Hadoop Administration on MapR培训

课程编码

hadoopmapr

课程时长

28 小时 通常来说是4天,包括中间休息。

要求

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

课程概览

听众:

本课程旨在揭开大数据/ hadoop技术的神秘面纱,并表明它不难理解。

Machine Translated

课程大纲

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.

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