For those who want to add Hadoop to their skillset, or hone the skills they already have, look to free online Hadoop Tutorials to jumpstart your learning.
Hadoop, an Apache open source software framework for storing and crunching big data sets across clusters of machines, has hit the big time. Markets and Markets forecasted in January 2017 that the Hadoop market could grow from $6.71 billion in 2016 to more than $40 billion by 2021. (For perspective, that same market expanded from $1.5 billion to $4 billion from 2012 through 2014.) Growth on that scale precipitates an urgent need for many more able-bodied IT pros to develop, manage and administer all those Hadoop implementations.
Tutorial Chat, the leading FREE online tutorial offers FREE guide and training materials for learning Hadoop. They have a 24 x 7 customer support to help you with all the queries/ problems you face during your learning. Apart from these, you will also have lifetime access to the course and work on projects.
I wish to share my own experience here before diving to the topic. While I wish to learn Hadoop, I subscribed Tutorial Chat. Each and every day they post Hadoop articles, beginners guide etc. with full information and also they are available to clear our doubts via the comments section.
It provides you hands-on training with Hadoop, Hive, Pig, and R practice on Real-World Projects. This one I took and this it is geared to folks just getting started with Big Data.
Similarly, if you want to learn Big Data Hadoop and desire a deep dive into real-world usage of Hadoop and related APIs and tools then there’s a Hadoop Developer Training Course
It would help you master all the relevant details of the Hadoop APIs and complete rigorous and challenging assignments in the context of a data aggregator case study.
For learning Big Data you just need to follow a right direction. By following the right direction you can easily start your career in this booming technology.
First, I will say that you took a right decision because today is the generation of Big Data. World’s 50% of data is already shifted in Hadoop and it is estimated that at the end of 2017 the percentage reach up to 75%. Now, you can estimate the Job vacancies and career opportunities in Big Data Hadoop. Companies are hunting for good candidates and there is a huge shortage of good Big Data Hadoop candidates.
Today everyone is learning Big Data Hadoop and you have to be stand out from them. Work Hard and also work smartly because in today’s world there is huge competition, so you have to work smart with hard work.
So, start learning from the very beginning. For learning Hadoop Big Data you should go through the sets of free blogs and videos. I am referring some good links which I am familiar with. Let’s start with Big data.
Goals for this Hadoop Tutorials Includes:
- Understand the scope of problems applicable to Hadoop
- Understand how Hadoop addresses these problems differently from other distributed systems.
Stay tuned with Tutorial Chat to learn more about the below-mentioned things!
You should go through the set of Big Data & Hadoop blog and videos first to understand what Big Data is & how Hadoop came into the picture. Then you should understand how Hadoop architecture works in respect of HDFS, YARN & MapReduce.
Further moving on you should install Hadoop on your system so that you can start working with Hadoop. This will help you in understanding the practical aspects in detail.
Further moving on take a deep dive into Hadoop Ecosystem and learn various tools inside Hadoop Ecosystem with their functionalities. So, that you will learn how to create a tailored solution according to your requirements.
Let us understand in brief:
What is Big Data?
Big Data is a term used for a collection of data sets that are large and complex, which is difficult to store and process using available database management tools or traditional data processing applications. The challenge includes capturing, curating, storing, searching, sharing, transferring, analyzing and visualization of this data.
It is characterized by 5 V’s.
VOLUME: Volume refers to the ‘amount of data’, which is growing day by day at a very fast pace.
VELOCITY: Velocity is defined as the pace at which different sources generate the data every day. This flow of data is massive and continuous.
VARIETY: As there are many sources which are contributing to Big Data, the type of data they are generating is different. It can be structured, semi-structured or unstructured.
VALUE: It is all well and good to have access to big data but unless we can turn it into value it is useless. Find insights in the data and make benefit out of it.
VERACITY: Veracity refers to the data in doubt or uncertainty of data available due to data inconsistency and incompleteness.
The main components of HDFS are NameNode and DataNode.
