Главная
Study mode:
on
1
Introduction
2
Agenda
3
Spark Use Cases
4
YARN in 2018
5
Scaling
6
Challenges
7
Image Management
8
Hybrid Approach
9
Hybrid Architecture
10
Hybrid Architecture Advantages
11
Spark Operator
12
Image Hierarchy Distribution
13
Recap
14
Improvements
15
Future Plans
16
Takeaways
Description:
Explore a 44-minute conference talk from Databricks detailing Lyft's innovative hybrid Apache Spark architecture utilizing YARN and Kubernetes. Dive into the challenges faced by Lyft when scaling their Batch ETL and ML spark workloads on Kubernetes, and discover the hybrid solution developed to optimize both containerized and non-containerized workloads. Learn about the dynamic runtime controller for environment-specific configurations and seamless resource manager switching. Gain insights into Spark use cases, scaling challenges, image management, and the advantages of the hybrid approach. Examine the Spark Operator, image hierarchy distribution, and recent improvements. Conclude with future plans and key takeaways for implementing a robust Spark architecture in large-scale transportation technology environments.

Hybrid Apache Spark Architecture: Optimizing YARN and Kubernetes for Lyft's Workloads

Databricks
Add to list
0:00 / 0:00