HBase For Developers

Course Overview

Section 1: Introduction to Big Data & NoSQL

• Big Data ecosystem
• NoSQL overview
• CAP theorem
• When is NoSQL appropriate
• Columnar storage
• HBase and NoSQL

Section 2 : HBase Intro

• Concepts and Design
• Architecture (HMaster and Region Server)
• Data integrity
• HBase ecosystem
• Lab : Exploring HBase

Section 3 : HBase Data model

• Namespaces, Tables and Regions
• Rows, columns, column families, versions
• HBase Shell and Admin commands
• Lab : HBase Shell

Section 4 : Accessing HBase using Java API

• Introduction to Java API
• Read / Write path
• Time Series data
• Scans
• Map Reduce
• Filters
• Counters
• Co-processors
• Labs (multiple) : Using HBase Java API to implement  time series , Map Reduce, Filters and counters.

Section 5 : HBase schema Design : Group session

• Students are presented with real world use cases
• Students work in groups to come up with design solutions
• Discuss / critique and learn from multiple designs
• Labs : implement a scenario in HBase

Section 6 : HBase Internals

• Understanding HBase under the hood
• Memfile / HFile / WAL
• HDFS storage
• Compactions
• Splits
• Bloom Filters
• Caches
• Diagnostics

Section 7 : HBase installation and configuration

• Hardware selection
• Install methods
• Common configurations
• Lab : installing HBase

Section 8 : HBase eco-system

• Developing applications using HBase
• Interacting with other Hadoop stack (MapReduce, Pig, Hive)
• Frameworks around HBase
• Advanced concepts (co-processors)
• Labs : writing HBase applications

Section 9 : Monitoring And Best Practices

• Monitoring tools and practices
• Optimizing HBase
• HBase in the cloud
• Real world use cases of HBase
• Labs : checking HBase vitals

Prerequisites

Prerequisites:

• comfortable with Java programming language
• comfortable in Java programming language (navigate Linux command line , edit files with vi / nano)
• A Java IDE like Eclipse or IntelliJ