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1
Introduction
2
Data is overwhelming
3
Interaction patterns
4
Buffers
5
Guarantees
6
Exactly once
7
Initial Collection Tier
8
Analysis Tier
9
Continuous Queries
10
Time Constraints
11
Other Topics
12
Data Access Theory
13
Openshift
14
Kubernetes
15
Vertex
16
Erics Java
17
FinishPlan
18
Demo
19
Google Maps
Description:
Explore critical patterns and principles for handling overwhelming amounts of real-time, streaming data in this 42-minute conference talk from Devoxx. Learn how to combine tools, platforms, and strategies to achieve greater scale and response speed when dealing with massive data volumes. Discover how an In-Memory Data Grid like Infinispan and a platform like Kubernetes can leverage these concepts to create a state-of-the-art distributed data processing architecture. Gain insights into interaction patterns, buffers, guarantees, and tiered analysis approaches. Watch a live demo showcasing the implementation of these principles, and delve into topics such as data access theory, OpenShift, Kubernetes, Vertex, and Google Maps integration.

Principles and Patterns for Streaming Data Analysis

Devoxx
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