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Pachyderm:
Data Storage and Processing with Docker
Joe Doliner
Founder & CEO
jd@pachyderm.io
Adroll’s Architecture
Amazon
S3
Luigi
Storage Scheduler Packaging
Docker
Storage Scheduler Packaging
Docker
• Open source
• Generalized for different use cases
• End-to-end solution
• Leverages Docker ecosystem
Pachyderm
Pipeline
System
(pps)
Pachyderm
File
System
(pfs)
Adroll’s Archiecture for everyone else
What is PFS?
A copy-on-write distributed file system
Core storage for Pachyderm
What is PFS?
Copy-on-write is the paradigm that “powers”
technologies like Docker and Spark
Why is this cool?
• View diffs of your data
• Instantly revert to previous state
• Immutability
• Reduce storage needs
• Branching Commit
0
Commit
1
Commit
2
Commit
3
Commit
4
Git for huge data sets
What is PPS?
• Schedules dependency graph
• Manages containerized pipelines
• Understands copy-on-write storage
Task 1
Task 2 Task 3
Task 4
Dashboard
Task 5
Task 6
PPS + PFS is…
Efficient: incremental processing
3
2
1
0
Data Analysis
Task 4
DashboardTask 6
Task 1
Task 2 Task 3
Task 5
1% more
data
Task 4
DashboardTask 6
Only process jobs
that rely on the
data that changed
PPS + PFS is…
Flexible: both batched pipelines and streaming
Daily batched
pipelines
Data Analysis
Task 4
DashboardTask 6
Task 1
Task 2 Task 3
Task 5
1
0
∆Time = 1 day
2
Large batched DAG
that processes all the
new data each day
PPS + PFS is…
Flexible: both batched pipelines and streaming
Data Analysis
Task 4
DashboardTask 6
Task 1
Task 2 Task 3
Task 5
2
1
0
Streaming
updates
3
∆Time = 1 second
4
Micro-batches that
update constantly as
new data streams in
Commits are insanely
cheap so you can take
one every second
PPS + PFS is…
Task 1
Task 2 Task 3
Task 4
Dashboard
Task 5
Task 6
$ Task 2 failed
$ Task 4 and 6 waiting…
… Fixing code …
$ Task 2 resuming...
$ Task 2 complete!
$ Task 4 starting…
Monitoring
Resilient: seamless pipeline restarts
PPS + PFS is…
PFS storage
nodes
PPS
Copy-on-write
storage nodes
Elastically scaling
computation nodes
Cost-effective: resource management through
delayed execution
d2.8xlarge
PPSPPS
PPS
Spot
SpotSpotElastically add spot
instances when prices are
cheap or needs are high
PPS + PFS is…
PFS storage
nodes
PPS
Copy-on-write
storage nodes
Elastically scaling
computation nodes
Cost-effective: resource management through
delayed execution
d2.8xlarge
PPSPPS
PPS
Spot
SpotSpot
S3
Slow/cheap
storage
Back up data to S3
for long-term storage
or “cold” data
Summary
• Container ecosystem is powerful
• Copy-on-write data is really powerful
• Containers plus copy-on-write is insanely powerful
Thank You!
Questions?
Pachyderm.io
jd@pachyderm.io

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Pachyderm: Data Storage and Processing with Docker

  • 1. Pachyderm: Data Storage and Processing with Docker Joe Doliner Founder & CEO jd@pachyderm.io
  • 3. Storage Scheduler Packaging Docker • Open source • Generalized for different use cases • End-to-end solution • Leverages Docker ecosystem Pachyderm Pipeline System (pps) Pachyderm File System (pfs) Adroll’s Archiecture for everyone else
  • 4. What is PFS? A copy-on-write distributed file system Core storage for Pachyderm
  • 5. What is PFS? Copy-on-write is the paradigm that “powers” technologies like Docker and Spark
  • 6. Why is this cool? • View diffs of your data • Instantly revert to previous state • Immutability • Reduce storage needs • Branching Commit 0 Commit 1 Commit 2 Commit 3 Commit 4 Git for huge data sets
  • 7. What is PPS? • Schedules dependency graph • Manages containerized pipelines • Understands copy-on-write storage Task 1 Task 2 Task 3 Task 4 Dashboard Task 5 Task 6
  • 8. PPS + PFS is… Efficient: incremental processing 3 2 1 0 Data Analysis Task 4 DashboardTask 6 Task 1 Task 2 Task 3 Task 5 1% more data Task 4 DashboardTask 6 Only process jobs that rely on the data that changed
  • 9. PPS + PFS is… Flexible: both batched pipelines and streaming Daily batched pipelines Data Analysis Task 4 DashboardTask 6 Task 1 Task 2 Task 3 Task 5 1 0 ∆Time = 1 day 2 Large batched DAG that processes all the new data each day
  • 10. PPS + PFS is… Flexible: both batched pipelines and streaming Data Analysis Task 4 DashboardTask 6 Task 1 Task 2 Task 3 Task 5 2 1 0 Streaming updates 3 ∆Time = 1 second 4 Micro-batches that update constantly as new data streams in Commits are insanely cheap so you can take one every second
  • 11. PPS + PFS is… Task 1 Task 2 Task 3 Task 4 Dashboard Task 5 Task 6 $ Task 2 failed $ Task 4 and 6 waiting… … Fixing code … $ Task 2 resuming... $ Task 2 complete! $ Task 4 starting… Monitoring Resilient: seamless pipeline restarts
  • 12. PPS + PFS is… PFS storage nodes PPS Copy-on-write storage nodes Elastically scaling computation nodes Cost-effective: resource management through delayed execution d2.8xlarge PPSPPS PPS Spot SpotSpotElastically add spot instances when prices are cheap or needs are high
  • 13. PPS + PFS is… PFS storage nodes PPS Copy-on-write storage nodes Elastically scaling computation nodes Cost-effective: resource management through delayed execution d2.8xlarge PPSPPS PPS Spot SpotSpot S3 Slow/cheap storage Back up data to S3 for long-term storage or “cold” data
  • 14. Summary • Container ecosystem is powerful • Copy-on-write data is really powerful • Containers plus copy-on-write is insanely powerful

Editor's Notes

  1. Git centered with graphic (no branch) Then bullets + branch
  2. PPS knows what data has changed and only recomputes tasks that rely on that diff
  3. Use docker monitoring tools
  4. Cost-effective becomes important when you’re managing a huge cluster Just text, then storage nodes and small pps. Then big pps. Then s3. And you can back to S3 to get the best of both worlds.
  5. Cost-effective becomes important when you’re managing a huge cluster Just text, then storage nodes and small pps. Then big pps. Then s3. And you can back to S3 to get the best of both worlds.