Apache HBase Training

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    Take your knowledge to the next level with Cloudera Training for Apache HBase. Cloudera Educational Services’ 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

    Audience and prerequisites

    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.

    Course Contents


    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


    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

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