Hadoop Training
Catalogue index: IFS/83
product- line 1
Features
Description
InfoShare Academy is a leading IT academy offering comprehensive educational programs in new technologies for companies. Since 2015, we have been supporting organizations in developing technology teams through dedicated courses in Machine Learning, DevOps, Data Engineering, Python, UX/UI Design, AWS, and Kubernetes. Our training is based on practical skills and real business cases. We collaborate with over 300 industry practitioners, ensuring that our programs are tailored to current market needs. We specialize in reskilling and upskilling employees. With us, you will build effective teams implementing new technologies that will accelerate innovation and strengthen your company's competitiveness in the market. Check out our training offerings designed for companies, created to enhance your employees' competencies in the IT field.
- The Hadoop training is an intensive two-day course focused on the practical application of this popular framework for processing and analyzing large datasets. The training program is designed so that participants gain solid theoretical foundations (20%) and develop their practical skills (80%) through numerous workshops and projects. The course is ideal for those looking to understand and utilize Hadoop in their projects.
- Required technical skills:
- Basic programming knowledge in Java or Python
- Basic knowledge of data processing
- Ability to work in a Unix/Linux environment
- Programmers and data engineers who want to expand their skills with Hadoop
- Data scientists and data analysts wishing to process large datasets efficiently
- IT specialists and big data professionals looking to utilize Hadoop in their projects
- You will learn:
- How to effectively manage data in HDFS and create MapReduce tasks
- How to process and analyze data using Hive and Pig
- How to optimize MapReduce tasks and manage Hadoop resources
- How to deploy and monitor Hadoop applications in a production environment
Day 1: Basics of Hadoop and Data Processing
Hadoop Architecture
Overview of main Hadoop components: HDFS, MapReduce, YARN
Interaction between components
Basics of HDFS and MapReduce
File management in HDFS
Creating and running basic MapReduce tasks
Basics of Apache Hive and Apache Pig
Introduction to Hive: table structure, SQL queries
Analyzing file structure under Hive
Introduction to Pig: Pig Latin scripts
Workshop: Data Processing using MapReduce
Implementing a simple MapReduce task
Analyzing results and optimizing the task
Day 2: Advanced Techniques and Practical Applications
Advanced Data Processing
Writing advanced Hive queries
Creating complex Pig scripts
Optimization and Performance Tuning
Techniques for optimizing MapReduce tasks
Managing resources in a Hadoop cluster
Workshop: Data Analysis using Hive and Pig
Implementing Hive queries on real datasets
Creating Pig scripts for data processing
Deploying and Managing Hadoop Clusters
Preparing and deploying Hadoop applications
Monitoring and managing Hadoop clusters in a production environment
Cost Optimization – how to control and optimize costs arising from Redshift warehouses
16 h/2 days
- Certificate of completion
- Monthly access to the training recording (in case of online format)
- Customization of the training program to client needs