This document outlines lessons learned from running HDFS on Kubernetes, covering key topics such as Kubernetes architecture, integration with big data tools like Spark, and the importance of data locality in enhancing performance. It details the challenges faced, including data locality issues and the solutions implemented to improve task execution efficiency. The document also encourages collaboration and further inquiries, providing links to relevant resources and career opportunities.

1. Kimoon Kim (kimoon@pepperdata.com)
HDFS on Kubernetes --
Lessons Learned

2. Outline
1. Kubernetes intro
2. Big Data on Kubernetes
3. Demo
4. Problems we fixed -- HDFS data locality

3. Kubernetes
New open-source cluster manager.
Runs programs in Linux containers.
1000+ contributors and 40,000+ commits.

4. “My app was running fine
until someone installed
their software”

5. More isolation is good
Kubernetes provides each program with:
• a lightweight virtual file system
– an independent set of S/W packages
• a virtual network interface
– a unique virtual IP address
– an entire range of ports
• etc

6. Kubernetes architecture
node A node B
Pod 1 Pod 2 Pod 3
10.0.0.2
196.0.0.5 196.0.0.6
10.0.0.3 10.0.1.2
Pod, a unit of scheduling and isolation.
• runs a user program in a primary container
• holds isolation layers like an virtual IP in an infra container

7. Big Data on Kubernetes
github.com/apache-spark-on-k8s
• Google, Haiwen, Hyperpilot, Intel, Palantir, Pepperdata, Red Hat,
and growing.
• patching up Spark Driver and Executor code to work on
Kubernetes.
Yesterday’s talk:
spark-summit.org/2017/events/apache-spark-on-kuberne
tes/

8. Spark on Kubernetes
node A node B
Driver Pod Executor Pod 1 Executor Pod 2
10.0.0.2
196.0.0.5 196.0.0.6
10.0.0.3 10.0.1.2
Client
Client
Driver Pod Executor Pod 1 Executor Pod 2
10.0.0.4 10.0.0.5 10.0.1.3
Job 1
Job 2

9. What about storage?
Spark often stores data on HDFS.
How can Spark on Kubernetes access HDFS data?

10. Hadoop Distributed File System
Namenode
• runs on a central cluster node.
• maintains file system metadata.
Datanodes
• on every cluster node.
• read and write file data on local disks.

11. HDFS on Kubernetes
node A node B
Driver Pod Executor Pod 1 Executor Pod 2
10.0.0.2
196.0.0.5 196.0.0.6
10.0.0.3 10.0.1.2
Client
Client
Driver Pod Executor Pod 1 Executor Pod 2
10.0.0.4 10.0.0.5 10.0.1.3
Job 1
Job 2
Namenode Pod Datanode Pod 1 Datanode Pod 2
HDFS
hadoop.fs.defaultFS
hdfs://hdfs-namenode-0.hdfs-namenode.default.svc.cluster.local:8020

12. Demo
1. Label cluster nodes
2. Stand up HDFS
3. Launch a Spark job
4. Check Spark job output

13. What about data locality?
• Read data from local disks when possible
• Remote reads can be slow if network is
slow
• Implemented in HDFS daemons, integrated
with app frameworks like Spark
Client 2
node B
Client 1
node A
Datanode 1 Datanode 2
SLOWFAST

14. HDFS data locality in YARN
Spark driver sends tasks to right executors with tasks’ HDFS data.
Driver
Executor 1 Executor 2
/fileA /fileB
Read /fileA
Read /fileB
(/fileA → Datanode 1 → 196.0.0.5) == (Executor 1 →196.0.0.5)
Datanode 1 Datanode 2
node A
196.0.0.5
node B
196.0.0.6
Job 1
HDFS
YARN example

15. Hmm, how do I find right executors in Kubernetes...
(/fileA → Datanode 1 → 196.0.0.5) != (Executor 1 → 10.0.0.3)
Executor Pod 2
10.0.1.2
Driver Pod Executor Pod 1
10.0.0.2 10.0.0.3
Read /fileB
Read /fileA
/fileA /fileB
Datanode Pod 1
node A
196.0.0.5
node B
196.0.0.6
Kubernetes example
Datanode Pod 2

16. Fix Spark Driver code
1. Ask Kubernetes master to find the cluster node where
the executor pod is running.
2. Get the node IP.
3. Compare with the datanode IPs.

17. Rescued data locality
Executor Pod 2
10.0.1.2
Driver Executor Pod 1
10.0.0.2 10.0.0.3
(/fileA → Datanode 1 → 196.0.0.5) == (Executor 1 →10.0.0.3 → 196.0.0.5)
Read /fileA
Read /fileB
/fileA /fileB
node A
196.0.0.5
node B
196.0.0.6
Datanode Pod 1 Datanode Pod 2

18. Rescued data locality!
with data locality fix
- duration: 10 minutes
without data locality fix
- duration: 25 minutes

20. Recap
Got HDFS up and running.
Basic data locality works.
Open problems:
• Remaining data locality issues -- rack locality, node preference, etc
• Kerberos support
• Namenode High Availability

21. Join us!
● github.com/apache-spark-on-k8s
● pepperdata.com/careers/
More questions?
● Come to Pepperdata booth #101
● Mail kimoon@pepperdata.com