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Introduction
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Traditional approach
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DCOS
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Trinity
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Project Trinity
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Examples
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Temporal Operators
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Aggregate Points
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Aggregate Bins
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Demo
11
Deployment Portability
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Deploy across different environments
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Installing DCOS
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Installing Kafka
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Installing Elasticsearch
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Kafka Source
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Map Interface Demo
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Simulations
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Challenges
20
Open Source Extensions
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Autoscaling
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Metrics
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Stateful Processing
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Batch Analysis
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Recurring Analytics
Description:
Explore how DC/OS and Mesos enable massive-scale geospatial analytics using Kafka, Spark, and Elasticsearch in this 41-minute conference talk by Adam Mollenkopf from Esri. Discover Esri's approach to establishing a foundational operating environment for high-velocity IoT data consumption, streaming analytics, and high-volume spatiotemporal data storage and querying. Learn about making DC/OS applications portable across public cloud providers, private cloud providers, and on-premise environments. Gain insights into real-time and big data capabilities in the ArcGIS platform through demonstrations and examples of temporal operators, aggregate points, and aggregate bins. Understand the deployment process, including installing DC/OS, Kafka, and Elasticsearch, and explore challenges such as autoscaling, metrics, stateful processing, and recurring batch analytics using Apache Spark and Metronome.

Applying Geospatial Analytics at a Massive Scale Using Kafka, Spark and Elasticsearch on DC/OS

Linux Foundation
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