Book Image

Hadoop Essentials

By : Shiva Achari
Book Image

Hadoop Essentials

By: Shiva Achari

Overview of this book

This book jumps into the world of Hadoop and its tools, to help you learn how to use them effectively to optimize and improve the way you handle Big Data. Starting with the fundamentals Hadoop YARN, MapReduce, HDFS, and other vital elements in the Hadoop ecosystem, you will soon learn many exciting topics such as MapReduce patterns, data management, and real-time data analysis using Hadoop. You will also explore a number of the leading data processing tools including Hive and Pig, and learn how to use Sqoop and Flume, two of the most powerful technologies used for data ingestion. With further guidance on data streaming and real-time analytics with Storm and Spark, Hadoop Essentials is a reliable and relevant resource for anyone who understands the difficulties - and opportunities - presented by Big Data today. With this guide, you'll develop your confidence with Hadoop, and be able to use the knowledge and skills you learn to successfully harness its unparalleled capabilities.
Table of Contents (15 chapters)
Hadoop Essentials
About the Author
About the Reviewers
Pillars of Hadoop – HDFS, MapReduce, and YARN

Storm topology

Streams can be partitioned among bolts by using stream grouping, which allows the streams to be routed towards a bolt. Storm provides the following built-in stream groupings, and you can implement a custom stream grouping by implementing the interface:

  • Shuffle grouping: Each bolt is configured uniformly to get an almost equal number of tuples

  • Fields grouping: Grouping on a particular field is possible to consolidate the tuples of the same field value and different value tuples to different bolts

  • All grouping: Each tuple can be sent to all the bolts but can increase the overhead

  • Global grouping: All the tuples go to a single bolt

  • Direct grouping: The producer can decide which tuples to be sent to which bolt