It is the master daemon that maintains
and manages the DataNodes (slave nodes). It records the metadata of all the files stored in the cluster, e.g. location of blocks stored, the size of the files, permissions, hierarchy, etc. It records each and every change that takes place to the file system metadata.
For example, if a file is deleted in HDFS, the NameNode will immediately record this in the EditLog. It regularly receives a Heartbeat and a block report from all the DataNodes in the cluster to ensure that the DataNodes are live. It keeps a record of all the blocks in HDFS and in which nodes these blocks are stored.
These are slave daemons which run on each slave machine. The actual data is stored on DataNodes. They are responsible for serving read and write requests from the clients. They are also responsible for creating blocks, deleting blocks and replicating the same based on the decisions taken by the NameNode.
For processing, we use YARN(Yet Another Resource Negotiator). The components of YARN are ResourceManager and NodeManager.
It is a cluster level (one for each cluster) component and runs on the master machine. It manages resources and schedule applications running on top of YARN.
It is a node level component (one on each node) and runs on each slave machine. It is responsible for managing containers and monitoring resource utilization in each container. It also keeps track of node health and log management. It continuously communicates with ResourceManager to remain up-to-date.
So, you can perform parallel processing on HDFS using MapReduce.
It is the core component of processing in a Hadoop Ecosystem as it provides the logic of processing. In other words, MapReduce is a software framework which helps in writing applications that process large data sets using distributed and parallel algorithms inside Hadoop environment. In a MapReduce program, Map() and Reduce() are two functions.The Map function performs actions like filtering, grouping, and sorting.While Reduce function aggregates and summarizes the result produced by map function.The result generated by the Map function is a key-value pair (K, V) which acts as the input for Reduce function.
You should go through an oriented series of Hadoop Tutorial videos and blogs to learn Big Data & Hadoop with clear understanding. I would suggest you to first understand Big Data & opportunities hidden in Big Data. So then moving on you would figure out the problems associated in encasing Big Data opportunities & how Hadoop solved those problems.
Read Hadoop Architecture in Tutorial Chat to Learn More
Then further moving on you should understand What is Hadoop to learn Hadoop architecture in terms of HDFS & YARN and their architectures. Further moving on you can go through MapReduce to learn how it carries parallel processing. Go through the below-given blog links:
In no particular order, here are over a dozen terrific free sources for Hadoop training.
Big Data University
Big Data University offers more than 50 courses on Hadoop, HBase, Pig, big data analytics, SQL, IBM BLU, DB2 and more, all available at your own pace. Most courses are in English, but some are in Japanese, Spanish, Portuguese, Russian and Polish.
Cloudera Essentials For Apache Hadoop
Cloudera has a Cloudera Essentials for Apache Hadoop online video course that’s distributed chapter by chapter, as well as Hadoop training aimed at administrators, data analysts, data scientists, and developers. Your next step could be taking the three-lesson Introduction to Hadoop and MapReducecourse, offered through Udacity. Cloudera also has a free live Hadoop demo, called Cloudera Live, to help you learn that environment.
Dispensing with glitz and glam, coreservlets.com provides a series of tutorials on developing big data applications with Hadoop, delivered from a straight-up text-based interface. Each tutorial section lets you follow along using PDFs and/or slideshares, but you also get downloadable virtual machines in some instances as well as exercises (with solutions).
Coursera has a large library of courses that are offered in partnership with several leading universities, such as UC San Diego, Stanford, Duke and much more. The company’s policy states that you can access video lectures and certain non-graded assignments for free in all courses. These previews give you the opportunity to decide if you want to purchase a course (priced between $29 and $99) and perhaps keep going to complete a certificate.
Similar to Coursera, edX offers courses from well-known universities, as well as high-tech firms and other contributors. On the main web page, enter “Hadoop” into the search field to see what’s currently available. You can audit an edX course for free, and work on all assignments and exams, but only paid participants receive a certificate of completion.
