Apache Hadoop Engineer Training Course

Qualified for CPFA® Certificate in Apache Hadoop Engineer (CE.HD)

Duration: 2 Days

Overview

Understand the key modules of Apache Hadoop and Hadoop clients (the interactive environment such as Python, Scala, Java, R). Apply the skills in building applications and analytics program that effectively handle big data, the best practice in performance tuning and trouble shooting.

For private classes, please contact us at (852) 2116 3328 for more details.

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Course Objectives

This module guides people through the critical ways one can manage Apache Hadoop Big Data platform. It starts from introduction and architecture of Apache Hadoop’s core modules and gradually builds up to the level where attendees can not only store Big Data in the fault-tolerant way but also walk away with a solid understanding of the concepts about scalable Big data analytic engine.

Intended Audience

Designed for power users or engineers to manage their data at scale, in unstructured and/or structured formats according to the Big Data De Facto standard

Course Outline

This course will cover the following concepts:

  • Apache Hadoop – The Fault-Tolerant Big Data Storage
  • Introduction of 4 core modules of Apache Hadoop
  • Apache Hadoop Cluster Architecture
  • Apache Hadoop Benchmark tool
  • Unstructured data, semi-structured and structured data
  • Introduction of Apache Hadoop's Distributed File System (HDFS)
  • Apache Hadoop Archival Storage, SSD, Disk, and Memory Disk
  • Apache Hadoop End-to-end Encryption-decryption
  • Apache Hadoop Key Management System
  • Introduction of Apache Hadoop’s YARN
  • Apache Hadoop Schedulers
  • Power User of HDFS and YARN
  • Use YARN to manage GPU and CPU partitions
  • Introduction of Apache Hadoop MapReduce

Trainer

Mr. Patrick Tsoi

  • Certified Professional for Apache projects Trainer
  • Doctor of Education (in progress), Hong Kong Baptist University
  • Master in IT in Education, University of Hong Kong
  • Bachelor of Engineering in System Engineering and Engineering Management, Chinese University of Hong Kong
  • Over 20+ years in the IT training field, and work includes complex projects applying data science, and software development in Finance, Data Science and Quantitative Analysis

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