Course Overview
1h 04m | 9 Videos | 76275 Views | 
Intermediate HDFS and MapReduce
We are introducing another course on HDFS Architecture and MapReduce for the aspiring students of Data Architecture and to those who are passionate about learning. The intention of this course is to enlighten and envision business better. Anyone who is keen on learning can join us and be an apart of us. Once you finish this course you will get familiar with NameNode, DataNode, Heartbeats, Yarn, etc.
About HDFS Architecture and MapReduce
The purpose of this courseware is to provide in-depth knowledge of HDFS Architecture and MapReduce. To make you more clear about the concept and practical exposure we have project supported study.
This course will definitely help you grasp the basics and advanced study of HDFS and MapReduce. We have a different approach to study. We believe in giving exposure it is important for students because that will help you to have an upper hand on problem-solving approach.
We will help you install Hadoop 2.6.0 on Ubunter Linux.
The courseware is divided into two modules. They are:-
- HDFS Architecture and
- MapReduce
HDFS Architecture content:
HDFS Architecture or Hardtop distributed File System files which are divided into blocks and how these blocks are stored in multiple machines. It is designed to turn the industry servers into a massive storage system that can store unlimited data with multiple copies without any loss of data. This application allows parallel processing happen how it manages to store data in unlimited amount.
To make data reliable it is not dependant on any data protection mechanism instead file contents are replicated. One of the advantages is multiple data transfers.
Name Node files and directories are denoted by anodes. It records modification and access time, etc. It also helps in determining a mapping of blocks to Data Nodes. The application data of HDFS is stored in Data Node. HDFS files consist of many blocks. Each block is replicated and stored in Data Node. It provides read and writes requests for HDFS.
Block is replicated any number of times and stored in HDFS. When a block is added space is allocated and each replica is stored separately in different Data Node. It helps in managing reliability and performance of data storage and transfer. You will learn the practical application of HDFS as well.
HDFS works for the storage and processing of data. By providing a command to interact with HDFS provided by Hadoop.NameNode and DataNode Check the status of clusters and provide access to file system. Then authentication is given by HDFS.
MapReduce Content:
MapReduce as a batch processing tool. Servers can run in parallel to process huge data stored in HDFS. It supports languages for developers, c++, and java. MapReduce is about two algorithms Map and Reduce.
Map converts set of data into another set wherein elements are individually broken into tuples. Reduce takes map data that are tuples and combines it into a smaller set. MapReduce has an advantage that it is its Simple Scalability.
It has three stages namely Mapstage, shuffle and reduce stage.
In Mapstage input data is processed which is stored in the form of a directory in HDFS. Data is processed in chunks. Blend of Mapstage and Reduce stage results in Shuffle. Data is processed further and stored in HDFS.
Hadoop and HDFS Architecture sends tasks to the clusters during a MapReduce Work. It manages all the tasks issued and copies the data between a cluster and a node. Many of the computing work take place on nodes with data that is on local disks, this helps to reduce network traffic. The resultant of the specified task is then transferred back to Hadoop and HDFS Architecture.
MapReduce works on pairs that are the input are viewed as a set of pairs which in turn produces the output in pairs. The value is arranged chronologically and therefore there is a need to implement the Writable.
Writable Comparable is also implemented to help to sort. When applications are written to process bulk data then execution time increases, network traffic increases when data is moved from source to server. MapReduce is used to solve this issue.
This courseware is designed to help you understand how these configurations allow better cluster utilization that will enable priority workload and group-based policies across the business.
It will help you understand how Hadoop ecosystem works? Once you gain indepth knowledge of basic, which will include Hadoop and HDFS YARN, Hadoop and HDFS Ecosystem, and Hadoop and HDFS basics.
Research provides evidence that Companies like Google and Facebook use Hadoop and HDFS Architecture.
Advantage of using Hadoop and HDFS Architecture:
- Hadoop and HDFS Architecture being highly scalable can store and transfer huge data to multiple servers operating in parallel. This makes the business process easier.
- Hadoop and HDFS require less cost to store bulk data or huge data for future reference.
- Hadoop and HDFS Architecture adds value to raw data by processing and generating value to it.
- Hadoop and HDFS Architecture can be used as data warehousing, analysis, fraud detection and many more multiple usages.
- Unique data storage is an advantage since it is based on mapping data when it is located in a cluster.
- Processing of structured or unstructured data in Hadoop and HDFS Architecture happens on the same server, but within a minute the data is processed.
- Since the data is replicated to nodes in a cluster, if there is any failure the replicated data is available, this again an advantage.
Contents of Study for HDFS Architecture are:
- Introduction of HDFS
- Architecture of HDFS
- Edits viewer
- Image viewers
- Blocks
- Name Node
- Data Node
- Data Nodes Functions and Heartbeat
- Data Node and Secondary Name Node
- Data Replication in HDFS
- Read and Write mechanism in HDFS
- loading data in HDFS
- Replications and Rack Awareness
Contents of study for MapReduce are :
- Yarn
- Algorithms
- Inputs and outputs
- Flow charts of data flow through Map Resource manager,
- Node manager
- Application Master
- Architect – MapReduce
- Partitioners and Combiners
- Installation of Hadoop 2.6.0 on Ubuntu Linux OS and
- Project in MapReduce
HDFS architecture or Hadoop Certification: Market overview
According to the latest survey reports Hadoop and HDFS certification is an add-on in the profile of job seekers. This certification will place them on the top list of employers. The HDFS or Hadoop will help trained and certified people to get easy access in Hadoop technology.
