HBase Course And Certification

What is HBase?

HBase is a column-oriented, distributed database that is built on top of the Hadoop file system. It is an open-source software project and it is also horizontally scalable.

HBase is a data model that is very comparable to Google’s big table that was designed to provide quick and random access to huge volumes of structured data. It makes use of the fault tolerance that is provided by the Hadoop File System (HDFS).

HBase is a part of the Hadoop ecosystem that offers random and real-time read/write access to data that is in the Hadoop File System.

One can store the data in Hadoop File System either directly or with the use of HBase. Data consumer reads and accesses the data in HDFS randomly by using HBase. HBase sits on top of the Hadoop File System and provides software developers with a read and write access.

HBase is a truly open-source NoSQL distributed database designed with inspiration from Google's Bigtable and built with Java. It is built as part of the Apache Software Foundation Apache Hadoop project and executes on top of HDFS (Hadoop Distributed File System) or Alluxio, offering Bigtable-type capabilities for Hadoop. it offers a fault-tolerant process of saving large quantities of separated data (small volumes of information found within a large collection of empty or data that aren't important, for example finding the 50 biggest items in a group of 2 billion data points or searching for non-zero items representing less than 0.1% of a huge collection).

HBase provides compression, in-memory processing, and Bloom filters on a per single column basis as mentioned in the authentic Bigtable paper. Tables in HBase can work as the input and output for MapReduce processes run in Hadoop and it may be accessed via the Java API but also via REST, Avro or Thrift gateway APIs. HBase is a column disciplined key-value data storage database and it is widely been adopted because of its connection with Hadoop and HDFS. HBase executes on top of HDFS and is well built for faster read and write operations on large volumes of datasets with very high throughput and low input/output latency.

HBase is not a direct replacement for a traditional SQL database, Although, Apache Phoenix project offers a SQL layer for HBase also with JDBC driver that can be connected with different analytics and business intelligence software. The Apache Trafodion project offers an SQL query system with ODBC and JDBC drivers and shared ACID transaction protection across multiple statements, tables and rows that make use of HBase as a storage engine/system.

HBase is now serving a couple of data-driven websites although Facebook's Messaging Platform recently transitioned from HBase to MyRocks. Unlike relational and classic databases, HBase does not have support SQL scripting; instead, the equivalent to SQL scripting is written in Java, providing similarity with a MapReduce application.

Features of HBase

There are lots of features of HBase and some of them are:

1. Consistency: HBase has a very high consistency ratio and is very suitable for high-speed requirements because it gives you consistent reads and writes access.

2. Atomic Read and Write: During one of your read or write processes, all other processes are restricted from carrying out any other read or write operations this is known as Atomic read and write. So, HBase offers you atomic read and write, on a very low level.

3. Sharding: In order to take down the I/O time and overhead cost, HBase gives you both automatic and manual splitting of regions into smaller subregions, as soon as it attains a threshold size.

4. High Availability: Furthermore, it makes use of WAN and LAN which manages and supports failover and recovery. Essentially, there is a master server, at the core of the application, which manages the monitoring of the region servers as well as all metadata for the data cluster.

Benefits of Studying HBase

1. Low cost: HBase can be run on regular cheap hardware, Hadoop can be operated on average performing hardware and it doesn't need a high-performance system to run on, which can help in taking down the cost of operation and to achieve performance and scalability. Adding or taking away nodes from the cluster is very simple. The cost per terabyte of data is lower for storage purposes and for data processing in Hadoop.

2. Storage flexibility: Hadoop can be used to store data in raw format in a distributed production environment. Hadoop can be used to process the data that is in an unstructured or semi-structured format much better than most of the available technologies. Hadoop gives you complete flexibility to process the stored data and there are zero possibilities of data loss in Hadoop.

3. Open-source community: Hadoop is an open-source project and it is maintained by many contributors with an ever-growing network of software developers and contributors worldwide. Many organizations such as Facebook, Yahoo, Hortonworks, and others have immensely contributed toward the growth and progress of Hadoop and other related sub-projects.

4. Fault-tolerant: Hadoop is fault-tolerant and highly scalable. Hadoop is reliable in the areas of data availability, and even if some of your nodes go down, Hadoop can recover the lost data. Hadoop architecture expects that nodes can go down and the system should be able to process the data and recover from data loss.

5. Complex data analytics: With the development and emergence of big data, data science has also advanced beyond leaps and bounds, and we have complex and high algorithms that are computation-intensive for carrying out data analysis. Hadoop can also process such scalable algorithms for very large-scale data and it can also process the algorithms very fast.

6. Job Opportunities and Career Advancement.

HBase Course Outline

HBase - Introduction

HBase - Overview

HBase - Architecture

HBase - Installation

HBase - Shell

HBase - General Commands

HBase - Admin API

HBase - Create Table

HBase - Listing Table

HBase - Disabling a Table

HBase - Enabling a Table

HBase - Describe & Alter

HBase - Exists

HBase - Drop a Table

HBase - Shutting Down

HBase - Client API

HBase - Create Data

HBase - Update Data

HBase - Read Data

HBase - Delete Data

HBase - Scan

HBase - Count & Truncate

HBase - Security

HBase - Video Lectures 

HBase - Exams and Certification