Hadoop Developer Certification Training
The EdUnbox Big Data Hadoop Developer training course is created by specialized Hadoop subject matter experts and covers in-depth data relating to Big Data and Hadoop ecosystem tools like Oozie, Flume, and HBase. We also offer real-life industry cases for in-depth training in this area. We also cover trending Big Data apps on Hadoop. Our training will enable students to clear certification exams and secure their future as best-in-class developers.
What will you learn in this Big Data Hadoop Developer Training course?
This Big Data Hadoop Certification course is designed to offer comprehensive knowledge of the Big Data framework. This deploys Hadoop, Spark, HDFS and MapReduce. In-depth discussions and explanations will center around Pig, Hive and other Hadoop themes to process and analyze large datasets within the HDFS and the use of Flume and Sqoop for data consumption along with practical training sessions. Real-time data processing can also be mastered using functional programming via Spark, implementation of Spark apps, understanding parallel processing in Spark and using Spark RDD optimization methods. Through this Big Data Course, students will also acquire knowledge about various interactive Spark algorithms and the basics of Hadoop ecosystems, including the following:
- Acquire knowledge about Hadoop fundamentals and Hadoop architecture for beginners.
- Prepare for Cloudera Spark and Hadoop Developer Certification.
- Integrate HBase as well as MapReduce for advanced deployment and indexing.
- Develop Big Data apps using Hadoop technology.
- Work on the core of Big Data Analytics using components of the Hadoop ecosystem like Pig and Hive.
- Compose MapReduce programs and use Hadoop clusters.
- Learn all about Hadoop administration and development of best practices.
- Learn how Spark works as a framework
- Understand RDD in Spark framework
- Master Oozie for job scheduling and management of work.
Who should go for this Big Data Hadoop Developer training?
Big Data offers a multitude of career opportunities for growth. Hadoop is becoming the must-know technology in Big Data architecture. Additionally, Big Data training is best oriented towards meeting the needs of IT, data management and analytics experts looking to gain a competitive edge. The market for Big Data analytics is booming. For IT professionals and those looking to acquire developer skills, our Big Data Hadoop developer training helps you to catalyze your career aspirations and work well for professionals and freshers as well. Hadoop experts are among the highest paid IT professionals with salaries ranging across USD 97K and the market demand is growing rapidly, too. Here’s a brief idea of who can benefit from this training course:
- Graduates Looking to Build a Career in Big Data (CS. or Non-CS backgrounds)
- DBAs and DB pros
- Senior and middle-level IT professionals
- Data analytics specialists
- Software developers, project managers, and software architects
- ETL and Data Warehousing workers
- Big Data Hadoop developers and architects as well as testing personnel.
- Job aspirants
What are the prerequisites for this Big Data Hadoop Developer training?
- You don’t need prior Apache Hadoop knowledge.
- However, knowledge of SQL and Core Java knowledge will be an additional add-on.
- The international Hadoop market is poised to grow at USD 84.6 billion within 2 years, according to Allied MR research.
- IBM estimates data professionals will experience a surge in jobs in the US at a rate of 2.7 million annually.
- Hadoop developers in the US can receive a salary of USD 100K, according to Indeed.com
- McKinsey further estimates that there will be a shortage of 1.4 to 1.9 million Hadoop Data analysts in the US alone by 2018.
- Forbes holds that the Hadoop market will reach USD 99.3 1 billion by 2022 at the CAGR of 42.1 percent.
- Introduction to Big Data and the Hadoop Ecosystem.
- Introduction to the concept of Big Data and Hadoop Fundamentals
- Dimensions of Big Data
- Kinds of Data Generation
- Limitations of traditional solutions for Big Data problems and architecture
- Hadoop Ecosystem
- Hadoop 2.x Core Components
- Hadoop Storage: HDFS
- Hadoop Architecture
- Anatomy of File Read
- Hadoop Processing: MapReduce Framework.
- Different Hadoop Distributions.
