Hadoop Administrator Course Description
Be a Big Data Hadoop Administrator by learning concepts of Hadoop and implement advanced operations on Hadoop Clusters.
Hadoop Administration will help you master Hadoop admin activities like planning, Installation, Monitoring, Configuration and performance tuning large complex Hadoop clusters.
In this Hadoop admin course, you will learn to implement security using Kerberos and Hadoop yarn features using real-life use cases. This course will prepare you for Cloudera CCA Administrator Exam (CCA131) Exam.
Hadoop Administrator Course Learning Outcomes;
- Learn about Hadoop Architecture and its main components.
- Learn Hadoop installation and configuration.
- Deep dive into Hadoop Distributed File System (HDFS).
- Understand MapReduce abstraction and its working.
- Troubleshoot cluster issues and recover from Node failures.
- Learn about Hive, Pig, Ooozie, Sqoop and Flume.
- Optimize Hadoop cluster for high performance.
- Prepare for the Cloudera Certified Administrator for Apache Hadoop.
Hadoop Administration Training – Suggested Audience
This training is aimed at professionals who want to make a career in Big data & Hadoop. Suggested attendees are:
- Hadoop developers
- Hadoop Admin
- IT managers
- Support Engineers.
- QA professionals.
Hadoop Administrator Training – Prerequisites
No prerequisites required for taking this training. Having a basic knowledge of Linux can help.
Hadoop Administrator In-house/Corporate Training
If you have a group of 5-6 participants, apply for in-house training. For commercials please send us an email with group size to email@example.com
|1. Hadoop introduction|
|2. Hadoop Configuration|
|3. Hadoop maintenance|
|4. Hadoop distribution|
|5. Vanilla Hadoop installation|
|6. HDFS Architecture: Namenode|
|7. HDFS Architecture: Datanode|
|8. Apache Hadoop MySQL Sqoop Installation|
|9. Controlling Data in HDFS|
|10. Rebalancing the cluster|
|11. Node commissioning & decommissioning|
|12. Cloudera Manager for Rack Awareness|
|13. Hadoop Admin Project|
|Project 1 : Streaming Twitter Data using Flume Details||00:00:00|
|Project 2 : Hive & Impala comparison Details||00:00:00|
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