Hadoop, (Part 4 of 4): HBase and MapReduce

Big Data development is a growing field and understanding how technologies such as the MapReduce Combiner and HBase can make data analysis easier is important. Learn how to use the Combiner, look deeply at HBase, a NoSQL tool for managing the storage and retrieval of large and diverse data sets, and create a starter app to use HBase in Java.

Lesson 1:

• MapReduce Components
• Combiner
• Why Use a Combiner?
• How the Combiner Works
• Combiner, Reducer Differences.

Lesson 2:

• Demo: Mapper Stub
• Demo: Reducer &amp Combiner Stubs
• Demo: Main
• Demo: Fill in Methods
• Demo: Run WordCountCombiner.

Lesson 3:

• Relational vs. Non-Relational Databases
• What Is HBase?
• What Does HBase Do?
• Other HBase Features
• The HBase Shell.

Lesson 4:

• Demo: The HBase Shell
• Demo: Ambari
• Demo: Build a Table
• Demo: Add Data.

Lesson 5:

• HBase Architecture
• HBase Scalability
• HBase Durability
• HBase Consistency
• HBase Input/Output
• Working with Data
• Partitioning a Table
• Serving Regions
• Partitioning Advantage
• Region Server Failover/Load Balancing.

Lesson 6:

• The HBase Write Path
• HBase MemStore
• HBase Write-Ahead Log
• HBase on a Single Server
• Scaling HBase
• The Flush Operation
• HBase Cache
• Read Optimization
• Minimizing Disk Seeks
• HBase Compaction
• HBase Load Balancing
• HBase Split Operation
• HBase Scalability
• HBase Limitations.

Lesson 7:

• HBase Archetypes
• What Is a Good HBase Archetype?
• Effective Design
• Effective Design of Queries
• Row-Key Design
• Effective Application Design
• Entities in HBase
• Working with Simple Entities
• Simple Entity Guidelines
• Working with Linked Entities
• Creating a Linked Entity
• Linked Entity Guidelines
• Compound Key
• Compound Time Series
• HBase Techniques for Historical Data
• Considerations for Timestamps.

Lesson 8:

• Demo: Setup
• Demo: HBase Methods
• Demo: Flesh Out Methods
• Demo: Main Method
• Demo: HBase Environment
• Demo: Run HBase App.