- Hadoop Replications
- HDFS Core Concepts
- Modes of Hadoop Employment
- HDFS Mr.V1 versus MrV2 architecture
- Kinds of Data Compression Techniques
- Rack Topology
- Hadoop Distributors
2. Hadoop Installation and Setup
- Hadoop 2.x Cluster Architecture
- High Availability & Federation
- Typical Production Cluster Setup
- Hadoop Cluster Modes
- Common Hadoop Shell Commands
- Hadoop 2.x Configuration Files
- Typical Production Hadoop Cluster
- Hadoop Cluster Modes
- Common Hadoop Shell Commands
- Single & Multi-Node Cluster Setup
3. Hadoop MapReduce Framework
- MapReduce Versus Traditional Ways
- Why Opt for MapReduce
- YARN Components
- YARN Architecture
- YARN Workflow
- YARN MapReduce Application Execution Flow
- Structure and Anatomy of MapReduce Program
- MapReduce Combiners and Partitioners
- Relation Between Input Splits and HDFS Blocks
- MapReduce Design Flow
- MapReduce Program Execution
- Types of Input and output formats
- MapReduce Datatypes
- MapReduce Jobs Performance Tuning
- Counters Methods & Techniques
- Deep Drive in MapReduce
- How Driver Works
- Shuffle and Sort
- Mapside Joins
- Reduce Side Joins
- Distributed Cache
- Writing a WordCount Program
- Working with HDFS
- Writing Custom Partitioner
- MapReduce With Combiner
- Unit Testing MapReduce
- Running MapReduce in Local Job Runner Mode,
- Graph Representation
- Breadth First Search Algorithm
- Graph Representation of MapReduce
- How to Carry Out a Graph Algorithm
- Illustrations of Graph MapReduce.
4. Advanced MapReduce
- Distributed Cache
- Custom Input Format
- Sequence Input Format
- XML File Parsing Using MapReduce
5. Apache Pig
- Introduction and description of Apache Pig
- MapReduce Versus Apache Pig
- Pig Components & Execution
- Pig Data Types and Data Models
- Pig Latin Programs
- Utility and Shell Commands
- Pig UDF and Pig Streaming
- Testing Pig Scripts
- Deploying Pig for Data Analysis
- Pig Latin syntax,
- Data Types
- Deploying Pig for ETL
- Data Loading
- Scheme Viewing
- Field Definitions
- Functions used
- Pig for Complex Processing of Data
- Loading Data Into Relations
- Nested and Complex Data Types
- Grouped Data Iteration
- Multi-Dataset Operations
- Data set Joining, Data Set Splitting
- Methods for Data Set Combining
- Set Operations
- User-defined functions: An Introduction
- Performing data processing with imports, Macros, and languages to extend Pig
- Using the GRUNT Shell + Pig Script Execution in Shell/HUE
- Working with Basic Data Transformations
- Working with Advanced Data Transformations
- Pig modes of storage, execution concepts.
- Pig program logics explanations
- Pig Basic Commands
- Introduction to Apache Hive
- Hive Versus Pig
- Hive Components and Architecture
- Hive Metastore
- Hive’s Limitations
- Comparison with Traditional Database
- Hive Data Models and Data Types
- Hive Partition
- Hive Bucketing
- Hive Managed & External Tables
- Importing Data
- Querying Data and Managing Outputs
- Hive Script and UDF
- Hive for Relational Data Analysis
- HiveQL and syntax
- Tables and Databases
- Data set joining
- Inbuilt Functions
- Deploying Hive on Scripts, Hue and Shell.
