Webinar: Proven Approaches to Hive Query Tuning

Webinar: Proven Approaches to Hive Query Tuning

Eliminate Manual Tuning and Save

Pepperdata Capacity Optimizer automatically optimizes your big data cluster resources and recaptures wasted capacity so you can run more applications and get the most out of your infrastructure investment.
Capacity Optimizer enables you to:

  • Experience up to 50% more throughput than with AWS autoscaling.
  • Recapture wasted capacity so you can run more applications and get the best ROI from your infrastructure investment.
  • Optimize each node’s ability to run an optimal number of containers and run the same number of workloads on fewer instances.
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Improve Big Data Cluster Throughput Up to 50%

By monitoring the entire infrastructure in real time and leveraging active resource management, Capacity Optimizer identifies where more work can be done and adds tasks to servers with available resources. On a typical cluster, Capacity Optimizer makes thousands of decisions per second on how to best optimize your big data clusters. Even the most experienced operator can’t make manual configuration changes at this precision and speed.

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Reduce Amazon EMR Costs

Cloud providers provision infrastructure based on the peak needs of workloads. This guarantees the maximums are met, but can create a lot of waste. Capacity Optimizer makes thousands of decisions per second, analyzing the resource usage of each node in real time to optimize the utilization of CPU, memory, and I/O resources on big data clusters. The net effect is that horizontal scaling is optimized and waste is eliminated.

Capacity Optimizer for Amazon EMR is available on AWS Marketplace as part of Pepperdata Cloud. In addition to automatically tuning your cloud deployment for optimal performance, get full-stack observability, automated tuning, and real-time insights across your entire Amazon EMR—all in one place. Automatically optimize your big data and deliver superior application performance.

  • Get full-stack observability, automated tuning, and job-specific recommendations for Spark and MapReduce.
  • Automatically optimize node performance and prevent waste by applications.
  • Customize alerts to quickly understand and troubleshoot application and infrastructure issues.

Benefits for Your Team

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Operation Teams

  • Ensure big data cluster stability and efficiency.
  • Avoid overspending on hardware.
  • Reduce time spent on capacity planning.
  • Run more jobs on existing infrastructure.
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Application Teams

  • Run more jobs.
  • Access additional cluster capacity.
  • Spend less time in backlog queues.
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Business Teams

  • Report on capacity trends.
  • Get accurate chargeback reporting.
  • Increase productivity. Improve ROI.
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Take a Free Thirty-Day Trial to See What Big Data Success Looks Like

Pepperdata products provide complete visibility and automation for your big data environment. Get the observability, automated tuning, recommendations, and alerting you need to efficiently and autonomously optimize big data environments at scale.