Hadoop emerged in response to the proliferation of masses and masses
of data collected by organizations, offering a strong solution to store,
process, and analyze what has commonly become known as Big Data. It
comprises a comprehensive stack of components designed to enable these
tasks on a distributed scale, across multiple servers and thousands of
machines.
Learning Hadoop 2 introduces you to the powerful system synonymous
with Big Data, demonstrating how to create an instance and leverage
Hadoop ecosystem's many components to store, process, manage, and query
massive data sets with confidence.
We open this course by providing an overview of the Hadoop component
ecosystem, including HDFS, Sqoop, Flume, YARN, MapReduce, Pig, and Hive,
before installing and configuring our Hadoop environment. We take a
look at Hue, the graphical user interface of Hadoop.
We will then discover HDFS, Hadoop’s file-system used to store data.
We will learn how to import and export data, both manually and
automatically. Afterward, we turn our attention toward running
computations using MapReduce, and get to grips working with Hadoop’s
scripting language, Pig. Lastly, we will siphon data from HDFS into
Hive, and demonstrate how it can be used to structure and query data
sets.
About The Author
Randal Scott King is the Managing Partner of Brilliant Data, a
consulting firm specialized in data analytics. In his 16 years of
consulting, Scott has amassed an impressive list of clientele from
mid-market leaders to Fortune 500 household names. Scott lives just
outside Atlanta, GA, with his children. You can visit his blog at
http://www.randalscottking.com.
