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Apache HBase

( Duration: 3 Days )

Apache HBase is a NoSQL database that runs on Hadoop’s HDFS and is fully integrated with Hadoop. It is designed to handle large sets of data, which contain billions of columns and rows. It is an ideal choice for storing sparse and semi-structured data because it provides fault tolerance through replication, automatic failover, sharding, and load balancing. It also provides fast real-time lookups, in-memory caching, and server-side processing. Apache HBase can be accessed using various client APIs, including Java, Thrift, and REST.

This Apache HBase training course covers the HBase architecture and data models, install HBase, use the shell and client APIs to access the data.

By attending Apache HBase workshop, delegates will learn to:

  • Understand HBase Architecture and use HBase shell to directly manipulate HBase Tables
  • Design optimal HBase schemas for efficient data storage and recovery
  • Connect to HBase using the Java API
  • Understand how to bulk load data into HBase using MapReduce
  • Administer HBase cluster and Identify, resolve performance bottlenecks

  • Core Java knowledge

The Apache HBase class is ideal for:

  • Administrators and developers who need experience using Hbase.




  • Overview of HBase
  • HBase Requirements
  • HBase Software Requirements
  • HBase Filesystems
  • HBase Installation Modes
  • Installing HBase in Local Mode
  • Installing HBase in Fully Distributed Mode
  • Accessing the Web-Based Management Console
  • Using the HBase Shell


  • HBase Components
  • HFiles and Regions
  • The Write-Ahead Log and MemStore
  • Compaction and Splits
  • Data Replication
  • Access HBase
  • Securing HBase
  • Hadoop’s MapReduce Integration with HBase

Data Modeling

  • HBase Schema Overview
  • Designing Tables
  • Designing Rowkeys for Tables
  • Versions, DataTypes, and Joins
  • Time to Live and Deleted Cells

Table Creation in the Shell

  • Creating Tables Using the Shell
  • Disabling, Enabling, and Dropping a Table
  • Altering a Table’s Properties

Data Management in the Shell

  • Adding Data to a Table
  • Using the scan and get Commands
  • Deleting Data from a Table
  • Using Counters

Insert Data Using Java Client API

  • Establishing a Connection
  • Creating Tables using the Client Java API
  • Creating a Put Class Instance
  • Adding Data using the add() Option
  • Using Timestamp with Put for Versioning
  • Using the get() and has() Method

Get Data Using Java Client API

  • Using the Get Class
  • Retrieving Columns using the Get Class
  • Retrieving Versions of Columns using the Get Class
  • Retrieving Specific Values from a Cell
  • Using List with the Get Class

Scan Data using Java Client API

  • Using Scan() to read an Entire Table
  • Scanning Rows Starting at a Specific Row or a Range
  • Using Constructors to Narrow Search Results
  • Using getScanner() Method
  • Using the ResultScanner Class

Delete and Update Data using Java Client

  • Updating Data
  • Deleting Data


  • Implementing Utility Filters
  • Implementing Comparison Filters
  • Implementing Custom Filters

Cluster Administration

  • Checking the Status of the HBase Instance
  • Listing the User Space Tables
  • Deleting Tables
  • Completing a Major Compaction Manually
  • Merging Adjoining Regions
  • Stopping and Decommissioning a RegionServer
  • Performing a Rolling Restart
  • Adding a New Node
  • Monitoring HBase

Snapshots and Backups

  • Taking a Snapshot
  • Using a Snapshot to Clone a Table
  • Exporting and Restoring Snapshots
  • Performing a Full Shutdown Backup
  • Performing a Backup on a Live Cluster
  • Performing a Restore


  • Using HBase as a Data Sink for MapReduce Jobs
  • Using HBase as a Data Source for MapReduce Jobs
  • Bulk Loading Data
  • Splitting Map Tasks When Sourcing an HBase Table
  • Accessing Other HBase Tables within a MapReduce Job

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