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Only 3 days
Classroom
28/10/2024 (Monday)
Overview
Get the skills you need to write, maintain, and optimise Apache Hadoop on this accelerated Cloudera Certified Developer for Apache Hadoop (CCDH) course. Learn how create robust data processing applications using Apache Hadoop.
This course is 33% faster than traditional training. You’ll be prepared for the real world challenges faced by Hadoop developers and study the following topics:
- The internals of MapReduce, Hadoop Distributed File System (HDFS) and how to write MapReduce code
- Best practices for Hadoop development, debugging, and implementation of workflows and common algorithms
- How to leverage Hive, Pig, Sqoop, Flume, Oozie, and other Hadoop ecosystem projects
- Creating custom components such as WritableComparables and InputFormats to manage complex data types Writing and executing joins to link data sets in MapReduce
- Advanced Hadoop API topics required for real-world data analysis
Curriculum
The Motivation for Hadoop
- Problems with traditional large-scale systems
- Introducing Hadoop
- Hadoopable problems
Hadoop: Basic Concepts and HDFS
- The Hadoop project and Hadoop components
- The Hadoop Distributed File System
Introduction to MapReduce
- MapReduce overview
- Example: WordCount
- Mappers
- Reducers
Hadoop Clusters and the Hadoop Ecosystem
- Hadoop cluster overview
- Hadoop jobs and tasks
- Other Hadoop ecosystem components
Writing a MapReduce Program in Java
- Basic MapReduce API Concepts
- Writing MapReduce Drivers, Mappers, and Reducers in Java
- Speeding up Hadoop development by using eclipse
- Differences between the old and new MapReduce APIs
Writing a MapReduce Program Using Streaming
- Writing Mappers and Reducers with the streaming API
Unit Testing MapReduce Programs
- Unit testing
- The JUnit and MRUnit testing frameworks
- Writing unit tests with MRUnit
- Running unit tests
Delving Deeper into the Hadoop API
- Using the ToolRunner class
- Setting up and tearing down Mappers and Reducers
- Decreasing the amount of intermediate data with combiners
- Accessing HDFS programmatically
- Using the distributed cache
- Using the Hadoop API’s Library of Mappers, Reducers, and Partitioners
Practical Development Tips and Techniques
- Strategies for debugging MapReduce code
- Testing MapReduce code locally by using LocalJobRunner
- Writing and viewing log files
- Retrieving job information with counters
- Reusing objects
- Creating map-only MapReduce jobs
Partitioners and Reducers
- How partitioners and Reducers work together
- Determining the optimal number of Reducers for a job
- Writing customer partitioners
Data Input and Output
- Creating custom writable and WritableComparable implementations
- Saving binary data using sequenceFile and Avro data files
- Issues to consider when using file compression
- Implementing custom InputFormats and OutputFormats
Common MapReduce Algorithms
- Sorting and searching large data sets
- Indexing data
- Computing term frequency — Inverse Document Frequency
- Calculating word co-occurrence
- Performing Secondary Sort
Joining Data Sets in MapReduce Jobs
- Writing a Map-Side Join
- Writing a Reduce-Side Join
Integrating Hadoop into the Enterprise Workflow
- Integrating Hadoop into an existing enterprise
- Loading data from an RDBMS into HDFS by using Sqoop
- Managing real-time data using Flume
- Accessing HDFS from legacy systems with FuseDFS and HttpFS
An Introduction to Hive, Imapala, and Pig
- The motivation for Hive, Impala, and Pig
- Hive overview
- Impala overview
- Pig overview
- Choosing Between Hive, Impala, and Pig
An Introduction to Oozie
- Introduction to Oozie
- Creating Oozie workflows
Exam Track
As part of this accelerated course, you'll receive the following exam voucher:
- Cloudera Certified Developer for Apache Hadoop (CCD-410)
The exam consists of 55 questions and must be completed within 90 minutes. You must have a passing score of at least 70% to get your certification.
This course will cover content and practical tests to cover preparation to the exam. Firebrand cannot deliver the exam at our centre. Delegates will be provided with an exam voucher to take the exam.
What's included
Included:
- Official Cloudera courseware
Prerequisites
This course is best suited to developers and engineers with programming experience. Knowledge of Java is strongly recommended and is required to complete the hands-on exercises. Prior knowledge of Apache Hadoop is not required.
Benefits
Seven reasons why you should sit your course with Firebrand Training
- Two options of training. Choose between residential classroom-based, or online courses
- You'll be certified fast. With us, you’ll be trained in record time
- Our course is all-inclusive. A one-off fee covers all course materials, exams**, accommodation* and meals*. No hidden extras.
- Pass the first time or train again for free. This is our guarantee. We’re confident you’ll pass your course the first time. But if not, come back within a year and only pay for accommodation, exams and incidental costs
- You’ll learn more. A day with a traditional training provider generally runs from 9 am – 5 pm, with a nice long break for lunch. With Firebrand Training you’ll get at least 12 hours/day of quality learning time, with your instructor
- You’ll learn faster. Chances are, you’ll have a different learning style to those around you. We combine visual, auditory and tactile styles to deliver the material in a way that ensures you will learn faster and more easily
- You’ll be studying with the best. We’ve been named in the Training Industry’s “Top 20 IT Training Companies of the Year” every year since 2010. As well as winning many more awards, we’ve trained and certified over 135,000 professionals
*For residential training only. Doesn't apply for online courses
**Some exceptions apply. Please refer to the Exam Track or speak with our experts
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