The Fifth Elephant

The Fifth Elephant 2015

A conference on data, machine learning, and distributed and parallel computing

Machine Learning, Distributed and Parallel Computing, and High-performance Computing are the themes for this year’s edition of Fifth Elephant.

The deadline for submitting a proposal is 15th June 2015

We are looking for talks and workshops from academics and practitioners who are in the business of making sense of data, big and small.

Track 1: Discovering Insights and Driving Decisions

This track is about general, novel, fundamental, and advanced techniques for making sense of data and driving decisions from data. This could encompass applications of the following ML paradigms:

  • Statistical Visualizations
  • Unsupervised Learning
  • Supervised Learning
  • Semi-Supervised Learning
  • Active Learning
  • Reinforcement Learning
  • Monte-carlo techniques and probabilistic programming
  • Deep Learning

Across various data modalities including multi-variate, text, speech, time series, images, video, transactions, etc.

Track 2: Speed at Scale

This track is about tools and processes for collecting, indexing, and processing vast amounts of data. The theme includes:

  • Distributed and Parallel Computing
  • Real Time Analytics and Stream Processing
  • MapReduce and Graph Computing frameworks
  • Kafka, Spark, Hadoop, MPI
  • Stories of parallelizing sequential programs
  • Cost/Security/Disaster Management of Data

Commitment to Open Source

HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source license. If your software is commercially licensed or available under a combination of commercial and restrictive open source licenses (such as the various forms of the GPL), please consider picking up a sponsorship. We recognize that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.

Workshops

If you are interested in conducting a hands-on session on any of the topics falling under the themes of the two tracks described above, please submit a proposal under the workshops section. We also need you to tell us about your past experience in teaching and/or conducting workshops.

Hosted by

The Fifth Elephant
The Fifth Elephant
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
All submissions

ravi teja

@ravi_teja

Think Incremental with hive.

Submitted Jun 15, 2015

Section: Crisp Talk Technical level: Intermediate Session type: Demo

Hive is a data warehouse infrastructure over hadoop for summarization, query, and analysis of data.
We propose a incremental processing approach for hive.
This would optimise the data processing speeds upto ~70% .

Outline

Data is IP.
In the current day scenario, data processing at scale ,has become a necessity for every company and every system.
With scale comes challenges and need for optimisations. Incremental is one of it!

To process with scale, the de-facto tools used are MR, Hive ,Pig and Spark.
Hive holds a big chunk in these!

Running computations over the complete data every time would be very inconvenient and is inefficient way to process in many cases.
Instead computing the complete data, computing only the newly arrived data and then merging the result would be of a great use.

This approach would enable the processing to happen only the new feed into the system instead of re-processing the complete available data set.
Incremental read ,incremental joins and sidelines will be the main aspects of this approach.

Sideline of join failures for the data which hasn’t arrived yet while incremental read.

Speaker bio

Ravi Teja Chilukuri works as a Software developer at Flipkart’s Data Platform. He has been working on the processing and web-analytics layer at Flipkart. Prior to Flipkart he has been working with the data teams for Paypal and Huawei.
The speaker has given company wide talks on Yarn and Mapreduce earlier in PayPal and Huawei and is a Mapreduce and Yarn contributor at Apache Software Foundation.

Siddhartha Reddy is an Architect at Flipkart. Siddhartha Reddy and Ravi are working together on the incremental pipeline in the Data platform.

All submissions

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Hosted by

The Fifth Elephant
The Fifth Elephant
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more