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Course Outline
Section 1: Introduction to Hadoop
- hadoop history, concepts
- eco system
- distributions
- high level architecture
- hadoop myths
- hadoop challenges
- hardware / software
- lab : first look at Hadoop
Section 2: HDFS
- Design and architecture
- concepts (horizontal scaling, replication, data locality, rack awareness)
- Daemons : Namenode, Secondary namenode, Data node
- communications / heart-beats
- data integrity
- read / write path
- Namenode High Availability (HA), Federation
- labs : Interacting with HDFS
Section 3 : Map Reduce
- concepts and architecture
- daemons (MRV1) : jobtracker / tasktracker
- phases : driver, mapper, shuffle/sort, reducer
- Map Reduce Version 1 and Version 2 (YARN)
- Internals of Map Reduce
- Introduction to Java Map Reduce program
- labs : Running a sample MapReduce program
Section 4 : Pig
- pig vs java map reduce
- pig job flow
- pig latin language
- ETL with Pig
- Transformations & Joins
- User defined functions (UDF)
- labs : writing Pig scripts to analyze data
Section 5: Hive
- architecture and design
- data types
- SQL support in Hive
- Creating Hive tables and querying
- partitions
- joins
- text processing
- labs : various labs on processing data with Hive
Section 6: HBase
- concepts and architecture
- hbase vs RDBMS vs cassandra
- HBase Java API
- Time series data on HBase
- schema design
- labs : Interacting with HBase using shell; programming in HBase Java API ; Schema design exercise
Requirements
- comfortable with Java programming language (most programming exercises are in java)
- comfortable in Linux environment (be able to navigate Linux command line, edit files using vi / nano)
Lab environment
Zero Install : There is no need to install hadoop software on students’ machines! A working hadoop cluster will be provided for students.
Students will need the following
- an SSH client (Linux and Mac already have ssh clients, for Windows Putty is recommended)
- a browser to access the cluster. We recommend Firefox browser
28 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €9120 online delivery, based on a group of 2 delegates, €2880 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
Contact us for an exact quote and to hear our latest promotions
Public Training
Please see our public courses
Testimonials (5)
The live examples
Ahmet Bolat - Accenture Industrial SS
Course - Python, Spark, and Hadoop for Big Data
During the exercises, James explained me every step whereever I was getting stuck in more detail. I was completely new to NIFI. He explained the actual purpose of NIFI, even the basics such as open source. He covered every concept of Nifi starting from Beginner Level to Developer Level.
Firdous Hashim Ali - MOD A BLOCK
Course - Apache NiFi for Administrators
Trainer's preparation & organization, and quality of materials provided on github.
Mateusz Rek - MicroStrategy Poland Sp. z o.o.
Course - Impala for Business Intelligence
That I had it in the first place.
Peter Scales - CACI Ltd
Course - Apache NiFi for Developers
practical things of doing, also theory was served good by Ajay
