Hadoop Training in New Zealand

This instructor-led, live training in New Zealand (available online or on-site) is tailored for developers seeking to use and integrate Spark, Hadoop, and Python to process, analyse, and transform large and complex data sets.

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

• Set up the necessary environment to begin processing big data using Spark, Hadoop, and Python.
• Understand the key features, core components, and architecture of both Spark and Hadoop.
• Learn how to integrate Spark, Hadoop, and Python for efficient big data processing.
• Explore tools within the Spark ecosystem, including Spark MLlib, Spark Streaming, Kafka, Sqoop, and Flume.
• Build collaborative filtering recommendation systems similar to those used by Netflix, YouTube, Amazon, Spotify, and Google.
• Use Apache Mahout to scale machine learning algorithms.

Apache Hadoop is the most popular framework for processing Big Data across clusters of servers. In this three-day course (with an optional fourth day), attendees will explore the business benefits and use cases for Hadoop and its ecosystem, learn how to plan cluster deployment and growth, and gain hands-on experience installing, maintaining, monitoring, troubleshooting and optimising Hadoop. Participants will also perform bulk data loads into clusters, become familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course concludes with a discussion on securing clusters using Kerberos.

“…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organised”
— Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising

Audience

Hadoop administrators

Format

Lectures and hands-on labs, with an approximate balance of 60% lectures and 40% labs.

Apache NiFi is an open-source, flow-based data integration and event-processing platform. It enables automated, real-time data routing, transformation, and system mediation between disparate systems, with a web-based UI and fine-grained control.

This instructor-led, live training (onsite or remote) is aimed at intermediate-level administrators and engineers who wish to deploy, manage, secure, and optimise NiFi dataflows in production environments.

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

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows from varied sources and sinks.
• Implement flow automation, routing, and transformation logic.
• Optimise performance, monitor operations, and troubleshoot issues.

Format of the Course

• Interactive lecture with real-world architecture discussion.
• Hands-on labs: building, deploying, and managing flows.
• Scenario-based exercises in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

In this instructor-led, live training in New Zealand, participants will learn the fundamentals of flow-based programming as they develop a range 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 diverse and uncommon file formats and data sources.