DeZyre lets you learn about big data and Hadoop from industry experts, get a mentor and complete projects… for a fee. But the company’s free tutorials are available to anyone, anytime. Browse the lengthy list of tutorials on the DeZyre Tutorials page and click on anything that sparks your interest — no signup needed.
Hortonworks also has a lot of good for-a-fee courses as well as free Hadoop training and tutorials. For most tutorials, you’ll need to download and install the Hortonworks Sandbox, and the company recommends other tutorials as prerequisites to ensure you’re ready to learn most efficiently.
IBM developerWorks serves up free tutorials and tools for big data analytics, cloud computing, and other high-tech categories, based on IBM technologies. For example, Choose IBM Open Platform for your Hadoop and Spark projects explores this Apache Hadoop and Apache Spark distribution, describing the purpose or function of each component, such as Spark, MapReduce, Sqoop and more. Although it’s a little long in the tooth, Open Source Big Data for the Impatient is a solid tutorial that walks you through the fundamentals of big data and Hadoop and has you download a Hadoop image (Cloudera is recommended) to work through examples of Hadoop, Hive, Pig, Oozie and Sqoop.
MapR is the provider of a leading Apache Hadoop distribution. The company’s on-demand Hadoop training courses include video lessons, labs, hands-on exercises and more, and can lead to certification as a Hadoop Cluster Administrator, Hadoop Data Analyst or Hadoop Developer. MapR currently offers Apache Hadoop Essentials, five different Cluster Administration courses, Developing Hadoop Applications and many more on-demand courses that cover HBase, MapR Streams, Apache Spark, Apache Drill and Apache Hive.
Udacity is well known for its catalog of training courses on data science, web development, software engineering and mobile operating systems — built by Silicon Valley heavy-hitters like Facebook and Twitter, Cadence and much more. Udacity offers free courses and course materials, but you must enroll in a paid program to earn a Nanodegree credential. To see all free courses at a glance, go to the Courses and Nanodegree Programs page and check the Free Courses checkbox.
Udemy offers more than 40,000 free and for-a-fee courses on just about everything under the sun. When you get to the home page, enter “Hadoop free” in the search box to see what’s currently being offered. You should get several hits on courses that range from 5 to more than 40 lectures each, aimed mainly at the beginner to intermediate levels.
Microsoft Virtual Academy
Microsoft Virtual Academy offers a big data analytics video training course that focuses on HDInsight (which is Microsoft’s managed Hadoop distribution that runs on the Azure cloud) and using Hadoop on Azure. The free video course covers Hive, Tez, Pig, Sqoop, Oozie and Mahout, and offers additional resources and next steps.
As you would expect, YouTube has a long list of Hadoop training videos. Search for “Hadoop” on the main page, noodle through the results and pick some videos that look right for you.
Hadoop Users LinkedIn Group
There’s also great information on Hadoop training resources exchanged by members of the Hadoop Users LinkedIn group.
So, let’s start learning in detail:
Why Learn Big Data?
To get an answer for Why You should learn Big Data? Let’s start with what industry leaders say about Big Data:
- Gartner – Big Data is the new Oil.
- IDC – Big Data market will be growing 7 times faster than the overall IT market.
- IBM – Big data is not just a technology – it’s a Business Strategy for capitalizing on information resources.
- IBM – Big Data is the biggest buzz word because technology makes it possible to analyze all available data.
- McKinsey – There will be a shortage of 1500000 Big Data professionals by the end of 2018.
Industries today are searching new and better ways to maintain their position and be prepared for the future. According to experts, Big Data analytics provides leaders a path to capture insights and ideas to stay ahead in the tough competition.
According to Gartner:
Big data is huge-volume, fast-velocity, and different variety information assets that demand innovative platform for enhanced insights and decision making.
A Revolution, authors explain it as:
Big Data is a way to solve all the unsolved problems related to data management and handling, an earlier industry was used to live with such problems. With Big data analytics, you can unlock hidden patterns and know the 360-degree view of customers and better understand their needs
You can learn more about Hadoop via Tutorial Chat
Learn and master the most popular big data technologies in this comprehensive course, taught by a former engineer and senior manager at Amazon and IMDb.
