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Hbase Essentials
Hbase Essentials

Hbase Essentials: A practical guide to realizing the seamless potential of storing and managing high-volume, high-velocity data quickly and painlessly with HBase

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Hbase Essentials

Chapter 2. Defining the Schema

In this chapter, we are going to learn some of the basic concepts of the column family database, that is, HBase, and cover the following topics:

  • Data modeling
  • Designing tables
  • CRUD operations

Let's dive in and start off by taking a look at how we can model data in HBase.

Data modeling in HBase

In the RDBMS world, data modeling has principles around tables, columns, data types, size, and so on, and the only supported format is structured data. HBase is quite different in this aspect, as in each row, it can store different numbers of columns and data types, making it ideal for storing so-called semi-structured data. Storing semi-structured data not only impacts the physical schema but also the logical schema of HBase. For the same reason, some features such as relational constraints are also not present in HBase.

Similar to a typical RDBMS, tables are composed of rows and these rows are composed of columns. Rows in HBase are identified by a unique rowkey and are compared with each other at the byte level, which resembles a primary key in RDBMS.

In HBase, columns are organized into column families. There is no restriction on the number of columns that can be grouped together in a single column family. This column family is part of the data definition statement...

Designing tables

In HBase, when modeling the schema for any table, a designer should also keep in mind the following, among other things:

  • The number of column families and which data goes to which column family
  • The maximum number of columns in each column family
  • The type of data to be stored in the column
  • The number of historical values that need to be maintained for each column
  • The structure of a rowkey

Once we have answers, certain practices are followed to ensure optimal table design. Some of the design practices are as follows:

  • Data for a given column family goes into a single store on HDFS. This store might consist of multiple HFiles, which eventually get converted to a single HFile using compaction techniques.
  • Columns in a column family are also stored together on the disk, and the columns with different access patterns should be kept in different column families.
  • If we design tables with fewer columns and many rows (a tall table), we might achieve O(1) operations but also compromise with...

Accessing HBase

In the previous chapter, we saw how to create a table and simple data operations using the HBase shell. HBase can be accessed using a variety of clients, such as REST clients, Thrift client, object mapper framework—Kundera, and so on. HBase clients are discussed in detail in Chapter 6, HBase Clients. HBase also offers advanced Java-based APIs for playing with tables and column families. (HBase shell is a wrapper around this Java API.) This API also supports metadata management, for example, data compression for column family, region split, and so on. In addition to schema definition, the API also provides an interface for a table scan with various functions such as limiting the number of columns returned or limiting the number of versions of each cell to be stored. For data manipulation, the Hbase API supports create, read, update, and delete operations on individual rows. This API comes with many advanced features, which will be discussed throughout this book.

Note...

Summary

In this chapter, we learned the basics of modeling data and some strategies to consider when designing a table in HBase. We also learned how to perform basic CRUD operations on the table created using various APIs provided by HBase. In the next chapter, we will look into HBase table keys, table scan, and some other advanced features such as filters.

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Description

This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. This book is also for Big Data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic, scalable database solution in the Big Data space.

What you will learn

  • Realize the need for HBase
  • Download and set up HBase cluster
  • Grasp data modeling concepts in HBase and how to perform CRUD operations on data
  • Perform effective data scanning and data filtration in HBase
  • Understand data storage and replication in HBase
  • Explore HBase counters, coprocessors, and MapReduce integration
  • Get acquainted with different clients of HBase such as REST and Kundera ORM
  • Learn about cluster management and performance tuning in HBase

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 14, 2014
Length: 164 pages
Edition : 1st
Language : English
ISBN-13 : 9781783987245
Vendor :
Apache
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Publication date : Nov 14, 2014
Length: 164 pages
Edition : 1st
Language : English
ISBN-13 : 9781783987245
Vendor :
Apache
Category :
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Table of Contents

8 Chapters
1. Introducing HBase Chevron down icon Chevron up icon
2. Defining the Schema Chevron down icon Chevron up icon
3. Advanced Data Modeling Chevron down icon Chevron up icon
4. The HBase Architecture Chevron down icon Chevron up icon
5. The HBase Advanced API Chevron down icon Chevron up icon
6. HBase Clients Chevron down icon Chevron up icon
7. HBase Administration Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.5
(2 Ratings)
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1 star 0%
Ian Stirk Sep 29, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Hi,I have written a detailed chapter-by-chapter review of this book on www DOT i-programmer DOT info, the first and last parts of this review are given here. For my review of all chapters, search i-programmer DOT info for STIRK together with the book's title.This book aims at getting you started in programming with HBase, how does it fare?Hadoop is the most popular platform for processing big data, and HBase is the NoSQL database included with Hadoop. The book is aimed at software developers that have no previous experience of HBase, wanting a hands-on approach.Below is a chapter-by-chapter exploration of the topics covered.Chapter 1 Introducing HBaseThis chapter opens with the observation that relational database management systems (RDBMS) are unable to scale to process huge amounts of data in a timely manner. Instead, this is the realm of big data databases such as HBase.The chapter defines big data in terms of huge volumes, high velocity, and varied types of data. Currently 20 terabytes of data is created every second, and this metric is increasing. The foundations of big data processing were established by Google in their papers on the Google File System (GFS) storage, and MapReduce processing model. Google also produced details of a scalable Bigtable database which could handle millions of columns and billions of rows, HBase is based on Bigtable.The chapter continues with a look at how to install HBase together with its prerequisites. The various modes of running HBase are discussed, these are: local, pseudo-distributed and fully distributed.The various HBase cluster components are briefly described, namely:-HBase Master – coordinates HBase cluster/admin operations-Zookeeper – centralized service for distributed synchronization-Region Servers – store horizontal rows as regionsThe chapter ends with a look at the HBase shell, this provides an environment to run interactive commands or batches, it’s a useful tool for experimenting with HBase. Various commands are introduced, including: status, create table, list, get, put, scan, delete, describe, and drop.This chapter provides a useful introduction to HBase in terms of the history of big data, the need to process huge amounts of data, and an outline of the HBase components. Useful installation instructions are provided, together with a HBase shell tutorial for playing and testing with HBase.This chapter provides well written discussions which are generally easy to read, has helpful diagrams, outputs, scripts, and brief practical walkthroughs. There are useful links to other chapters. Sometimes, terms are used before they are defined (e.g. HMaster and Zookeeper). These traits apply to the whole of the book....ConclusionThe book has well-written discussions which are generally easy to read, helpful diagrams, outputs, scripts, and brief practical walkthroughs. There are useful links to other chapters.This book aims to get you started in programming with HBase, however, it deviates from this, containing as much administration detail as programming. Sometimes terms are used before they are defined (e.g. HMaster and Zookeeper), suggesting you need some knowledge of Hadoop. It would have been helpful to list where to go next to extend your HBase knowledge.This book will help you get up and running with HBase, show you how to use HBase from various clients, and give you an understanding of its internal structure, I can recommend it as a starter book.
Amazon Verified review Amazon
MMT Oct 31, 2016
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Easy to understand....
Amazon Verified review Amazon
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