- Database creation
- Data modeling
- Data loading
- Changing tables and databases
- Query Simplification through Views
- Thrift Server
- Managing Data With Hive
- Hive Optimization
- Extending Hive
- Deploying user-defined functions for Hive Extensions
- Hive Query Optimizers
7. HBase Architecture
- Advanced Apache HBase concepts
- Demos on HBase Bulk Loading and HBase Filters
- HBase Data Model
- HBase Shell
- HBase Client API
- Hive Data Loading Techniques
- Apache Zookeeper Introduction
- Zookeeper Data Model
- Zookeeper Service
- HBase Bulk Loading
- Inserting and Getting Data
- HBase Filters
- HBase Versus RDBMS
- HBase Components
- HBase Cluster Deployment
- HBase Architecture
- HBase Run Modes
- HBase Configuration
- Introduction to NoSQL/CAP Theorem concepts
- HBase design and architecture flow
- HBase table commands
- Hive and HBase Integration Module or Jars Deployment
- HBase execution in Shell/HUE
8. Apache Sqoop
- Introduction to Sqoop Concepts
- Sqoop Internal Design/Architecture
- Sqoop Export Statements Concepts
- Sqoop Import Statements Concepts
- Quest Data Connectors Flow
- Creating a MySQL Database for Importing to HDFS
- Incremental Updating Concepts
- Sqoop Command Execution in Shell/HUE
9. Apache Hue & Flume
- Introduction to Hue Design
- UI Interface/Hue Architecture Flow
- Introduction to Flume and Features
- Flume Core Concepts and Topology
- Property File Parameters Logic
- Installing Flume,
- Flume Agent and Events
10. Principles of Hadoop Administration
- Principles of Hadoop Administration and Importance
- Hadoop Admin Commands Explanation
- Balancer Concepts
- Rolling Upgrade Mechanism Explanation
- Oozie Introduction
- Oozie Components
- Oozie Workflow
- Scheduling with Oozie Job Scheduler
- Demo of Oozie WorkFlow
- Oozie Coordinator
- Oozie Commands
- Oozie Web Console
- Oozie MapReduce
- Combining Flow of MapReduce Jobs
- Hive in Oozie
- Hadoop Demo
- Hadoop Talend Integration
- Oozie Install and Setup
- Workflows and Coordinators
- Bundles For Data Pipelines
12. Apache Spark
- Apache Kafka architecture and Key Concepts
- Apache Storm and Key Concepts
- Stream Processing with Spark Streaming
- Processing Distributed Data With Apache Spark
- Spark Context and Ecosystem.
- Resilient Distributed Datasets in Apache Spark
- What is Spark?
- Spark Ecosystem
- What is Scala?
- Spark Components
- Benefits of Scala
- Spark Context
- Spark RDD
13. Big Data Hadoop Best Practices & Real-Time Projects
EdUnbox is delighted to offer this comprehensive course for clearing Hadoop Component of “Cloudera Spark and Hadoop Developer Certification”. Now, get the best positions in private companies, MNCs and PSUs with this useful qualification. As part of the training, we are also offering real-time assignments and projects that have amazing implications in the real-world industry scenario helping to accelerate your career effortlessly.
Towards the completion of this training program, you will participate in the real-time projects and quizzes that will prepare you for questions in the certification examination and help you to score well in this exam. EdUnbox Course Completion Certificate will be awarded on the completion of projects on the basis of trainer reviews and on scoring 50% minimum marks in the quiz.
EdUnbox certification is well recognized among leading corporate brands in a wide range of industries and verticals including Fortune 500 companies. Let the community know about your achievement and become certified today! Advance your career with our Big Data Hadoop Developer Training course.
Payments can be made using any of the following options. You will be emailed a receipt after the payment is made.
- Visa Credit or Debit Card
- American Express
- Diner’s Club
Thank you for your course. I am giving full marks to the entire EDUNBOX support team. You are the best!
This EDUNBOX Hadoop tutorial has delivered more than what they had promised to me. EDUNBOX took it to a different level with their attention to details and Hadoop domain expertise. I recommend this training to everybody.
I mastered Hadoop through the EDUNBOX Big Data Hadoop online training. Let me frankly tell you that this course is designed in a comprehensive manner that is by far the best.
I completed my HADOOP training, thanks to edunbox. I personally feel that edunbox is the right place to embark on a successful big data hadoop career with this hadoop course.
A big thank you to the entire EDUNBOX Big Data Hadoop Team! You have delivered a great Hadoop online certification training course, with equally informative Hadoop online tutorials, Big Data video tutorials that are absolutely free.
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I am completely in awe of the EDUNBOX support that came with the HADOOP training which as they promised was 24/7 and also very dependable and friendly.
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It was a wonderful experience and learning from EDUNBOX trainers. For me learning cutting edge and latest technologies EDUNBOX is the right place.
I am glad that I took the EDUNBOX HADOOP training. The trainers offered quality HADOOP training with real-world examples, and there was extensive interactivity throughout the training that made the EDUNBOX training the best according to me.
I enjoyed this course from the very first session. The content guides you from the very basic approach of the fundamentals to the advanced level with practical knowledge in just a few days of training.
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The course was conducted by recognized professionals which helped me understand the subject easily. The trainer was cooperative enough to clarify things perfectly to me.
This is the best course for beginners in IT. I got highly advanced knowledge on almost all the concepts related to HADOOP.
I loved the way the trainer took the classes systematically.