Using HBase for Real-time Access to your Big Data
This course introduces you to HBase, the open source Hadoop database used for random, real-time read/writes to your Big Data. The course will cover fundamental concepts of HBase such as HBase system and architecture, the use of the Client API to perform data operations on HBase, the various HBase client used to communicate with HBase, how to integrate HBase with a MapReduce job, and more!
About This Course
HBase is the open source Hadoop database used for random, real-time read/writes to your Big Data. HBase runs on a distributed architecture on top of commodity hardware. HBase has the following features:
- Linear and modular scalability
- Strictly consistent read and writes
- Automatic and configurable sharding of tables
- Automatic failover support between RegionServers
- Easy to use Java API for client access
- And more…
Course Syllabus
- Lesson 1: Introduction to HBase
- CAP Theorem and ACID properties
- Roles of HBase and difference between RDBMS
- HBase Shell and Tables
- Lesson 2: HBase Client API – The Basics
- Use of Java API for Batch, Scan, and Scan operations
- Lesson 3: Client API: Administrative and Advance Features
- Use of administrative operations and schemas
- Use of Filters, Counters, and ImportTSV tool
- Lesson 4: Available HBase Clients
- Understand how interactive and batch clients interact with HBase
- Lesson 5: HBase and MapReduce Integration
- Understand how MapReduce works in the Hadoop framework
- How to setup HBase as a source and a sink
- Lesson 6: HBase Configuration and Administration
- Configuration of HBase for various environmental optimization
- Architecture and administrative tasks
Recommended skills prior to taking this course
- None
Grading scheme
- The minimum passing mark for the course is 60%, the final exam is worth 100% of the course mark.
- You have 1 attempt to take the exam with multiple attempts per question.
