Learn by Example : HBase - The Big data Hadoop Database

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Course Summary :

Prerequisites: Working with HBase requires knowledge of Java

Taught by a team which includes 2 Stanford-educated, ex-Googlers  and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scale data processing jobs. 

Relational Databases are so stuffy and old! Welcome to HBase - a database solution for a new age. 

HBase: Do you feel like your relational database is not giving you the flexibility you need anymore? Column oriented storage, no fixed schema and low latency make HBase a great choice for the dynamically changing needs of your applications. 

What's Covered: 

25 solved examples covering all aspects of working with data in HBase
CRUD operations in the shell and with the Java API, Filters, Counters, MapReduce 

Implement your own notification service for a social network using HBase

HBase and it’s role in the Hadoop ecosystem, HBase architecture and what makes HBase different from RDBMS and other Hadoop technologies like Hive. 

Talk to us!

  • Write us about anything - anything! - and we will always reply :-)

What am I going to get from this course?

  • Set up a database for your application using HBase
  • Integrate HBase with MapReduce for data processing tasks
  • Create tables, insert , read and delete data from HBase
  • Get an all round understanding of HBase and it's role in the Hadoop ecosystem

Pre-Requisites :

What are the requirements? You'll need to have an IDE where you can run Java code, Intellij IDEA and Eclipse are both good options You'll need to have some experience with Java programming

Target Audience :

What is the target audience? Yep! Anyone who is interested in understanding HBase, NoSQL and distributed database management Yep! Engineers who want to move away from RDBMS and use HBase for their database solution Yep! Folks who are using Hadoop ecosystem

Curriculum :

Section 1 - You, This Course and Us
      1 : You, This Course and Us01:50
    Section 2 - Introduction to HBase
        2 : The problem with distributed computing
        3 : Installing HBase
        4 : The Hadoop ecosystem
        5 : The role of HBase in the Hadoop ecosystem
        6 : How is HBase different from RDBMS?
        7 : HBase Data Model
        8 : Introducing CRUD operations
        9 : HBase is different from Hive
      Section 3 - CRUD operations using the HBase Shell
          10 : Example1 - Creating a table for User Notifications Preview
          11 : Example 2 - Inserting a row
          12 : Example 3 - Updating a row
          13 : Example 4 - Retrieving a row
          14 : Example 5 - Retrieving a range of rows
          15 : Example 6 - Deleting a row
          16 : Example 7 - Deleting a table
        Section 4 - CRUD operations using the Java API
            17 : Example 8 - Creating a table with HBaseAdmin
            18 : Example 9 - Inserting a row using a Put object
            19 : Example 10 - Inserting a list of Puts
            20 : Example 11 - Retrieving data - Get and Result objects
            21 : Example 12 - A list of Gets
            22 : Example 13 - Deleting a row
            23 : Example 14 - A list of Deletes
            24 : Example 15 - Mix and match with batch operations
            25 : Example 16 - Scanning a range of rows
            26 : Example 17 - Deleting a table
          Section 5 - HBase Architecture
              27 : HBase Architecture
            Section 6 - Advanced operations - Filters and Counters
                28 : Example 18 - Filter by Row id - RowFilter
                29 : Example 19 - Filter by column value - SingleColumnValueFilter
                30 : Example 20 - Apply multiple conditions - Filterlist Preview
                31 : Example 21 - Retrieve rows within a time range Preview
                32 : Example 22 - Atomically incrementing a value with Counters
              Section 7 - MapReduce with HBase
                  33 : Example 23 : A MapReduce task to count Notifications by Type
                  34 : Example 23 continued: Implementing the MapReduce in Java
                  35 : Demo : Running a MapReduce task
                Section 8 - Build a Notification Service
                    36 : Example 24 : Implement a Notification Hierarchy
                    37 : Example 25: Implement a Notifications Manager
                  Section 9 - Installing Hadoop in a Local Environment
                      38 : Hadoop Install Modes
                      39 : Setup a Virtual Linux Instance (For Windows users)
                      40 : Hadoop Standalone mode Install
                      41 : Hadoop Pseudo-Distributed mode Install


Instructor :

Loonycorn A 4-ppl team;ex-Google.


Loonycorn is us, Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh. Between the four of us, we have studied at Stanford, IIM Ahmedabad, the IITs and have spent years (decades, actually) working in tech, in the Bay Area, New York, Singapore and Bangalore. Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too Swetha: Early Flipkart employee, IIM Ahmedabad and IIT Madras alum Navdeep: longtime Flipkart employee too, and IIT Guwahati alum We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Unanth! We hope you will try our offerings, and think you'll like them :-)


Average Rating
 (1 Reviews)



posted 6 month before

Nice way of teaching

I enjoyed learning from this course. Teaching style is good. Concepts explained in nice way.