Hadoop Administration on MapR ( hadoopmapr | 28 hours )

• Basic knowledge of Linux FS
• Basic Java
• Knowledge of Apache Hadoop (recommended)

Audience:

This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand.

Big Data Overview:

• What is Big Data
• Why Big Data is gaining popularity
• Big Data Case Studies
• Big Data Characteristics
• Solutions to work on Big Data.

Hadoop & Its components:

• What is Hadoop and what are its components.
• Hadoop Architecture and its characteristics of Data it can handle /Process.
• Brief on Hadoop History, companies using it and why they have started using it.
• Hadoop Frame work & its components- explained in detail.
• What is HDFS and Reads -Writes to Hadoop Distributed File System.
• How to Setup Hadoop Cluster in different modes- Stand- alone/Pseudo/Multi Node cluster.

(This includes setting up a Hadoop cluster in VirtualBox/KVM/VMware, Network configurations that need to be carefully looked into, running Hadoop Daemons and testing the cluster).

• What is Map Reduce frame work and how it works.
• Running Map Reduce jobs on Hadoop cluster.
• Understanding Replication , Mirroring and Rack awareness in context of Hadoop clusters.

Hadoop Cluster Planning:

• How to plan your hadoop cluster.
• Understanding hardware-software to plan your hadoop cluster.
• Understanding workloads and planning cluster to avoid failures and perform optimum.

What is MapR and why MapR :

• Overview of MapR and its architecture.
• Understanding & working of MapR Control System, MapR Volumes , snapshots & Mirrors.
• Planning a cluster in context of MapR.
• Comparison of MapR with other distributions and Apache Hadoop.
• MapR installation and cluster deployment.

Cluster Setup & Administration:

• Managing services, nodes ,snapshots, mirror volumes and remote clusters.
• Understanding and managing Nodes.
• Understanding of Hadoop components, Installing Hadoop components alongside MapR Services.
• Accessing Data on cluster including via NFS Managing services & nodes.
• Managing data by using volumes, managing users and groups, managing & assigning roles to nodes, commissioning decommissioning of nodes, cluster administration and performance monitoring, configuring/ analyzing and monitoring metrics to monitor performance, configuring and administering MapR security.
• Understanding and working with M7- Native storage for MapR tables.
• Cluster configuration and tuning for optimum performance.

Cluster upgrade and integration with other setups:

• Upgrading software version of MapR and types of upgrade.
• Configuring Mapr cluster to access HDFS cluster.
• Setting up MapR cluster on Amazon Elastic Mapreduce.

All the above topics include Demonstrations and practice sessions for learners to have hands on experience of the technology.