Hadoop Training in Patras

This instructor-led live training in Patras (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets.

By the end of this training, participants will be able to:

• Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
• Understand the features, core components, and architecture of Spark and Hadoop.
• Learn how to integrate Spark, Hadoop, and Python for big data processing.
• Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
• Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
• Use Apache Mahout to scale machine learning algorithms.

Apache Hadoop stands as the leading framework for processing Big Data across server clusters. This three-day (or optionally four-day) program enables participants to understand the business advantages and real-world applications of Hadoop and its broader ecosystem. The curriculum covers planning for cluster deployment and scalability, as well as installing, maintaining, monitoring, troubleshooting, and optimizing Hadoop environments. Attendees will gain practical experience with bulk data loading, explore various Hadoop distributions, and manage ecosystem tools. The course concludes with a focus on securing clusters using Kerberos.

“The course materials were exceptionally well-prepared and thorough. The laboratory sessions were highly beneficial and expertly organized.”
— Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising

Audience

Hadoop system administrators

Format

A blend of theoretical lectures and practical hands-on labs, maintaining an approximate ratio of 60% lectures to 40% lab work.

Apache NiFi is an open-source platform designed for flow-based data integration and event processing. It facilitates automated, real-time data routing, transformation, and system mediation between diverse systems, featuring a web-based UI that offers fine-grained control.

This instructor-led training session, available either on-site or remotely, targets intermediate-level administrators and engineers who aim to deploy, manage, secure, and optimize NiFi dataflows within production environments.

Upon completing this training, participants will be equipped to:

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows originating from various sources and destinations.
• Implement logic for flow automation, routing, and transformation.
• Optimize performance, monitor operational metrics, and troubleshoot issues.

Course Format

• Interactive lectures accompanied by discussions on real-world architectures.
• Hands-on labs focused on building, deploying, and managing data flows.
• Scenario-based exercises conducted in a live laboratory environment.

Course Customization Options

• For organizations seeking a tailored training experience for this course, please reach out to us to make arrangements.

In this instructor-led, live training in Patras, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi.

By the end of this training, participants will be able to:

• Understand NiFi's architecture and dataflow concepts.
• Develop extensions using NiFi and third-party APIs.
• Custom develop their own Apache Nifi processor.
• Ingest and process real-time data from disparate and uncommon file formats and data sources.