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
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
Akshay Rai
@akshayrai
Submitted Apr 28, 2017
Do you want to know the real-time status of your big data job? Not sure of how to collect all the metrics from these jobs and make sense out of them? Want to track and monitor the metrics in real time? Want to track the historical performance of your job? Want to build business reporting dashboards?
The Big Data world has a variety of frameworks to run Hadoop and Spark jobs and tracking these jobs in real time is a huge challenge. The frameworks have kept on increasing but very few attempts have been made to comprehensively monitor these jobs and optimize them.
In this talk, we will discuss a framework to collect and stream big data metrics from different sources in real time, capture them in a metrics OLAP store, run analytics, monitor and alert on them.
The Problem:
For a company like Linkedin, where we run thousands of production BigData workflows, it is important to dedicate enough resources to all the critical workflows. It is also important from a business perspective that these flows don’t waste the resources. In such a scenario it is very crucial to have a system which can easily help visualize all the Workflow metrics and help monitor, debug and optimize the workflows. In addition, it would be really cool if we as developers get automatically alerted when something goes wrong in the workflow like the output records suddenly dropped or there was a spike in the delay and then do slice and dice over the individual delays and figure out what caused it. Whether it was the workflow itself that had an issue or was it due to heavy load on the cluster?
The Design:
We will discuss the architecture and design for building such a near realtime framework that includes components like Apache Kafka, Samza and OLAP stores. We will also discuss the scope of such a Big Data Metrics store and how consumers like Dr. Elephant can consume from such Metrics Stores and do a lot of analytic processing on them and potentially also auto-tune the jobs based on some models.
Akshay Rai is an engineer at Linkedin working with the Grid team. He is also the lead engineer for the open sourced Dr. Elephant project by Linkedin. He has been working on solutions to improve the developer productivity and building systems to monitor Big Data applications in real time.
https://drive.google.com/file/d/0BzdEJVP7_lZjdEpRMmJCaXRVQzQ/view?usp=sharing
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
Hosted by
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