Hadoop Multi-Tenancy and Cluster Resource Scheduling at Scale
How do you create a shared infrastructure for Hadoop that fosters rapid enterprise-wide deployment and ensures a big return on your investment?
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"If we didn't have Grid Engine it would be a major investment to go live with Aggregator and Hadoop."
Katrina Montinola, Archimedes
MapR and Univa have teamed up to provide a foundation for scalable workload management that delivers advanced resource sharing policies, job prioritization, multi-tenant access, and granular cluster management to enterprises.
Learn how MapR's distribution for Hadoop and Univa Grid Engine provide enterprises with an optimized architecture - saving you money on hardware while at the same time simplifying your operation of cluster resources.
You will learn:
If you're looking to improve the effectiveness of your pipeline with data management tools like Hadoop while saving up to half of the investment with a production-ready solution then this webinar is for you.
Univa Grid Engine creates a shared infrastructure that easily unifies Big Compute and Big Data workload management making it possible to fully leverage shared cluster resources with support for innovations like Hadoop automation, multi-core systems, hybrid servers and cloud computing. Ensure your organization is future-proofed today with Univa.
Alan Geary, Sr. Director of Business Development at MapR, is responsible for Technology Alliances. Working with the best partners that customers see value in is one of the things that sets MapR apart from other distributions.
Fritz Ferstl, Chief Technology Officer and Business Development for EMEA at Univa. Fritz is also the father of Grid Engine and a veteran in all aspects of Grid and Cloud workload management.