Apache HBase Training Course and Workshop in Bangalore, Mysore, Chennai, Hyderabad, Pune, Mumbai, Delhi, Noida, Gurgaon, Kolkata

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.

Installation

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

Architecture

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

Filters

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

MapReduce

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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Apache HBase

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