Cloudera Apache Hbase

Overview

Take your knowledge to the next level with Cloudera Training for Apache HBase. Cloudera University’s three-day training course enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second.

Hands-on Hadoop

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

The use cases and usage occasions for HBase, Hadoop, and RDBMS
Using the HBase shell to directly manipulate HBase tables
Designing optimal HBase schemas for efficient data storage and recovery
How to connect to HBase using the Java API to insert and retrieve data in real time
Best practices for identifying and resolving performance bottlenecks

Advance your ecosystem expertise

Apache HBase is a distributed, scalable, NoSQL database for big data built on Hadoop. HBase can store data in massive tables consisting of billions of rows and millions of columns, serve data to many users in near real time, and provide fast, random read/write access to applications.

Course Curriculum

Introduction

Introduction to Hadoop and HBase

Introducing Hadoop
Core Hadoop Components
What Is HBase?
Why Use HBase?
Strengths of HBase
HBase in Production
Weaknesses of HBase

HBase Tables

HBase Concepts
HBase Table Fundamentals
Thinking About Table Design

HBase Shell

Creating Tables with the HBase Shell
Working with Tables
Working with Table Data

HBase Architecture Fundamentals

HBase Regions
HBase Cluster Architecture
HBase and HDFS Data Locality

HBase Schema Design

General Design Considerations
Application-Centric Design
Designing HBase Row Keys
Other HBase Table Features

Basic Data Access with the HBase API

Options to Access HBase Data
Creating and Deleting HBase Tables
Retrieving Data with Get
Retrieving Data with Scan
Inserting and Updating Data
Deleting Data

More Advanced HBase API Features

Filtering Scans
Best Practices
HBase Coprocessors

HBase Write Path

HBase Write Path
Compaction
Splits

HBase Read Path

How HBase Reads Data
Block Caches for Reading

HBase Performance Tuning

Column Family Considerations
Schema Design Considerations
Configuring for Caching
Memory Considerations
Dealing with Time Series and Sequential Data
Pre-Splitting Regions

HBase Administration and Cluster Management

HBase Daemons
ZooKeeper Considerations
HBase High Availability
Using the HBase Balancer
Fixing Tables with hbck
HBase Security

HBase Replication and Backup

HBase Replication
HBase Backup
MapReduce and HBase Clusters

Using Hive and Impala with HBase

How to Use Hive and Impala to Access HBase

Conclusion

Appendix A: Accessing Data with Python and Thrift

Thrift Usage
Working with Tables
Getting and Putting Data
Scanning Data
Deleting Data
Counters
Filters

Appendix B: OpenTSDB

Prerequisite

This course is appropriate for developers and administrators who intend to use HBase. Prior experience with databases and data modeling is helpful, but not required. Knowledge of Java is assumed. Prior knowledge of Hadoop is not required, but Cloudera Developer Training for Spark and Hadoop provides an excellent foundation for this course.

Certification

On successful completion of the training program, participants will receive the certificate of participation from Cloudera.

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