Learn Hadoop in 24 Hours (eBook, ePUB)
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Hadoop has changed the way large data sets are analyzed, stored, transferred, and processed. At such low cost, it provides benefits like supports partial failure, fault tolerance, consistency, scalability, flexible schema, and so on. It also supports cloud computing. More and more number of individuals are looking forward to mastering their Hadoop skills.While initiating with Hadoop, most users are unsure about how to proceed with Hadoop. They are not aware of what are the pre-requisite or data structure they should be familiar with. Or How to make the most efficient use of Hadoop and its ecos...
Hadoop has changed the way large data sets are analyzed, stored, transferred, and processed. At such low cost, it provides benefits like supports partial failure, fault tolerance, consistency, scalability, flexible schema, and so on. It also supports cloud computing. More and more number of individuals are looking forward to mastering their Hadoop skills.
While initiating with Hadoop, most users are unsure about how to proceed with Hadoop. They are not aware of what are the pre-requisite or data structure they should be familiar with. Or How to make the most efficient use of Hadoop and its ecosystem. To help them with all these queries and other issues this e-book is designed.
The book gives insights into many of Hadoop libraries and packages that are not known to many Big data Analysts and Architects. The e-book also tells you about Hadoop MapReduce and HDFS. The example in the e-book is well chosen and demonstrates how to control Hadoop ecosystem through various shell commands. With this book, users will gain expertise in Hadoop technology and its related components. The book leverages you with the best Hadoop content with the lowest price range.
After going through this book, you will also acquire knowledge on Hadoop Security required for Hadoop Certifications like CCAH and CCDH. It is a definite guide to Hadoop.
Table Contents
Chapter 1: What Is Big Data
Examples Of 'Big Data'
Categories Of 'Big Data'
Characteristics Of 'Big Data'
Advantages Of Big Data Processing
Chapter 2: Introduction to Hadoop
Components of Hadoop
Features Of 'Hadoop'
Network Topology In Hadoop
Chapter 3: Hadoop Installation
Chapter 4: HDFS
Read Operation
Write Operation
Access HDFS using JAVA API
Access HDFS Using COMMAND-LINE INTERFACE
Chapter 5: Mapreduce
How MapReduce works
How MapReduce Organizes Work?
Chapter 6: First Program
Understanding MapReducer Code
Explanation of SalesMapper Class
Explanation of SalesCountryReducer Class
Explanation of SalesCountryDriver Class
Chapter 7: Counters & Joins In MapReduce
Two types of counters
MapReduce Join
Chapter 8: MapReduce Hadoop Program To Join Data
Chapter 9: Flume and Sqoop
What is SQOOP in Hadoop?
What is FLUME in Hadoop?
Some Important features of FLUME
Chapter 10: Pig
Introduction to PIG
Create your First PIG Program
PART 1) Pig Installation
PART 2) Pig Demo
Chapter 11: OOZIE
What is OOZIE?
How does OOZIE work?
Example Workflow Diagram
Oozie workflow application
Why use Oozie?
FEATURES OF OOZIE
While initiating with Hadoop, most users are unsure about how to proceed with Hadoop. They are not aware of what are the pre-requisite or data structure they should be familiar with. Or How to make the most efficient use of Hadoop and its ecosystem. To help them with all these queries and other issues this e-book is designed.
The book gives insights into many of Hadoop libraries and packages that are not known to many Big data Analysts and Architects. The e-book also tells you about Hadoop MapReduce and HDFS. The example in the e-book is well chosen and demonstrates how to control Hadoop ecosystem through various shell commands. With this book, users will gain expertise in Hadoop technology and its related components. The book leverages you with the best Hadoop content with the lowest price range.
After going through this book, you will also acquire knowledge on Hadoop Security required for Hadoop Certifications like CCAH and CCDH. It is a definite guide to Hadoop.
Table Contents
Chapter 1: What Is Big Data
Examples Of 'Big Data'
Categories Of 'Big Data'
Characteristics Of 'Big Data'
Advantages Of Big Data Processing
Chapter 2: Introduction to Hadoop
Components of Hadoop
Features Of 'Hadoop'
Network Topology In Hadoop
Chapter 3: Hadoop Installation
Chapter 4: HDFS
Read Operation
Write Operation
Access HDFS using JAVA API
Access HDFS Using COMMAND-LINE INTERFACE
Chapter 5: Mapreduce
How MapReduce works
How MapReduce Organizes Work?
Chapter 6: First Program
Understanding MapReducer Code
Explanation of SalesMapper Class
Explanation of SalesCountryReducer Class
Explanation of SalesCountryDriver Class
Chapter 7: Counters & Joins In MapReduce
Two types of counters
MapReduce Join
Chapter 8: MapReduce Hadoop Program To Join Data
Chapter 9: Flume and Sqoop
What is SQOOP in Hadoop?
What is FLUME in Hadoop?
Some Important features of FLUME
Chapter 10: Pig
Introduction to PIG
Create your First PIG Program
PART 1) Pig Installation
PART 2) Pig Demo
Chapter 11: OOZIE
What is OOZIE?
How does OOZIE work?
Example Workflow Diagram
Oozie workflow application
Why use Oozie?
FEATURES OF OOZIE
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