Go way beyond Hadoop itself, and dive into all sorts of distributed systems you may need to integrate with.
- Install and work with a real Hadoop installation right on your desktop with Hortonworks and the Ambari UI
- Manage big data on a cluster with HDFS and MapReduce
- Write programs to analyze data on Hadoop with Pig and Spark
- Store and query your data with Sqoop, Hive, MySQL, HBase, Cassandra, MongoDB, Drill, Phoenix, and Presto
- Design real-world systems using the Hadoop ecosystem
- Learn how your cluster is managed with YARN, Mesos, Zookeeper, Oozie, Zeppelin, and Hue
- Handle streaming data in real time with Kafka, Flume, Spark Streaming, Flink, and Storm
Understanding Hadoop is a highly valuable skill for anyone working at companies with large amounts of data.
Almost every large company you might want to work at uses Hadoop in some way, including Amazon, Ebay, Facebook, Google, LinkedIn, IBM, Spotify, Twitter, and Yahoo! And it’s not just technology companies that need Hadoop; even the New York Times uses Hadoop for processing images.
This course is comprehensive, covering all aspects of Hadoop blogs and it’s filled with hands-on activities and exercises, so you get some real experience in using Hadoop – it’s not just theory.
You’ll find a range of activities in this course for people at every level. If you’re a project manager who just wants to learn the buzzwords, there are web UI’s for many of the activities in the course that require no programming knowledge. If you’re comfortable with command lines, we’ll show you how to work with them too. And if you’re a programmer, I’ll challenge you with writing real scripts on a Hadoop system using Scala, Pig Latin, and Python.
You’ll walk away from this course with a real, deep understanding of Hadoop and its associated distributed systems, and you can apply Hadoop to real-world problems.
What career path should I take to become a Hadoop Developer?
According to a Forbes report of 2015, about 90% of global organizations report medium to high levels of investment in big data analytics, and about a third call their investments “very significant.” Most importantly, about two-thirds of respondents report that big data and analytics initiatives have had a significant, measurable impact on revenues.
Hadoop skills are in demand – this is an undeniable fact! Hence, there is an urgent need for IT professionals to keep themselves in trend with Hadoop and Big Data technologies.
Apache Hadoop provides you with means to ramp up your career and gives you the following advantages:
- Accelerated career growth.
- Increased pay package due to Hadoop skill.
It is no rocket science that a career in Hadoop is very rewarding. Do want to have an accelerated and rewarding career in Hadoop? Click below to kick start your career in Hadoop.
Looking at the Big Data market forecast, it looks promising and the upward trend will keep progressing with time. Hence, the job trend or Market is not a short-lived phenomenon as Big Data and its technologies are here to stay. Hadoop has the potential to improve job prospects whether you are a fresher or an experienced professional.
A research report by Avendus Capital estimates that the IT market for big data in India is hovering around $1.15 billion as 2015 comes to an end. This contributed to one-fifth of India’s KPO market worth $5.6 billion. Also, The Hindu predicts that by end of 2018, India alone will face a shortage of close to two lakh Data Scientists. This presents a tremendous career and growth opportunity.
This skill gap in Big Data can be bridged through comprehensive learning of Apache Hadoop that enables professionals and freshers alike, to add the valuable Big Data skills to their profile.
Hadoop Career Path Explained
Having worked your way up on the IT totem pole in the same job role, you have decided this is the best to find new horizons, new environment and a new gig in the big data domain. Starting a new career is exciting but it is not easy as a lot of analysis goes into choosing a new career path. Let’s help you out with some detailed analysis on the career path taken by Hadoop developers so you can easily decide on the career path you should follow to become a Hadoop developer.
