Spark Monitoring
Details
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MEETUP TOPIC
Spark is an open-source cluster computing framework that runs in-memory to provide performance up to 100 times faster than MapReduce for certain applications. By allowing user programs to load data into a cluster's memory and query it repeatedly, Spark is well suited to machine learning algorithms and interactive analytics.
You need to monitor Spark to get the best performance and to avoid issues. Learn how you can gain real-time insight into Spark jobs across CPU, RAM, I/O and network.
The main discussion will be held in the form of a panel with distinguished Spark experts in Silicon Valley. Hear how they are monitoring
Spark jobs, the biggest challenges, best practices and real life use cases.
We will be raffling off an iPad mini at the end of the session so be sure to drop your business card off at registration desk.
AGENDA
6:00 Arrive – Drinks, heavy appetizers, networking
6:30 Kickoff – Introductions
6:45 Spark Monitoring
7:00 Panel Discussion
7:45 Audience Questions and Apple iPad Mini Giveaway!
PANELISTS
Asrith Mekala - Solutions Architect
Lieman Soewito - Manager, Software Development & Data Platform Lead
Brock Nolan - Software Engineer
Shahank Bharadwaj - Big Data Administrator
Paul Ho -Principal Engineer
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Alex Pierce - Field Engineer & Panel Moderator
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Spark Monitoring