Hadoop Developer In Real World
From the creators of the successful Hadoop Starter Kit course hosted in Udemy, comes Hadoop In Real World course. This course is designed for anyone who aspire a career as a Hadoop developer. In this course we have covered all the concepts that every aspiring Hadoop developer must know to SURVIVE in REAL WORLD Hadoop environments.
The course covers all the must know topics like HDFS, MapReduce, YARN, Apache Pig and Hive etc. and we go deep in exploring the concepts. We just don’t stop with the easy concepts, we take it a step further and cover important and complex topics like file formats, custom Writables, input/output formats, troubleshooting, optimizations etc.
All concepts are backed by interesting hands-on projects like analyzing million song dataset to find less familiar artists with hot songs, ranking pages with page dumps from wikipedia, simulating mutual friends functionality in Facebook just to name a few.
Thank You and Let's Get Started
Introduction To Big Data
With Amazon EMR we can start a brand new Hadoop cluster and run MapReduce jobs in matter of minutes. This lecture will walk through step by step how to set up a Hadoop cluster and run MapReduce jobs in it.
Hadoop Administrator In Real World (Preview)
In this lecture we will learn about the benefits of Cloudera Manager, differences between Packages and Parcels and lifecycle of Parcels.
In this lecture we will see how to install a 3 node Hadoop cluster on AWS using Cloudera Manager
Troubleshooting and Optimizations
This lecture will give an introduction to Apache Sqoop and demonstrate Sqoop imports to bring data from a traditional databases like MySQL to HDFS
This lecture will cover custom Sqoop imports and how Sqoop can be used to export tables in different file formats
This lecture will cover Sqoop jobs & incremental imports.
This lecture will demonstrate how Sqoop can be used to create and populate a Hive Table directly and also how to export data from HDFS to a MySQL table
In this lecture, we will see an introduction to Flume and we will look in detail about the different flume components - source, channel and sink. We will also look at a very simple flume configuration to ingest log messages to HDFS.
In this lecture we will ingest log messages from a single source and replicate the flume events in to HDFS and local file system.