“Hadoop Developer Careers-Analysis”-
“48.48% of Hadoop Developers are graduates or postgraduates from a non-computer background like Statistics, Physics, Electronics, Material Processing, Mathematics, Business Analytics, etc.”
“Hadoop Developer Careers-Inference”-
A career in Hadoop can be pursued by individuals from any educational background as almost all industry sectors are hiring big data Hadoop professionals.
“Hadoop Developer Careers –Analysis”-
60% of the professionals have only 0-3years of experience as Hadoopers.
“Hadoop Developer Careers-Inference”-
Companies do not have a bias against people with years of experience when hiring for Hadoop job roles. This is mainly due to the shortage of Hadoop talent and increased demand in the market. Newbies or professionals with even 1 or 2 years of experience can become Hadoop Developers. Employers judge candidates based on the knowledge of Hadoop and willingness to work/learn.
“Hadoop developer careers-Analysis”-
67% of Hadoop Developers are from Java programming background.
“Hadoop developer careers -Inference”-
Hadoop is written in Java but that does not imply people need to have in-depth knowledge of advanced Java. Our career counselors get this question very often – “How much Java is required to learn Hadoop?” Only Java basics are essential to learn Hadoop and anybody with core Java knowledge can master Hadoop skills.
Industry statistics reports reveal that professionals change careers at least 3 to 4 times in their life and on an average hold 7 jobs i.e. approximately 50% of the people hold more than 7 jobs. Whether you are a cubicle loyalist with a wandering eye or a programming geek or an independent contractor, the question on how best to steer your career is always a matter of concern. If you are a techie planning to switch careers then, based on the demand in the market – Hadoop is a must-have skill on your resume to future-proof your career.
Becoming a Hadoop Developer – Career Outlook
Dice survey revealed that 9 out of 10 high paid IT jobs to require big data skills.
A McKinsey Research Report on Big Data highlights that by end of 2018 the demand for analytics professionals in the US is expected to be 60% higher than the anticipated supply.
According to the Economist, the big data market is expected to surpass $100 billion with increasing number of companies struggling to analyze the data from various online data sources.
A recent article on Economic Times highlighted –“If you are a programmer who knows what Hadoop is, you are a hot commodity on the job circuit.” Professionals looking to cash in on a healthy hiring market should consider building a career in Hadoop as IT companies would need 2.5 million more big data professionals by end of 2015 as acknowledged by market analysts and industry research reports. Job opportunities for Hadoop developers are expected to grow much faster when compared to the average for all other occupations.
According to job listing statistics from Dice, Big Data is expanding its reach into business in a big way with increased job opportunities. Here is an insight on the available big data jobs as listed on Dice –
- Boston represents 7.1% of all the available big data jobs.
- Los Angeles represents 4% of all the available big data jobs.
- Seattle represents 6% of all the available big data jobs
- New York represents 13.1% of all the available big data jobs.
- Washington DC represents 11.9% of all the available big data jobs.
- Philadelphia represents 2.9% of all the available big data jobs.
- Dallas represents 3.2% of all the available big data jobs.
- Atlanta represents 3.3% of all the available big data jobs.
- Chicago represents 3.4% of all the available big data jobs.
- San Francisco Bay Area (Silicon Valley) accounts for a total of 23.6% big data-related jobs.
The high paying job in big data can be grabbed through comprehensive learning of Hadoop that helps professionals and beginners add big data skills to their career profile. The Big Data Hadoop market is in its blossoming phase and it is difficult to find proper guidance.
At DeZyre, our Career Counsellors often get this question –“What career path should I take to become a Hadoop Developer?”
If you are among those individuals who understand that the tiny elephant Hadoop, is growing and will become big in future but don’t know how to start a career in Hadoop, then we are here to help. There is no well-laid out path that you can follow to enter the field of Hadoop but DeZyre experts have simplified this.
To answer the question, DeZyre experts did some research on 100 Hadoop profiles across the world.
DeZyre experts analyzed profiles of 76 Hadoop Developers, 10 Hadoop Administrators, and 14 Hadoop Architects.
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