Abizer Adenwala is a Sr. Technical Support Engineer at MapR.
In this post, I’ll show you what happens behind the scenes, from the time a user fires any job from a Client/Edge node or Cluster node, until the time the job actually gets submitted to the JobTracker for execution.
As a follow-up to my previous post on MapR-DB, I want to describe how to index MapR-DB table data in near real-time into Elasticsearch on Amazon Web Services (AWS) Elastic Compute Cloud (EC2).
In this post, you will learn how memory is sliced and diced from the time you start warden, how memory is allocated to each MapR service installed on the node, and what memory is made available for MR1 for running jobs.
In this blog post, you’ll learn how memory is sliced and diced from the time you start warden, how memory is allocated to each MapR service installed on the node, and what memory is made available for MR1/MR2 for running jobs.
In this tutorial, you’ll learn how you can deploy your MapR clusters with just one click on your private cloud infrastructure.
In this week's Whiteboard Walkthrough, Abizer Adenwala, Technical Support Engineer at MapR, walks you through what a storage pool is, why disks are striped, reasons disk would be marked as failed, what happens when a disk is marked failed, what to watch out for before reformatting/re-adding disk back, and what is the best path to recover from disk failure.
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