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1
Intro
2
Outline
3
Big Data History Cont.
4
Big Data Stack
5
Big Data Trend
6
Benefit of Containerization
7
Kubernetes Architecture
8
Challenges
9
CSI(Container Storage Interface)
10
CSI Core Services
11
CSI Advance Features
12
Volume Lifecycle Volume Lifecycle
13
Controller and Node Services
14
Kubernetes Storages
15
Kubernetes CSI Support
16
PV, PVC and Storage Class
17
Package and Deployment Suggestion
18
Hadoop HDFS
19
HDFS Cluster Scale
20
Apache Ozone
21
HDFS/Ozone as PV
22
HDFS Characteristics as PV
23
HDFS NFS Gateway CSI
24
Ozone CSI
25
Resources
Description:
Explore the integration of Kubernetes with on-premises big data clusters through this conference talk. Learn about the HDFS CSI Plugin design and architecture, addressing the challenge of consuming HDFS data with Kubernetes. Discover best practices for running Spark workloads on Kubernetes with HDFS access using the CSI plugin. Examine performance comparisons between Spark on Kubernetes with HDFS and Spark on YARN with HDFS using the TPC-DS benchmark suite. Gain insights into big data history, containerization benefits, Kubernetes architecture, CSI core services, volume lifecycle management, and Hadoop HDFS characteristics as persistent volumes. Understand the potential of Kubernetes as an alternative to Hadoop YARN for resource scheduling in on-premises big data environments.

HDFS CSI Plugin: Speeding Up Kubernetes in On-Premises Big Data Clusters

Linux Foundation
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