About Big Data Hadoop Training
Faculty : Realtime experience
This is an industry recognized Big Data certification training course that is a combination of the training courses in Hadoop developer, Hadoop administrator, Hadoop testing, and analytics. This Cloudera Hadoop training will prepare you to clear big data certification.
What you will learn in this Big Data Hadoop online training Course?
- Master fundamentals of Hadoop 2.7 and YARN and write applications using them
- Setting up Pseudo node and Multi node cluster on Amazon EC2
- Master HDFS, MapReduce, Hive, Pig, Oozie, Sqoop, Flume, Zookeeper, HBase
- Learn Spark, Spark RDD, Graphx, MLlib writing Spark applications
- Master Hadoop administration activities like cluster managing,monitoring,administration and troubleshooting
- Configuring ETL tools like Pentaho/Talend to work with MapReduce, Hive, Pig, etc
- Detailed understanding of Big Data analytics
- Hadoop testing applications using MR Unit and other automation tools.
- Work with Avro data formats
- Practice real-life projects using Hadoop and Apache Spark
- Be equipped to clear Big Data Hadoop Certification.
Who should take this Big Data Hadoop Online Training Course?
- Programming Developers and System Administrators
- Experienced working professionals , Project managers
- Big DataHadoop Developers eager to learn other verticals like Testing, Analytics, Administration
- Mainframe Professionals, Architects & Testing Professionals
- Business Intelligence, Data warehousing and Analytics Professionals
- Graduates, undergraduates eager to learn the latest Big Data technology can take this Big Data Hadoop Certification online training
What are the prerequisites for taking this Hadoop Certification Training?
There is no pre-requisite to take this Big data training and to master Hadoop. But basics of UNIX, SQL and java would be good. At Future Q Tech, we provide complimentary unix and Java course with our Big Data certification training to brush-up the required skills so that you are good on you Hadoop learning path.
Hadoop Online Training Course Content:
Course Objective Summary
- During this course, you will learn:
- Introduction to Big Data and Hadoop
- Hadoop ecosystem - Concepts
- Hadoop Map-reduce concepts and features
- Developing the map-reduce Applications
- Pig concepts
- Hive concepts
- Oozie workflow concepts
- HBASE Concepts
- Real Life Use Cases
Introduction to Big Data and Hadoop
- What is Big Data?
- What are the challenges for processing big data?
- What technologies support big data?
- What is Hadoop?
- Why Hadoop?
- History of Hadoop
- Use Cases of Hadoop
- Hadoop eco System
- HDFS
- Map Reduce
- Statistics
Understanding the Cluster
- Typical workflow
- Writing files to HDFS
- Reading files from HDFS
- Rack Awareness
- 5 daemons
Let's talk Map Reduce
- Before Map reduce
- Map Reduce Overview
- Word Count Problem
- Word Count Flow and Solution
- Map Reduce Flow
- Algorithms for simple & Complex problems
Developing the Map Reduce Application
- Data Types
- File Formats
- Explain the Driver, Mapper and Reducer code
- Configuring development environment - Eclipse
- Writing Unit Test
- Running locally
- Running on Cluster
- Hands on exercises
How Map-Reduce Works
- Anatomy of Map Reduce Job run
- Job Submission
- Job Initialization
- Task Assignment
- Job Completion
- Job Scheduling
- Job Failures
- Shuffle and sort
- Oozie Workflows
- Hands on Exercises
Map Reduce Types and Formats
- MapReduce Types
- Input Formats - Input splits & records, text input, binary input, multiple inputs & database input
- Output Formats - text Output, binary output, multiple outputs, lazy output and database output
- Hands on Exercises
Map Reduce Features
- Counters
- Sorting
- Joins - Map Side and Reduce Side
- Side Data Distribution
- MapReduce Combiner
- MapReduce Partitioner
- MapReduce Distributed Cache
- Hands Exercises
Hive and PIG
- Fundamentals
- When to Use PIG and HIVE
- Concepts
- Hands on Exercises
HBASE
- CAP Theorem
- Introduction to NOSQL
- Hbase Architecture and concepts
- Programming and Hands on Exercises
- Case Studies Discussions
- Certification Guidance
Full Course Content : Download Here
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