Cloudera Administrator Training For Apache Hadoop

$4,154.00

Duration: 4 days

Online Option: Only – Open Enrolment

Prerequisites :

  • Basic Linux experience
  • Prior knowledge of Apache Hadoop is not required

Course dates : 

Contact P2L to schedule the dates for this course.

Per Participant Pricing: $4,154 CAD

Description

Cloudera Administrator Training for Apache Hadoop 101

Cloudera Administrator Training for Apache Hadoop

Cloudera University’s four-day Administrator training course is for Apache Hadoop provides participants with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster using Cloudera Manager. From the installation and configuration through load balancing and tuning, Cloudera’s training course is the best preparation for the real-world challenges faced by Hadoop administrators.

What is Apache Hadoop?

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Who is this course for?

This course is best suited to systems administrators and IT managers who have basic Linux experience.

Prerequisites

  • Basic Linux experience
  • Prior knowledge of Apache Hadoop is not required

Skills You’ll Learn

  • Cloudera Manager features that make managing your clusters easier, such as aggregated logging, configuration management, resource management, reports, alerts, and service management
  • Configuring and deploying production-scale clusters that provide key Hadoop-related services, including YARN, HDFS, Impala, Hive, Spark, Kudu, and Kafka
  • Determining the correct hardware and infrastructure for your cluster
  • Proper cluster configuration and deployment to integrate with the data center
  • How to load file-based and streaming data into the cluster using Kafka and Flume
  • Configuring automatic resource management to ensure service-level agreements are met for multiple users of a cluster
  • Best practices for preparing, tuning, and maintaining a production cluster
  • Troubleshooting, diagnosing, tuning, and solving cluster issues

 

For more information about this course, please check this blog from P2L.

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