Cloudera Training for Apache HBase Training

Cloudera Training for Apache HBase Training (CAHB)

Introduction:

Cloudera Training for Apache HBase Training Course Description

Cloudera University’s three-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second.Through instructor-led discussion and interactive, hands-on exercises, you will learn to navigate the Hadoop ecosystem.

Customize It:

With onsite Training, courses can be scheduled on a date that is convenient for you, and because they can be scheduled at your location, you don’t incur travel costs and students won’t be away from home. Onsite classes can also be tailored to meet your needs. You might shorten a 5-day class into a 3-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff’s and site’s requirements.

Audience/Target Group

Developers
Administrators
Engineers

Cloudera Training for Apache HBase Training (CAHB)Related Courses:

Duration: 3 days

Class Prerequisites:

Prior experience with databases and data modeling is helpful
Knowledge of Java
Cloudera Developer Training for Apache Hadoop provides an excellent foundation for this course.

What You Will Learn:

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

Course Content:

Module 1: Introduction to Hadoop and HBase

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

Module 2: HBase Tables

HBase Concepts
HBase Table Fundamentals
Thinking About Table Design

Module 3: The HBase Shell

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

Module 4: HBase Architecture Fundamentals

HBase Regions
HBase Cluster Architecture
HBase and HDFS Data Locality

Module 5: HBase Schema Design

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

Module 6: 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

Module 7: More Advanced HBase API Features

Filtering Scans
Best Practices
HBase Coprocessors

Module 8: HBase on the Cluster

How HBase Uses HDFS
Compactions and Splits

Module 9: HBase Reads and Writes

How HBase Writes Data
How HBase Reads Data
Block Caches for Reading

Module 10: HBase Performance Tuning

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

Module 11: HBase Administration and Cluster Management

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

Module 12: HBase Replication and Backup

HBase Replication
HBase Backup
MapReduce and HBase Clusters

Module 13: Using Hive and Impala with HBase

Using Hive and Impala with HBase

Module 14: Appendix A: Accessing Data with Python and Thrift

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

Module 15: Appendix B: OpenTSDB

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Time Frame: 0-3 Months4-12 Months

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