Employers want certified people who can handle the data efficiently. Many Big companies have invested in Hadoop and HDFS certification they are Cloudera, IBM and many more which will give rise to job openings in a data analyst, operators, developers, administration.
Demand for Hadoop certified people is increasing by leaps and bounds.
- Survey reports by Comp TIA show that Hadoop certified people are rated extremely high by IT managers
- The salary of expertise people is somewhere between $124,000 a year,
- Openings for Hadoop and HDFS certified are much more as compared to other certifications.
It is expected that by the end of this year there will be a surge in IT Industries with a higher demand in professional system operators, developers, etc. This certification will help people master the management of data and tools and techniques required to cater the need.
The target audience is students, professionals, analysts, data management accompanied by an interest in learning more about data management. Hadoop and HDFS certification is in demand with such audience.
Organisations want people are acquainted with handling huge data and filter from these data the one that is needed and important to work. Certification of HDFS or Hadoop speaks volumes about the employee and people get hired easily or promoted to a higher level in a hierarchy.
IT certification 2016 shows the huge demand among people for HDFS or Hadoop certification. Chances of getting hired are greater with this certification in their profile.
A recent survey by Spice work showed that there are industries who will pay for their employees to get them HDFS or Hadoop certified because they believe that HDFS or Hadoop Certification will get 80% of boost career-wise.
HDFS and MapReduce Career objective:
- This courseware will help you gain a thorough knowledge of HDFS Architecture and MapReduce Architecture
- You can implement and develop HDFS according to business need
- A project-based study will help you understand the real-life situations properly
- Courseware is prepared with an intention to help you gain apt knowledge of HDFS and help you learn the influx of data and how to filter data
- You will get professionally certified and expertise in HDFS or Hadoop
- Another feature is the installation of Hadoop on your Laptop.
- You will exposure and practical learning which help you become more flexible in dealing complex situations.
HDFS and MapReduce Target Audience:
The target audience for HDFS Architecture and MapReduce Architecture includes the following people who are:
- Looking for a career as a data analyst, developers,
- Systems Administrators
- Professionals who are looking for a growth in their career
- Program Managers
- Engineering Managers and
- Enthusiastic people who have a burning desire to learn
HDFS and MapReduce Pre – Requisites:
- Conceptual knowledge of computers
- Analytics
- Linux
- Knowledge about Java will help but not required
HDFS and MapReduce Faqs:
- What are the career benefits of this course?
Apt knowledge about HDFS will help to boost careers. Top companies have invested in data management so the Hadoop certified professional will get first preference job wise as data analysts. And it is just like a feather in your cap. Apart from getting first preference in employers list, you gain expertise on tools and techniques of Hadoop and HDFS technology. The hiring rate is higher if you are certified in HDFS or Hadoop technology
- Why is this course considered more important?
When you are Hadoop certified it means you are more inclined towards data analysis, developer. And also accompanied with thorough knowledge of the subject will increase your chances of growth in your career. This course ware helps you gain a basic understanding of Hadoop and Big Data. You can easily become an expert by getting an advanced level certification. Many companies like LinkedIn, Yahoo and many more use this technology.
- Whom do I contact in case of further clarification or any doubts?
Our 27*7 support team is always happy to help you in case of any clarification and doubt. You can call us or chat with any agent of ours or request a call back to solve your doubts or further clarification of your doubt.
HDFS and MapReduce Course Testimonials:
Navjot Singh:
Ideal course for those who want to learn basics of HDFS architecture. This is an easy to understand course. Excellent content and curriculum. Will refer to my friends who want to learn basics of Hadoop or Big Data
Radhika:
Topics can be easily followed because of the easy structure flow. Good introductory course. Information about tools is given and explained its uses as well. I was happy with the course.
Raman:
Hadoop training course like this is good for beginners and professionals as well. Course content is in a flow, lucrative language makes itself explanatory and easily understood. I want to join other courses of eduCAB. I have recommended few of these courses to my friends and relatives.
Satya:
I’m happy with the easy and fluent language of this training program. Many of my friends have joined and benefited from this training. In future I’m also planning to join some course. I liked the explanation given in modules. They are self explanatory and don’t need help from any one.
Ranjan:
This training of HDFS Architecture and MapReduce had helped with the basic knowledge.The course is very concise and clear about the concepts of MapReduce framework. I am thankful to my friend who recommended me to join this practical programme when I was in dilemma about my future. This certification is really beneficial career wise. I wish to join some more advanced course.
Career benefits of this HDFS and MapReduce Training:
- Hadoop skills are in demand so this training will definitely help you in an upward trend in your organisation
- This training as a beginner or a professional will improve your job prospects
- This training will definitely add value to your profile
- Certification is helpful in mastering tools of HDFS Architecture or Hadoop
- Training will make you eligible for advanced study In HDFS Architecture
