Big Data Applications

•

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Pachyderm is a big data analytics platform deployed with Kubernetes and Docker. Pachyderm is inspired by the Hadoop ecosystem but shares no code with it. Instead, we leverage the container ecosystem to provide the broad functionality of Hadoop with the ease of use of Docker.

Data & Analytics

Pachyderm
Big Data Applications with Containers
Joe Doliner
Founder & CEO
jd@pachyderm.io

What is Pachyderm?
Big data with Containers
• Version control for data
• Uses containers for data processing
• Batched and streaming
• Data lives in object storage (S3, GCS, Ceph)
• Shares no code with Hadoop

Intro to Containers
• What are containers and why are they
useful for Big Data Applications?
• What is Kubernetes and why is it useful
for Big Data Application?

Version Control for Data
• View diffs of data
• Collaboration
• Data provenance
Commit
0
Commit
1
Commit
2
Commit
3
Commit
4
Git for huge data sets

Containerized Data Pipelines
• DAG of jobs
• Pipelines triggered by data
changes
• Processing efficiency
• Incrementality
Task 1
Task 2 Task 3
Task 4
Dashboard
Task 5
Task 6

Data Lake Use Case
Production
databases
Application
Pachyderm
Object storage
Pachyderm Pipelines
Data
Warehouse
Pachyderm File System

Demo:
• Start Pachyderm on K8s
• Add data
• Create pipeline
• Incrementally update steaming results
Steaming data pipelines

Thank You!
Questions?
pachyderm.io
jd@pachyderm.io
github.com/pachyderm/pachyderm

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