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Items Tagged: YARN

news / Blog

Project Myriad Will Become Your Next Data Center Platform

One of the big things bubbling around at Strata this week is talk about YARN, Mesos, and Project Myriad (initiated/sponsored by MapR). One on hand it seems that this is just about some evolution of the Hadoop scheduling layer, but looking at with a critical eye, I see the impending culmination of what I predicted years ago - that the Hadoop ecosystem will quickly evolve to bring high-powered HPC technologies right into the heart of the next gen enterprise data center.

  • Premiered: 02/19/15
  • Author: Mike Matchett
Topic(s): MapR Big Data YARN Hadoop Mesos Scheduling Project Myriad
news

Hadoop Storage Options: Time to Ditch DAS?

Hadoop is immensely popular today because it makes big data analysis cheap and simple: you get a cluster of commodity servers and use their processors as compute nodes to do the number crunching, while their internal direct attached storage (DAS) operate as very low cost storage nodes.

  • Premiered: 02/19/15
  • Author: Taneja Group
  • Published: Infostor
Topic(s): TBA Hadoop TBA Storage TBA DAS TBA Direct attached storage TBA Compute TBA SATA TBA HDFS TBA Hadoop Distributed File System TBA data TBA MapReduce TBA YARN TBA Hadoop 2 TBA data lake TBA data refinery TBA Enterprise Storage TBA DR TBA Disaster Recovery TBA compliance TBA Security TBA Business Continuity TBA Performance TBA FC TBA Fibre Channel TBA SAN TBA NAS TBA Virtualization TBA Cloud TBA VM TBA Virtual Machine TBA MapR
news

Data lakes swim with golden information for analytics

First we had data. Then we had big data. Now we have data lakes. Will the murky depths prove bountiful?

  • Premiered: 04/14/15
  • Author: Mike Matchett
  • Published: TechTarget: Search Data Center
Topic(s): TBA data lake TBA analytics TBA Big Data TBA Mike Matchett TBA TechTarget TBA Hadoop TBA Business Intelligence TBA BI TBA OLAP TBA OLTP TBA NoSQL TBA SQL TBA Optimization TBA ETL TBA IoT TBA Internet of Things TBA MapR TBA Project Myriad TBA YARN TBA Virtualization TBA Business Continuity TBA Disaster Recovery TBA DR TBA BC TBA data swamp TBA BlueData TBA Dataguise TBA HDFS TBA Hadoop Distributed File System TBA IBM
news

Big data analytics applications impact storage systems

Analytics applications for big data have placed extensive demands on storage systems, which Mike Matchett says often requires new or modified storage structures.

  • Premiered: 09/03/15
  • Author: Mike Matchett
  • Published: TechTarget: Search Storage
Topic(s): TBA Mike Matchett TBA Big Data TBA analytics TBA Storage TBA Primary Storage TBA scalability TBA Business Intelligence TBA BI TBA AWS TBA Amazon AWS TBA S3 TBA HPC TBA High Performance Computing TBA High Performance TBA ETL TBA HP Haven TBA HP TBA Hadoop TBA Vertica TBA convergence TBA converged TBA IOPS TBA Capacity TBA latency TBA scale-out TBA software-defined TBA software-defined storage TBA SDS TBA YARN TBA Spark
Profiles/Reports

Now Big Data Works for Every Enterprise: Pepperdata Adds Missing Performance QoS to Hadoop

While a few well-publicized web 2.0 companies are taking great advantage of foundational big data solution that they have themselves created (e.g. Hadoop), most traditional enterprise IT shops are still thinking about how to practically deploy their first business-impacting big data applications – or have dived in and are now struggling mightily to effectively manage a large Hadoop cluster in the middle of their production data center. This has led to the common perception that realistic big data business value may yet be just out of reach for most organizations – especially those that need to run lean and mean on both staffing and resources.   

This new big data ecosystem consists of scale-out platforms, cutting-edge open source solutions, and massive storage that is inherently difficult for traditional IT shops to optimally manage in production – especially with still evolving ecosystem management capabilities. In addition, most organizations need to run large clusters supporting multiple users and applications to control both capital and operational costs. Yet there are no native ways to guarantee, control, or even gain visibility into workload-level performance within Hadoop. Even if there wasn’t a real high-end skills and deep expertise gap for most, there still isn’t any practical way that additional experts could tweak and tune mixed Hadoop workload environments to meet production performance SLA’s.

At the same time, the competitive game of mining of value from big data has moved from day-long batch ELT/ETL jobs feeding downstream BI systems, to more user interactive queries and business process “real time” applications. Live performance matters as much now in big data as it does in any other data center solution. Ensuring multi-tenant workload performance within Hadoop is why Pepperdata, a cluster performance optimization solution, is critical to the success of enterprise big data initiatives.

In this report we’ll look deeper into today’s Hadoop deployment challenges and learn how performance optimization capabilities are not only necessary for big data success in enterprise production environments, but can open up new opportunities to mine additional business value. We’ll look at Pepperdata’s unique performance solution that enables successful Hadoop adoption for the common enterprise. We’ll also examine how it inherently provides deep visibility and reporting into who is doing what/when for troubleshooting, chargeback and other management needs. Because Pepperdata’s function is essential and unique, not to mention its compelling net value, it should be a checklist item in any data center Hadoop implementation.

To read this full report please click here.

Publish date: 12/17/15
news

Mobile gaming company plays new Hadoop cluster management card

Chartboost, which operates a platform for mobile games, turned to new cluster management software in an effort to overcome problems in controlling the use of its Hadoop processing resources.

  • Premiered: 01/05/16
  • Author: Taneja Group
  • Published: TechTarget: Search Data Management
Topic(s): TBA Chartboost TBA mobile TBA cluster TBA Cluster Management TBA Hadoop TBA processing TBA data processing TBA analytics TBA Big Data TBA MapReduce TBA Hive TBA Spark TBA Optimization TBA Cloudera TBA AWS TBA Amazon TBA Cloud TBA YARN TBA Pepperdata TBA Memory TBA CPU TBA Application TBA Concurrent TBA SLA TBA service-level agreement TBA HBase TBA application performance TBA application performance management TBA Mike Matchett
news

It’s 3 a.m. — Do You Know What Your Cluster’s Doing?

Performance challenges in Hadoop environments are par for the course as organizations attempt to capture the benefits of big data.

  • Premiered: 07/20/16
  • Author: Taneja Group
  • Published: Enterprise Tech
Topic(s): TBA Mike Matchett TBA Hadoop TBA cluster TBA Big Data TBA big data analytics TBA QoS TBA HBase TBA ETL TBA SLA TBA ROI TBA Performance Management TBA YARN TBA Hadoop 2 TBA Mesos TBA OpenStack TBA Docker