career in Hadoop, having basic knowledge of Linux and knowing the basic programming principles of Java is a must. Thus, to incredibly excel in the entrenched technology of Apache Hadoop, it is recommended that you at least learn Java basics.
Java and Linux- Building Blocks of Hadoop
Apache Hadoop is an open source platform built on two technologies Linux operating system and Java programming language. Java is used for storing, analysing and processing large data sets. The choice of using Java as the programming language for the development of hadoop is merely accidental and not thoughtful. Apache Hadoop was initially a sub project of the open search engine Nutch. The Nutch team at that point of time was more comfortable in using Java rather than any other programming language. The choice for using Java for hadoop development was definitely a right decision made by the team with several Java intellects available in the market. Hadoop is Java-based, so it typically requires professionals to learn Java for Hadoop.
Apache Hadoop solves big data processing challenges using distributed parallel processing in a novel way. Apache Hadoop architecture mainly consists of two components-
1.Hadoop Distributed File System (HDFS) –A virtual file system
2.Hadoop Java MapReduce Programming Model Component- Java based system tool
HDFS is the virtual file system component of Hadoop that splits a huge data file into smaller files to be processed by different processors. These small files are then replicated and stored on various servers for fault tolerance constraints. HDFS is a basic file system abstraction where the user need not bother on how it operates or stores files unless he/she is an administrator.
Google’s Java MapReduce framework is the roost of large scale data processing( YARN can also be used for data processing with Hadoop 2.0).Hadoop Java MapReduce component is used to work with processing of huge data sets rather than bogging down its users with the distributed environment complexities.
The Map function mainly filters and sorts data whereas Reduce deals with integrating the outcomes of the map () function. Google’s Java MapReduce framework provides the users with a java based programming interface to facilitate interaction between the Hadoop components. There are various high level abstraction tools like Pig (programmed in Pig Latin ) and Hive (programmed using HiveQL) provided by Apache to work with the data sets on your cluster. The programs written using either of these languages are converted to MapReduce programs in Java.The MapReduce programs can also be written in various other scripting languages like Perl, Ruby, C or Python that support streaming through the Hadoop streaming API, however, there are certain advanced features that are as of now available only with Java API.
Image Credit: saphanatutorial.com
At times, Hadoop developers might be required to dig deep into Hadoop code to understand the functionality of certain modules or why a particular piece of code is behaving strange. Under, such circumstances knowledge of Java basics and advanced programming concepts comes as a boon to Hadoop developers. Technology experts’ advice prospective Hadoopers to learn Java basics before they deep dive into Hadoop for a well-rounded real world Hadoop implementation. Career counsellors suggest students to learn Java for Hadoop before they attempt to work on Hadoop Map Reduce.
How to learn Java for Hadoop?
If you are planning to enrol for Hadoop training, ramp up java knowledge required for hadoop beforehand.
- Professionals aspiring to pursue a successful career in Hadoop can try to learn Java on their own by reading various e-books or by checking out free Java tutorials available online. The learning approach through Java tutorials will work out if a person is skilled at programming. Java tutorials will help you understand and retain information with practical code snippets. This approach might not be the best choice for less experienced programmers as they might not be able to comprehend the code snippets and other examples in the Java tutorial with ease.
- There are several reputed online e-learning classes which provide great options to learn Java for Hadoop. Knowledge experts explain Java basics, plus the students can clarify any doubts they have then and there and engage in discussion with other students to improve their java concepts for hadoop.