The Fifth Elephant 2017
On data engineering and application of ML in diverse domains
Jul 2017
24 Mon
25 Tue
26 Wed
27 Thu 08:15 AM – 10:00 PM IST
28 Fri 08:15 AM – 06:25 PM IST
29 Sat
30 Sun
##Theme and format
The Fifth Elephant 2017 is a four-track conference on:
The Fifth Elephant is a conference for practitioners, by practitioners.
Talk submissions are now closed.
You must submit the following details along with your proposal, or within 10 days of submission:
##About the conference
This year is the sixth edition of The Fifth Elephant. The conference is a renowned gathering of data scientists, programmers, analysts, researchers, and technologists working in the areas of data mining, analytics, machine learning and deep learning from different domains.
We invite proposals for the following sessions, with a clear focus on the big picture and insights that participants can apply in their work:
##Selection Process
We will notify you if we move your proposal to the next round or reject it. A speaker is NOT confirmed for a slot unless we explicitly mention so in an email or over any other medium of communication.
Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.
There is only one speaker per session. Entry is free for selected speakers.
##Travel grants
Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.
##Commitment to Open Source
We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.
##Important Dates:
##Contact
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.
Hosted by
Ragesh Rajagopalan
@rajagopr
Submitted Apr 30, 2017
Continuous deployment of hadoop workflows is by and large a distant dream for every hadoop engineer. Reducing wastage of compute resources, improving developer productivity, eliminating costly bugs and avoiding data corruption are basic goals for every deployment. Yet, often times these goals are not achieved due to lack of comprehensive test coverage and standard best practices. This in-turn results in non-availability of critical data for downstream applications. Further, there is huge room for improving developer happiness which is a direct function of speed of deployments and ease of rollback mechanisms. If only Hadoop workflows could benefit from standard best practices such as code reviews, unit tests, test deployments etc that are followed for online services, the dream of continuous deployment can become a reality.
In this talk, we discuss in detail about how we have made this dream a reality by taking every release candidate through the various phases of the software development life cycle.
We will discuss about leveraging internal and open-sourced tools to ensure disciplined, quick and quality deployments
Discipline:
Treating every commit as a release candidate ; Testing with datamock (internal tool) ; Deploying to a test cluster before deploying to prod
Quality:
Executing flows in Azkaban (open-sourced) ; Determining health of your flows from Dr. Elephant
Speed:
One click deployment with CRT(internal tool)
None
I’m currently working as a Senior Software Engineer at LinkedIN responsible for the development of tools and applications to improve developer productivity. I have around 12 years for experience in the software industry with significant experience in payments and ecommerce platforms. For the last one and half years I have been working with the data team at linkedIN and have contributed to opensource projects like Dr. Elephant and Azkaban.
I was reponsible for enabling continous integration for hadoop and spark applications at LinkedIN bringing them at-par with the online services.
https://docs.google.com/presentation/d/1wbEK17IjV0hUUXbM8Ay5buhvbtWFbsK9kVi6o55EbNs/edit?usp=sharing
Hosted by
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