Hadoop Learning Path - Quick start your career in IT industry
In this article I will provide information for learning Hadoop in a step-by-step fashion. You can learn Hadoop with following learning mentioned here. Hadoop and Big Data is one of the most lucrative careers in IT industry as there is huge gap between demand skilled IT professionals in the market. Developers can take advantage of this opportunity and make their career in Hadoop Application Development, Hadoop Administration or Big Data analytics.
Hadoop is open source platform for storing data over thousands of nodes in a cluster. It is also a platform for distributed parallel processing of data over nodes in the cluster. Hadoop is designed to process the data over the cluster where it resides to avoid large scale movement of data between cluster. For example if you developed a program for some processing, Hadoop will distribute the processing work through MapReduce job on the data nodes where data resides.
Hadoop was developed as a platform for handling data over HDFS in the Hadoop cluster and process data using MapReduce. There are many parallel projects at Apache Foundation for Hadoop Platform. These software are collectively known as Hadoop eco-system components. Examples of eco-system components are Pig, Hive, HBase, Sqoop etc.. and developers are expected to learn these software to work on any Big Data project.
Hadoop growth potential
According to the various researches by various organizations, the market of Hadoop will be of $46.34 billion dollars by 2018 and there will be a growth of 58.2% by 2020. So, this is good opportunity for the IT professionals in making good career in IT field. Developers and other IT professional having prior experience in software related activities can learn Hadoop and Big Data to tap these opportunities.
There is huge growth potential in the field of Big Data and Hadoop, but there is shortage of skilled professionals in this field. So, learning Hadoop and Big Data will make your career boost with the opportunity to move further with the growth of industry.
Hadoop Learning Path
Now lets discuss the learning Path for Hadoop and the Big Data. Here is the step-by-step guide for learning Hadoop from scratch and make your career in Big Data based technologies.
1. Pre-requisites to learn Hadoop
Let's first see who call can learn Hadoop and application development technologies for Hadoop Platform. IT professionals having prior experience in programming, databases, scripting or testing can learn Hadoop. If you don't have any programming experience you are advised to learn any programming language such Java, Scala or Python. Developers having experience in Microsoft technologies can also start learning Hadoop and Big Data.
2. Understand Big Data and Hadoop
The next step is to understand Big Data and Hadoop in detail. Big Data is a term used to present extremely high quantity of data which is impossible to manage with traditional software and a single computer. Example of Big Data is enormous amount of data generated by social networking websites which requires thousands of computers to handle it. Specialized software packages are used these days to manage and process these data over large number of sever(node) in a cluster. These software packages are known as Big Data Platform. You can view complete details at What is Big Data Platform?. Hadoop is one of the Big Data platform which is open source and free.
3. Getting Started with Hadoop
Now you can start learning Hadoop, but before this you have to download and install one of the distribution of Hadoop for your computer. We would suggest you to download and install Hortonworks Hadoop VirtualBox distribution which contains all the Hadoop component to get started with it. Check tutorial: Install Hortonworks sandbox on Virtual Box.
After installing Hadoop you should reset the root password so that you can access it from ssh terminal and work easily. Check tutorial: Hortonworks sandbox reset root password.
4. Getting Started with HDFS
The next step is to learn the basic command to work with the HDFS. HDFS stands for Hadoop Distributed File System and this used by Hadoop to store the files on data nodes in a distributed cluster. Here you should learn to upload files, download files, move file, view content of file and delete files command. Check the tutorial: Hadoop shell commands with example for managing files.
5. Getting Started with HBase
The HBase is NoSQL database which runs on the top of Hadoop platform and its written in Java. HBase is columnar database which provides random and fast access to the data.
HBase is used by famous organizations such as Facebook, Adobe, Pinterest, Rocket Fuel and many others.
You should learn to use HBase for storing, querying and updating data into HBase database.
6. Getting Started with Hive
Apache Hive is one of the man project under Hadoop eco-system being developed at Apache Foundation. This project is aimed to provide data warehouse solution on the top of Hadoop HDFS file system. It allows the developers to use SQL like query to create tables, insert data and then summarize data store in Hive table.
You should learn to work with Hive and perform various operations on the Hive table. Here are the operations you can perform on the Hive table:
- Create and Delete tables
- Insert Data
- Update Data
- Search data
- Perform query to get selected data
- Join tables and fetch conditional data
7. Getting Started with Apache Pig
Apache Pig is one of the Hadoop project which provides the functionality of creating and running MapReduce jobs on the HDFS. Pig is an abstraction layer for creating and running MapReduce job on the Hadoop HDFS.
8. Getting started with Apache Mahout
Apache Mahout is machine library which can be used for various machine learning and artificial intelligence work. Learn this framework it you want to make your career as Data Scientist. But these days Apache SparkML is preferred language for Machine learning and AI related projects. So, you should first learn Apache Spark and see if there is requirement of learning Apache Mahout then you can learn this also.
9. Getting started with Apache Spark
Apache Spark is in-memory job processing engine over distributed cluster as a parallel job. This framework is used to perform real-time analytics, data cleansing and machine learning. Big Data and Hadoop developer must learn Apache Spark as its one of the most asked skills in the Hadoop technology.
10. Getting Started with Oozie
Apache Oozie is a tool for managing jobs and workflow in the Hadoop cluster through the scheduling system that comes with the Oozie. It is powerful tool for defining workflow in the Hadoop distributed cluster. Ooze can also handle the failed job and can start from the point it is failed. Developer must learn Oozie for scheduling jobs into the system.
11. Getting started with Zookeeper
Developer should also learn about the Apache Zookeeper, which is a software system for centralized management of configuration information, name providing, distributed synchronization and providing group services in Hadoop cluster.
You should know about the configuration files and the steps to customize Zookeeper.
Read all tutorials of Hadoop at Big Data at Big Data tutorials, technologies, questions and answers.
