Key Training Topics for Hadoop Developer

hadoop training
This article represents key topics that one would want to learn in order to become a Hadoop Developer. One may also check these topics against topics provider by the training vendor. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos.

Following are the key areas tof focus for learning/training which are described later in this article:

  • Java Essentials
  • Hadoop Essentials
Java Essentials

As Hadoop is based on Java programming language, one would want to get expertise of at least intermediary level to do good with Hadoop development. Following are some of the key concepts that one would want to learn or get trained on:

  • JVM concepts
  • Data types
  • Basic Java constructs
  • Looping, switch concepts
  • Classes, objects and methods
  • Collections concepts such as HashMap, ArrayList, LinkedList
  • Exception handling
  • Building Java projects
Hadoop Essentials

It would be important to learn introductory and advanced concepts in relation with some of the following topics:

  • Basic introduction to Big Data and Hadoop
  • Hadoop Architecture: One should try and learn some of the following concepts:
    • Hadoop core components including HDFS & MapReduce
    • HDFS architecture (Name Node, Data Node)
    • MapReduce architecture (Job tracker, Task tracker)
    • Coordination service
  • Hadoop Installation & Deployment
  • Advanced concepts in HDFS
  • Advanced concepts in MapReduce
  • HBase concepts including HBase architecture, distributed data storage model, difference between RDBMS & HBase
  • Hive & Pig concepts including installation information, architecture related concepts, query compiler & optimizer, client & server components
  • Zookeeper concepts including installation information, challenges faced in coordination of distributed applications, usecases such as leader election or distributed locking service, data model etc.
  • Introduction to tools such as Apache Flume, Sqoop
  • Introduction to commercial distribution of Hadoop such as Cloudera, Hortonworks, MapR, IBM etc.
  • Introduction to Hadoop ecosystem including concepts on tools such as Oozie, Mahout, Spark etc.
  • Introduction to Hadoop administration, troubleshooting etc.
Ajitesh Kumar
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Ajitesh Kumar

I have been recently working in the area of Data Science and Machine Learning / Deep Learning. In addition, I am also passionate about various different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia etc and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc. I would love to connect with you on Linkedin.
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