Big Data Hadoop Key Highlights
Overview of Big Data Hadoop Training in Chennai
Big Data Hadoop Certification helps to use Hadoop from basic to sophisticated approaches taught by working pros. You can master ideas at an expert level in a practical setting with our Hadoop course in Chennai.
Why Big Data?
A collection of data set that is very complex and large is very difficult to process and store using traditional data processing applications (RDBMS) or database management tools. It has many challenging aspects, such as the visualization of data, analyzing, transferring, sharing, searching, storing, curating, and capturing.
Big Data is a phrase or methodology to resolve large data processing and storage problems which are not resolved by Traditional RDBMS Systems.
What is Hadoop Eco-Systems?
Apache Hadoop is a tool to achieve Big Data methodology by distributed storage and processing.
The software tools which can be integrated with the Hadoop software stack are known as Hadoop Eco-Systems. Familiar Eco-Systems are Sqoop, Hive, Kafka, Oozie, Hbase, etc.
Real-time industrial usage of Hadoop
Hadoop is used by AOL for behavior analysis, ETL-style processing, and statistics production. Hadoop is used by eBay for research and search engine optimization.
Hadoop is used by InMobi for a variety of analytics, data science, and machine learning applications with over 700 nodes and 16800 cores.
Why learn Big Data Hadoop Course?
After finishing the BTree Hadoop certification program, you’ll be prepared to apply to some of the world’s most prestigious MNCs. Just buy something for less than its worth.
Pre-Requisites for learning Big Data Hadoop Course
Learning Hadoop is a must, as it is becoming the de facto standard for big data processing. Although there are no pre-requisites for taking the Hadoop course, having some familiarity with the following concepts like programming skills, SQL Knowledge, and Linux help you get the most out of the course.
The term “big data” refers to the collection of data generated by a wide range of applications and hardware like Black Box, Social Media, Stock Exchange, Power Grid, Transport, and Search Engine. Various Hadoop applications include stream processing, fraud detection, and prevention, content management, risk management, and more fields using Hadoop.
Why take up big data Hadoop training in Chennai for the BTree system
One of the reasons for learning Hadoop is the fat paycheck. Companies pay exceptionally high wages to individuals who have expertise in Hadoop since there is a talent gap in this area. 364000 data experts are expected to be needed in the United States by 2020, IBM says
Based on payscale.com, the annual income for Hadoop experts ranges from $93K to $127K. The average salary for the other job posts is 95% more than this one.
BTree system provides 60+ IT Training courses in more than 10+ branches in Chennai with 15 years of experience at the level of training and industry expert facilities.
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Big Data Hadoop Career Transition
60%
Avg Salary Hike
40 LPA
Highest Salary
500+
Career Transitions
300+
Hiring Partners
Big Data Hadoop Course Skills Covered
Apache Hadoop
Apache Hadoop Map Reduce
Apache Sqoop
Apache Pig
Apache Hive
Apache Kafka
Impala
Spark Streaming
Big Data Hadoop Course Tools Covered
Big Data Hadoop Course Fees
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16
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08:00 PM TO 11:00 PM IST (GMT +5:30)
32
Sep
SAT - SUN
08:00 PM TO 11:00 PM IST (GMT +5:30)
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Curriculum for Big Data Hadoop Course in Chennai
Starting Hadoop
- Setting up single-node Hadoop Cluster (Pseudo mode)
- Understanding Hadoop configuration files
- Hadoop Components- HDFS, MapReduce
- Overview of Hadoop Processes
- Overview of Hadoop Distributed File System
- The building blocks of Hadoop
- Hands-On Exercise: Using HDFS commands
Introduction to Hadoop
- What is Hadoop?
- History of Hadoop?
- How Hadoop name was given?
- Problems with Traditional Large-Scale Systems and Need for Hadoop.
- Understanding Hadoop Architecture.
- Fundamental of HDFS (Blocks, Name Node, Data Node,Secondary Name Node).
