cloudera data analyst training for apache hadoop - xebia training

Software Development Done Right1

Software Development Done Right

for Apache HadoopCloudera Data Analyst training for Apache Hadoop

Training


Target Group & Prerequisites:

Cloudera Developer for Apache Hadoop

Agenda

Developer Certification

Xebia Worldwide

Contents Programme and Course

Overview

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Organizational Overview Founded in 2001, Xebia Training is a global leading brand in the Education Training space. An International IT Consulting, Project & Outsourcing organization. Specialized in Agile, Java, Software and Mobile development, Big Data, Architecture and

Agile testing. Work with Corporates, Students, Academic Institutes, PSUs & Government to enhance the

quality. Global delivery footprint. Trained over 30,000 students in India & abroad. Conducted training for more than 100 Corporates across various sectors.


Cloudera Developer for Apache Hadoop

Xebia's four-day developer training course delivers the key concepts and expertise participants need to create robust data processing applications using Apache Hadoop. From workflow implementation and working with APIs through writing MapReduce code and executing joins, Cloudera's training course is the best preparation for the realworld challenges faced by Hadoop developers.

http://training.xebia.in/big-data/cloudera-developer-for-apache-hadoop/


Programme and Course Overview

The only company which can support you on Learning, training and certification initiatives.

Xebia University delivers a developer-focused Cloudera Certified training course that closely analyzes Hadoop's structure and provides hands-on exercises that teach you how to import data from existing sources; process data with a variety of techniques such as Java MapReduce programs and Hadoop Streaming jobs; and work with Apache Hive and Pig.

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

• The internals of MapReduce and 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

•



Developer Certification:

Target Group & Prerequisites:

Certification is a great differentiator; it helps establish you as a leader in the field, providing employers and customers with tangible evidence of your skills and expertise.Learn more about the CCDH Certification Exam here:http://cloudera.com/content/cloudera/en/training/certification/ccdh.html

This course is best suited to developers and engineers who have programming experience. Knowledge of Java is strongly recommended and is required to complete the hands-on exercises.



Key Promises of this Training:

• The core technologies of Hadoop.• How HDFS and MapReduce work.• How to develop MapReduce applications.• How to unit test MapReduce applications.• How to use MapReduce combiners, partitioners and the

distributed cache.• Best practices for developing and debugging MapReduce

applications.• How to implement data input and output in MapReduce

applications.• Algorithms for common MapReduce tasks.• How to join data sets in MapReduce.• How Hadoop integrates into the data center.• How Hive, Impala and Pig can be used for rapid application

development.• How to create large workflows using Oozie.



Agenda:

• Introduction• The Motivation for Hadoop• Hadoop: Basic Concepts and HDFS• Introduction to MapReduce• Hadoop Clusters and the Hadoop

Ecosystem• Writing a MapReduce Program in Java• Writing a MapReduce Program Using

Streaming• Delving Deeper into the Hadoop API• Practical Development Tips and

Techniquess• Partitioners and Reducers• Data Input and Output• Implementing Custom InputFormats and

OutputFormats• Frequency• Joining Data Sets in MapReduce Jobs• Integrating Hadoop into the Enterprise

Workflow• An Introduction to Hive, Imapala, and Pig• An Introduction to Oozie• Conclusion



Key Promises of this Training:

• At least 4GB RAM;• 15GB of free hard disk space;• VMware Player 5.x or above (Windows)/ VMware Fusion 4.x or

above (Mac);• Your laptop must support a 64-bit VMware guest image. If the

machines are running a 64-bit version of WIndows, or Mac OS X on a Core DUO 2 processor or later, not other test is required. Otherwise, VMware provides a tool to check compatibility, which can be downloaded from http://tiny.cloudera.com/training2;

• Your laptop must have VT-x virtualization support enabled in the BIOS;

• If running Windows XP: 7-Zip or WinZip is needed (due to a bug in Windows XP's built-in Zip utility).


http://tiny.cloudera.com/training2


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