Big Data Processing With Spark & Hadoop Training Course: Distributed Data Handling

Introduction

Unlock the power of massive datasets with our Big Data Processing with Spark and Hadoop Training Course. This program is designed to equip you with the essential skills to handle large datasets with distributed computing frameworks, enabling you to build scalable and efficient big data solutions. In today's data-driven world, mastering Spark and Hadoop is crucial for processing and analyzing vast amounts of data, driving insights and innovation. Our big data processing training course offers hands-on experience and expert guidance, empowering you to leverage these powerful technologies.

This distributed computing frameworks training delves into the core concepts of Spark and Hadoop, covering topics such as distributed file systems, data processing pipelines, and cluster management. You'll gain expertise in using industry-standard tools and techniques to handle large datasets with distributed computing frameworks, meeting the demands of modern big data projects. Whether you're a data engineer, data scientist, or big data developer, this Big Data Processing with Spark and Hadoop course will empower you to build and deploy high-performance big data systems.

Target Audience:

• Data Engineers
• Data Scientists
• Big Data Developers
• Data Architects
• Software Engineers
• Database Administrators
• Anyone needing big data processing skills

Course Objectives:

• Understand the fundamentals of big data processing with Spark and Hadoop.
• Master Hadoop Distributed File System (HDFS) for scalable storage.
• Utilize Spark for distributed data processing and analysis.
• Implement MapReduce for batch processing in Hadoop.
• Design and build efficient big data processing pipelines.
• Optimize Spark and Hadoop jobs for performance and scalability.
• Troubleshoot and address common big data processing challenges.
• Implement cluster management and monitoring for big data systems.
• Integrate Spark and Hadoop with real-world data applications.
• Understand how to handle data security and governance in big data environments.
• Explore advanced big data processing techniques (e.g., streaming data processing with Spark Streaming).
• Apply real world use cases for big data processing.
• Leverage big data tools and libraries for efficient development.

Duration

10 Days

Course content

Module 1: Introduction to Big Data Processing with Spark and Hadoop

• Fundamentals of big data processing with Spark and Hadoop.
• Overview of distributed file systems and processing frameworks.
• Setting up a big data development environment.
• Introduction to Spark and Hadoop tools and libraries.
• Best practices for big data processing.

Module 2: Hadoop Distributed File System (HDFS)

• Implementing HDFS for scalable storage.
• Utilizing HDFS commands and file management.
• Designing and building data storage solutions with HDFS.
• Optimizing HDFS for data retrieval and processing.
• Best practices for HDFS.

Module 3: Spark for Distributed Data Processing

• Implementing Spark for distributed data processing.
• Utilizing Spark Core, Spark SQL, and Spark MLlib.
• Designing and building Spark data pipelines.
• Optimizing Spark jobs for performance.
• Best practices for Spark.

Module 4: MapReduce in Hadoop

• Implementing MapReduce for batch processing.
• Utilizing Map and Reduce functions for data transformation.
• Designing and building MapReduce jobs.
• Optimizing MapReduce for large-scale data processing.
• Best practices for MapReduce.

Module 5: Big Data Processing Pipeline Design

• Designing efficient big data processing pipelines.
• Implementing data ingestion, transformation, and analysis.
• Utilizing workflow management tools (Oozie, Airflow).
• Optimizing pipeline design for performance.
• Best practices for pipeline design.

Module 6: Spark and Hadoop Job Optimization

• Optimizing Spark and Hadoop jobs for performance and scalability.
• Utilizing performance tuning techniques.
• Implementing resource management and allocation.
• Designing scalable big data solutions.
• Best practices for job optimization.

Module 7: Troubleshooting Big Data Processing Challenges

• Debugging common big data processing issues.
• Analyzing job performance and errors.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common big data challenges.
• Best practices for troubleshooting.

Module 8: Cluster Management and Monitoring

• Implementing cluster management and monitoring.
• Utilizing YARN and cluster management tools.
• Designing and building monitoring dashboards.
• Optimizing cluster performance and resource utilization.
• Best practices for cluster management.

Module 9: Integration with Real-World Data Applications

• Integrating Spark and Hadoop with real-world data applications.
• Utilizing APIs and data connectors.
• Implementing real-time big data processing.
• Optimizing integration for business impact.
• Best practices for integration.

Module 10: Data Security and Governance

• Implementing data security and governance in big data environments.
• Utilizing data encryption and access control.
• Designing and building secure data pipelines.
• Optimizing data handling for compliance.
• Best practices for security.

Module 11: Advanced Big Data Processing Techniques

• Implementing streaming data processing with Spark Streaming.
• Utilizing advanced data analytics with Spark MLlib.
• Designing and building advanced big data solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced techniques.

Module 12: Real-World Use Cases

• Implementing big data processing for e-commerce analytics.
• Utilizing big data processing for financial data analysis.
• Implementing big data processing for healthcare data management.
• Utilizing big data processing for social media analysis.
• Best practices for real-world applications.

Module 13: Big Data Tools and Libraries Implementation

• Utilizing Spark and Hadoop libraries for data processing.
• Implementing big data pipelines with Python and Scala.
• Designing and building solutions with big data tools.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Performance Tuning and Optimization

• Implementing performance tuning and optimization techniques.
• Utilizing profiling and debugging tools.
• Designing and building optimized data processing jobs.
• Optimizing job performance and resource utilization.
• Best practices for performance tuning.

Module 15: Future Trends in Big Data Processing

• Emerging trends in big data processing.
• Utilizing cloud-based big data solutions.
• Implementing serverless big data processing.
• Best practices for future big data applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.