- Rack Awareness
- Read/Write from HDFS
- HDFS Federation and High Availability
Introduction to Big Data
- What is Big Data
- Examples of Big Data
- Reasons for Big Data Generation
- Why Big Data deserves your attention
- Use cases of Big Data
- Different options to analyze Big Data
Mapreduce-1(MR V1)
- Understanding Map Reduce
- Job Tracker and Task Tracker
- The basics of Map Reduce
- Data Flow of Map Reduce
- Hadoop Writable, Comparable & comparison with Java data types
- Creation of local files and directories
- Creation of HDFS files and directories
- Map Function & Reduce Function
- How Map Reduce Works
- Anatomy of Map Reduce Job
- Submission & Initialization of Map Reduce Job
- Monitoring & Progress of Map Reduce Job
- Understand the Difference Between Block and Input Split
- Role of Record Reader, Shuffler and Sorter
- File Input Formats
- Getting Started with Eclipse IDE
- Set up Eclipse Development Environment
- Create Map Reduce Projects
- Configure Hadoop API for Eclipse IDE
- Differences with Hadoop Old and New APIs
- The life cycle of the Job
- Identity Reducer
- Map Reduce program flow with word count
- Combiner & Partitioner, Custom Partitioner, with example
- Joining Multiple datasets in Map Reduce
- Map Side, Reduce Side joins with examples
- Distributed Cache with practical examples
- Stragglers & Speculative execution
- Schedulers (FIFO Scheduler, FAIR Scheduler, CAPACITY Scheduler)
Mapreduce-2(YARN)
- Limitations of Current Architecture
- YARN Architecture
- Application Master, Node Manager & Resource Manager
- Writing a Map Reduce using YARN
Apache Hive
- Introduction to Apache Hive
- The architecture of Hive
- Installing Hive
- Hive data types
- Exploring Hive metastore tables
- Types of Tables in Hive
- Partitions (Static & Dynamic)
- Buckets & Sampling
- Indexes & Views
- Developing hive scripts
- Parameter Substitution
- Difference between order by & sort
- Difference between Cluster by & distribute
- File Input formats (Text file, Sequence, Parquet)
- Optimization Techniques in HIVE
- Creating UDFs
- Hands-On Exercise
- Assignment on HIVE
Apache Pig
- Introduction to Apache Pig
- Building Blocks
- Installing Pig
- Different modes in PIG
- Working with various PIG Commands
- Developing PIG scripts
- Parameter Substitution
- Command-line arguments
- Passing parameters in param file
- Joins
- Nested queries
- Specialized joins in PIG
- HCatalog
- Working with unstructured data
- Working with Semi-structured data like XML JSON
- Optimization techniques
- Creating UDFs
- Hands-On Exercise
- Assignment on PIG
Sqoop
- Introduction to SQOOP & Architecture
- Import data from RDBMS to HDFS
- Import data from RDBMS to HDFS
- Import data from RDBMS to HDFS
- Importing Data from RDBMS to HIVE
- Exporting data from HIVE to RDBMS
- Handling incremental loads using sqoop
- Hands-on exercise
Apache HBase
- Introduction to HBase
- Installation of HBase
- Exploring HBASE Master & Region server
- Exploring Zookeeper
- CRUD Operation of HBase with Examples
- HIVE integration with HBASE (HBASE-Managed hive tables)
- Hands-on exercise on HBASE
Apache Oozie
- What is Oozie & Why Oozie.
- Features of Oozie.
- Control Nodes & Action Nodes.
- Oozie Workflow Process flow.
- Oozie Parameterization.
- Oozie Command Line examples – Developer.
- Oozie Web Console.
- Hands on exercise on OOZIE.
“Accelerate Your Career Growth: Empowering You to Reach New Heights in Big Data Hadoop Course”
Big Data HadoopTraining Options
Big Data Hadoop Classroom Training
50+ hours of Live Classroom Training Real-Time trainer assistance Cutting-Edge on Big Data Hadoop Course Tools Non-Crowded training batches Work on real-time projects Flexible timings for sessions
Big Data Hadoop Online Training
50+ Hours of online Big Data Hadoop Training 1:1 personalised assistance Practical knowledge Chat and discussion panel for assistance Work on live projects with virtual assistance 24/7 support through email, chat, and social media.
Big Data Hadoop Certification
BTree system is a globally recognized training institute where freshers and corporate trainees complete theoretical and practical sessions.
The certification indicates that the candidate has acquired the necessary skills to work as a Big Data Hadoop Developer after acquiring real-time project experience.
With this certificate along with your resume, you can increase the likelihood of being selected for an interview, and it also opens the door to many job opportunities.
Knowledge Hub with Additional Information of Big Data Hadoop Training
Hadoop Tester roles and responsibilities
• The role of a Hadoop Tester has grown in importance as Hadoop networks continue to grow in size and complexity.
• This raises fresh questions about the viability and security of the system, as well as the need to ensure that it runs without glitches.
• Hadoop Testers are in charge of finding and fixing problems with Hadoop applications as soon as they arise, ideally before they become life-threatening.
Hadoop Tester, you can expect the following responsibilities
• Use both positive and negative test scenarios in your research. Finding, documenting, and reporting issues with bugs and performance. Verify that MapReduce jobs are performing at their best.
• Test the robustness of the Hadoop scripts, such as HiveQL and Pig Latin, that make up the system.
