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In the session, we will provide you with some tips on tuning clusters based on monitoring and suggestions for best practices in Spark configuration.

We will explore how to optimize resource utilization, reduce job execution time, and improve overall stability of your workloads on Amazon EMR. You will learn how to identify bottlenecks using performance metrics, apply the right configuration to executors and memory, and leverage autoscaling and cost saving strategies.
By the end, you will walk away with actionable techniques to boost performance and lower cloud spend without compromising data reliability.

Language- Hebrew

Speaker: Omid Vahdaty
Omid is the Founder and CTO of Jutomate, a company that provides services and solutions in data, cloud, and AI.

He is an expert in data architecture, product innovation, and strategic engineering thinking, with over 20 years of experience across startups, global enterprises, and government organizations.

Amazon Elastic MapReduce (Amazon EMR)
Amazon Web Services
Apache Spark
Big Data
Cloud Cost Management

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