17 Mar 2014
Framework Training Ltd
Business Environment Group
Call us to discuss cost-effective options for training your team.
Price per person
Hadoop is a framework that offers high availability of large data sets, residing on anything from a single to server to clusters of thousands of computers, to be processed using a relatively simple programming model.
Our 2-day Apache Hadoop training course aims to help software developers, architects, IT managers and other interested parties, get a good understanding of what the Hadoop stack entails; of the pros and cons of implementing Hadoop, with demos and plenty of discussion.
We believe we are unique amongst providers of Hadoop training in the UK in that we have no ‘hidden agenda’. We don’t have any products to sell during our courses and we don’t have a commercial affiliation with any Hadoop or Cloud service provider.
This means we are able to give a genuinely unbiased overview of the technology and marketplace.
If you are interested in custom / on-site Hadoop / Big Data design and analysis training for any size of team, please get in touch – we would be glad to help build a course that meets your learning requirements.
We can take into account your existing technical skills, project requirements and timeframes, and specific topics of interest to tailor the most relevant and focussed course for you.
This can be particularly useful if you need to learn just the new features and Best Practices with Hadoop, or need to include extra topics to help with pre-requisite skills.
What you will learn
- Hadoop Architecture & Common Utilities
- Hadoop Distributed File System (HDFS)
- Structured data storage With HBase
- Cassandra multi-master database
- Data warehousing with Hive
- Parallel programming with Pig
- Data mining with Mahout
- Cloud computing with Amazon Elastic MapReduce
Who should attend
Big Data with Apache Hadoop Training Course Syllabus
History of Hadoop – Facebook, Dynamo, Yahoo, Google
Hadoop Distributed File System (HDFS)
HDFS Clusters – NameNodes, DataNodes & Clients
Processing & Generating large data sets
Programming MapReduce using SQL / Bash / Python
Data warehousing with Hive
Analysing large datasets
HiveQL (SQL-like Query Language)
Parallel processing with Pig
Query language interface
Data mining with Mahout
Batch-based collaborative filtering
Structured data storage With HBase
Big Data: How big is big?
Optimised realtime read/write access
Cassandra multi-master database
The Cassandra Data Model
When to use Cassandra
Overview of Amazon Web Services
Running Hadoop tasks with Elastic MapReduce
Data storage with Amazon S3
Creating ad-hoc datawarehouse with EMR and Hive