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Hadoop Essentials

You're reading from   Hadoop Essentials Delve into the key concepts of Hadoop and get a thorough understanding of the Hadoop ecosystem

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784396688
Length 194 pages
Edition 1st Edition
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Author (1):
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Shiva Achari Shiva Achari
Author Profile Icon Shiva Achari
Shiva Achari
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Table of Contents (9) Chapters Close

Preface 1. Introduction to Big Data and Hadoop FREE CHAPTER 2. Hadoop Ecosystem 3. Pillars of Hadoop – HDFS, MapReduce, and YARN 4. Data Access Components – Hive and Pig 5. Storage Component – HBase 6. Data Ingestion in Hadoop – Sqoop and Flume 7. Streaming and Real-time Analysis – Storm and Spark Index

The HBase data model


Storage of data in HBase is column oriented, in the form of a multi-hierarchical Key-Value map. The HBase Data Model is very flexible and its beauty is to add or remove column data on the fly, without impacting the performance. HBase can be used to process semi-structured data. It doesn't have any specific data types as the data is stored in bytes.

Logical components of a data model

The HBase data model has some logical components which are as follows:

  • Tables

  • Rows

  • Column Families/Columns

  • Versions/Timestamp

  • Cells

The HBase table is shown in the following figure:

Let's take a look at these components in detail:

  • Tables: A Table in HBase is actually more logical than physical. An HBase Table can be described as a collection of rows. The data of a Table is presented in different, multiple Regions, and is distributed by the range of rowkey.

  • Rows: A Row is just a logical representation in HBase. Physically, the data is not stored in row, but in columns. Rows in HBase are combinations...

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