Presentation from AWS re: Invent, where Mortar announced it's public availability on stage. Mortar facilitates Hadoop data development in two parts: an open source data development framework (like Rails for Hadoop) and a PaaS (like Heroku for Hadoop). The open source framework allows for sharing/repeating/maintaining code history, automated testing, and one-button deploy. The PaaS provides high availability execution, full job history, and helps users identify problems.

2. Open-source software
development frameworks

3. Open-source software dev frameworks
(and many more...)

4. Every platform needs
open-source,
code-based dev frameworks
• Avoid repeat work
• Remain 100% customizable
• Escape vendor lock-in

5. But for data?
Nothing.

6. Data work today
• Proprietary / GUI / No framework
• Not reusable
• Little collaboration
• Too many errors, too slow to fix

7. an open source dev framework for data

8. “Mortar takes something complex
and makes it simple and intuitive.”
—Jon Coveney, Twitter

9. What big data system should I use? Hadoop, HPCC, Disco, Storm…
What Hadoop distro should I use?
How much will this cost? Should I do it some other way?
How long is this going to take to learn? Should I do it some other way?
How many machines should I buy?
Can I run in the cloud?
How should I interact with it? Pig, Hive, Cascading, Scalding, Cascalog
Weeks
Can I use libraries I need?
How do I install everything?
How can my team share code?
How can I reuse code?
Is my workload typical?
How can I safely deploy?
How do I know if what I've written is correct?
Are there any libraries I could start with?
Can I connect to my key-value store?
Can I do machine learning in Hadoop?
Is it secure?
What if I need help?

10. More Weeks

11. Even More Weeks

12. —Alan Gates, Hortonworks co-founder
OPEN SOURCED PIG
“Our focus in designing Pig has always been to
make Hadoop easy...
Mortar's approach is right on—they extend our
quick start and ease of use focuses with pre-
built Hadoop clusters, clear examples, code
organization templates, and github for social
sharing of the code.”

13. Can Mortar help you?
Mortar is for analyzing lots of data in AWS.

14. Who is Mortar for?
Mortar serves companies of all sizes from any
industry.

15. —Dwight Merriman
FOUNDER OF 10GEN (MAKER OF MONGODB), DOUBLECLICK (ACQ.
GOOGLE), SHOPWIKI, BUSINESS INSIDER, GILT GROUPE
“...Mortar fits right in with our vision of the
future...
With this exciting launch, MongoDB users can
now also seamlessly use Mortar.”

16. By and for engineers
and data scientists

17. > gem install mortar

18. > mortar new my_project

20. > git clone your_project

21. > mortar run your_project

24. Pig is easy to learn
(and we’ve made it easier)

27. Illustrate is awesome
• Find your mistakes
• Understand code before collaborating
• Automated tests: a way to test every condition

28. Hadoop & Python are powerful data science tools

29. ...but they haven’t worked together before.

30. Now you can use Hadoop & real Python on Mortar

33. What you just saw
• Installed Mortar
• Made a new project
• Cloned a project
• Ran the project
• Illustrated project
• Use Python and other libraries on Hadoop

34. 2 options for using Mortar:
- Git Projects: modularity, testability, code
sharing, local dev, and revision control.
- Web Projects: zero install, in the browser

36. One-hour challenge
• Use your browser
• Minutes to connect data
• Productive in one hour

37. How does Mortar fit with other
As a good citizen, Mortar has a rich API

38. How about speed?
Full speed, directly on Hadoop

39. Mortar revolutionizes
your data pipeline.
• Easy start
• Keeps you productive
• Collaborate with data
• No lock-in
• Easy to budget

40. Tiers
• Free | Service use unlimited | 10 node-hours
• Pay as you Go | $0.89/node-hour | support
• Enterprise | $3,000/month | $0.69/node-hour | live
support

42. mortardata.com / @mortardata