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Hbase Essentials

Hbase Essentials

By : Garg
3.5 (2)
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Hbase Essentials

Hbase Essentials

3.5 (2)
By: Garg

Overview of this book

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.
Table of Contents (9 chapters)
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Preface
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Introducing HBase
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1. Introducing HBase
The world of Big Data
The origin of HBase
Use cases of HBase
Installing HBase
Understanding HBase cluster components
Summary
2
2. Defining the Schema
2. Defining the Schema
Data modeling in HBase
Designing tables
Accessing HBase
Summary
3
3. Advanced Data Modeling
3. Advanced Data Modeling
Understanding keys
HBase table scans
Implementing filters
Summary
4
4. The HBase Architecture
4. The HBase Architecture
Data storage
Data replication
Securing HBase
HBase and MapReduce
Summary
5
5. The HBase Advanced API
5. The HBase Advanced API
Counters
Coprocessors
The administrative API
Summary
6
6. HBase Clients
6. HBase Clients
The HBase shell
Kundera – object mapper
REST clients
The Thrift client
The Hadoop ecosystem client
Summary
7
7. HBase Administration
7. HBase Administration
Cluster management
Cluster monitoring
Performance tuning
Troubleshooting
Summary
8
Index
Index

The origin of HBase

Looking at the limitations of GFS and MR, Google approached another solution, which not only uses GFS for data storage but it is also used for processing the smaller data files very efficiently. They called this new solution BigTable.

Note

BigTable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers.

Welcome to the world of HBase, http://hbase.apache.org/. HBase is a NoSQL database that primarily works on top of Hadoop. HBase is based on the storage architecture followed by the BigTable. HBase inherits the storage design from the column-oriented databases and the data access design from the keyvalue store databases where a key-based access to a specific cell of data is provided.

Note

In column-oriented databases, data grouped by columns and column values is stored contiguously on a disk. Such a design is highly I/O effective when dealing with very large data sets used for analytical queries where not all the columns are needed.

HBase can be defined as a sparse, distributed, persistent, multidimensional sorted map, which is indexed by a row key, column key, and timestamp. HBase is designed to run on a cluster of commodity hardware and stores both structured and semi-structured data. HBase has the ability to scale horizontally as you add more machines to the cluster.

End of Section 3
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