• Be able to perform MapReduce testing with ease thanks to your extensive grasp of Java
• Recognize and utilize testing frameworks such as MRUnit and JUnit
• Make sure that you have a thorough understanding of Apache Pig and Hive
• Use the Selenium Testing Automation tool to its fullest potential and become an expert. In the event of a breakdown, devise a plan of action
Hadoop Administration Roles and Responsibilities
• The Hadoop Administrator also plays a very important part because he or she is the one who is accountable for ensuring that the Hadoop framework operates without any hiccups or interruptions.
• This job profile contains duties and responsibilities that are very similar to those of a System Administrator. It is essential to have an in-depth understanding of both the hardware environment and the Hadoop architecture.
Roles and responsibilities of Hadoop Developer
Coding is a key component of a Hadoop Developer’s profession. They primarily work as software developers in the Big Data Hadoop industry. They can create software design concepts.
Hadoop Developer, you can expect the following responsibilities
• Data analysis using Hadoop applications that I designed and coded.
• Developing frameworks for data processing.
• Retrieving data and separating it into several data groups
• Scripts are tested and outcomes are analyzed.
• Scripts are tested and outcomes are analyzed.
• Ensuring the safety of business information.
• Developing software to track data.
• Creating documentation for Hadoop development.
Big Data Hadoop career opportunities
• A successful Hadoop career can be built on a solid foundation of knowledge of Hadoop’s concepts. As more firms use Big Data, the demand for Hadoop workers who can comprehend and utilize data increases. Hadoop is a field with several chances for career development and advancement. In India, Hadoop Developer salaries range between 3.8 Lakhs and 10.5 Lakhs, with an average annual salary of 5.5 Lakhs.
• The estimated salary is based on 1,700 salaries submitted by Hadoop Developers. The median salary for Big Data / Hadoop Developers in the United States is $140,000, with a range between $73,445 and $140,000. The middle 50% of Big Data / Hadoop Developers earn $73,445, while the top 75% earn $168,000.
Scope of Hadoop in the Future
• Especially for large corporations, Hadoop is a technology of the near future. A growing amount of information is expected as a result. The need for this software is expected to rise at the same time.
• Only a small number of software professionals are skilled in MapReduce, the computational model used to create Hadoop applications A shortage of experienced engineers is also expected in the Analytics section. Despite this, the benefits that Hadoop provides continue to broaden its commercial reach.
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FAQ of Big Data Hadoop Course
FAQ for Big Data Training
• Well-equipped classrooms
• 100% Hands-on training skills
• Patterned and designed by a leading expert’s course curriculum
• Supports Trainers Flexible batch timings
• Industry Exposure
• Reasonable course Fee and Placement support
How can beginners learn Big Data and Hadoop?
Hadoop is one of the leading technological frameworks that is widely used in organisations to leverage big data. It is extremely difficult to take your first step toward big data.
As a result, we believe it’s critical to learn the fundamentals of technology before pursuing certification. Btree Systems to help you understand the Hadoop ecosystem and learn the fundamentals of Hadoop. Our comprehensive Big Data Hadoop certification training course get you up and running with big data.
Can I still learn Hadoop if I don't have any programming experience but have a fundamental understanding of it?
Yes, you can learn Hadoop without having a background in software. We offer Java and Linux courses to help you brush up on your programming skills. This assist you in learning Hadoop technologies more effectively and quickly.
What if I miss a session?
We BTree Systems supports the students with 100% secured recordings of Data Science with Python master course sessions. This is in order to be used by students for any revising or when they miss the session. Add-on, it can be used lifetime.
What would be my level of proficiency in the subject after the course completion?
• Exceptionally qualified instructors guide students through the Big Data Hadoop course.
• Students are independently ready to access the Real-time or current industry needs with the globally recognized trainers’ Big Data Hadoop certification.
• Students were gain both practical & theoretical aspects.
What can I accomplish from this Big data Hadoop Training?
• Students are impart the best IT required skills to elevate their careers
• In-depth knowledge of concepts of HDFS and MapReduce
• Accomplish a stable understanding of Apache Big Data Hadoop and its relates
• Boost up to develop the complicated map-reduce application
• Analyze data reference to the Pig and Hive
What is the Big Data Hadoop duration course
The Big Data Hadoop Certificate Course is expected to take 45 hours. Call us at +91-7397396665 to participate in that interactive and live session.
What is MapReduce?
MapReduce algorithm is utilized in scale substantial data sets diagonally thousands of servers within a Big Data Hadoop cluster.
Do you provide course materials?
We enhance the Big Data Hadoop training tools and course materials for lifetime access.
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