CrinLogic / Level One Personnel

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Forging ahead of the data curve: Learn how to apply Apache Hadoop to create Big Data solutions.

Summary: This three-day course teaches students the building blocks (HDFS and MapReduce), introduces and uses projects from the Hadoop ecosystem (Hive, Pig, HBase), and covers various Big Data use cases. Learning is both lecture and hands-on, providing ample opportunity to both discuss and experience. The goal is to walk away able to create a Hadoop environment, import your data, start processing and begin forging ahead of the curve.

Audience: This course is designed for experienced programmers who wish to create Big Data solutions. The class assumes Java, but students of other languages are welcome. Prior knowledge of Apache Hadoop and related technologies is not necessary.

Trainer: This course is taught by CrinLogic trainers. All our trainers are practitioners with multiple years of hands-on experience with the Apache Hadoop ecosystem. We believe the best training is delivered by those who impart their real world experiences, successes and failures to their students.

Prerequisites: Students must bring their own laptop capable of running a 1MB virtual machine. The virtual machine is provided.

Agenda:

Introduction to Apache Hadoop

• Why are we here? What's changed today?
• What is Hadoop?
• Hadoop architecture

Hadoop Distributed File System (HDFS)

• Storing and retrieving data from HDFS
• HDFS operations
• Hadoop architecture

Developing with MapReduce

• How MapReduce works
• Writing Mappers
• Writing Reducers
• Using Combiners for efficiency

Modern Development Practices

• Running with LocalJobRunner
• Running within an IDE
• Writing Unit Tests for Hadoop code

Hadoop Projects: Hive

• Data warehouses: then and now
• Hive query language
• Hive in practice

Hadoop Projects: Pig

• Pig: a DSL for MapReduce
• Pig in practice

Hadoop Projects: HBASE

• Column-oriented database, real-time read-write access
• HBASE in practice

Wrap-up

• Further resource
• What's new and exciting