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
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
3
Pillars of Hadoop – HDFS, MapReduce, and YARN
Index

Operations in Spark


RDDs support two types of operations:

  • Transformations

  • Actions

Transformations

The transformation operation performs some functions and creates another dataset. Transformations are processed in the lazy mode and only those transformations that are needed in the end result are processed. If any transformation is found unnecessary, then Spark ignores it, and this improves the efficiency.

Transformations, which are available and mentioned in Spark Apache docs at https://spark.apache.org/docs/latest/programming-guide.html#transformations, are as follows:

Transformation

Meaning

map (func)

Return a new distributed dataset formed by passing each element of the source through a function func.

filter (func)

Return a new dataset formed by selecting those elements of the source on which func returns true.

flatMap (func)

Similar to map, but each input item can be mapped to 0 or more output items (so func should return a Seq rather than a single item).

mapPartitions (func...