What is Big Data?
The size issue
Hadoop’s position in the landscape

Presentation of an existing node
Organization of services and study of sequencing with YARN

Workshop: modifying the size of HDFS blocks to reduce the number of Map / Reduce

Relationship between the installed platform and the development
frameworks Propose independent frameworks to ensure compatibility: Spring Data

Workshop: deploy an application for accessing HBase through an O / R Spring Data mapping

Deploy a Map / Reduce program on a cluster of Hadoop nodes
Search for logs
Report anomalies to developers
Suggest the use of Kafka file

Workshop: use of input output queue for a Map / Reduce program

Definition of software routes with Apache Flume
Set up a calculation case where the data triggers the programs

Workshop: routing data from an HDFS directory to a Kafka file which is the entry of a Map / Reduce program

Using Ambari views
Viewing the status of nodes in a cluster
Import / export configuration files

Workshop: relaunching a cluster of services, using the YARN and Tez views

Managing user accounts
Managing file rights on a distributed file system
Using certificates

Lab: Configure Knox and Ranger Services