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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
Testimonials (4)
Trainer's preparation & organization, and quality of materials provided on github.
Mateusz Rek - MicroStrategy Poland Sp. z o.o.
Course - Impala for Business Intelligence
The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.
Safar Alqahtani - Elm Information Security
Course - Big Data Analytics in Health
Liked very much the interactive way of learning.
Luigi Loiacono
Course - Data Analysis with Hive/HiveQL
I mostly liked the trainer giving real live Examples.
