Jul 2014
21 Mon
22 Tue
23 Wed 09:30 AM – 05:00 PM IST
24 Thu 09:45 AM – 05:00 PM IST
25 Fri 08:30 AM – 07:15 PM IST
26 Sat 08:30 AM – 07:15 PM IST
27 Sun
In 2014, infrastructure components such as Hadoop, Berkeley Data Stack and other commercial tools have stabilized and are thriving. The challenges have moved higher up the stack from data collection and storage to data analysis and its presentation to users. The focus for this year’s conference on analytics – the infrastructure that powers analytics and how analytics is done.
Talks will cover various forms of analytics including real-time and opportunity analytics, and technologies and models used for analyzing data.
Proposals will be reviewed using 5 criteria:
Domain diversity – proposals will be selected from different domains – medical, insurance, banking, online transactions, retail. If there is more than one proposal from a domain, the one which meets the editorial criteria will be chosen.
Novelty – what has been done beyond the obvious.
Insights – what insights does the proposal share with the audience that they did not know earlier.
Practical versus theoretical – we are looking for applied knowledge. If the proposal covers material that can be looked up online, it will not be considered.
Conceptual versus tools-centric – tell us why, not how. Tell the audience what was the philosophy underlying your use of an application, not how an application was used.
Presentation skills – proposer’s presentation skills will be reviewed carefully and assistance provided to ensure that the material is communicated in the most precise and effective manner to the audience.
Tickets: http://fifthel.doattend.com
Website: https://fifthelephant.in/2014
For queries about proposals / submissions, write to info@hasgeek.com
Data Collection and Transport – for e.g, Opendatatoolkit, Scribe, Kafka, RabbitMQ, etc.
Data Storage, Caching and Management – Distributed storage (such as Gluster, HDFS) or hardware-specific (such as SSD or memory) or databases (Postgresql, MySQL, Infobright) or caching/storage (Memcache, Cassandra, Redis, etc).
Data Processing, Querying and Analysis – Oozie, Azkaban, scikit-learn, Mahout, Impala, Hive, Tez, etc.
Real-time analytics
Opportunity analytics
Big data and security
Big data and internet of things
Data Usage and BI (Business Intelligence) in different sectors.
Please note: the technology stacks mentioned above indicate latest technologies that will be of interest to the community. Talks should not be on the technologies per se, but how these have been used and implemented in various sectors, enterprises and contexts.
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Shalin Mangar
@shalinmangar
Submitted Jun 15, 2014
The objective of this talk is to share the challenges and learnings from setting up a large SolrCloud installation running on hundreds of nodes with thousands of collections and millions of users. This talk will also help people understand the guts of SolrCloud’s architecture.
The traditional and typical search use case is the one large search collection distributed among many nodes and shared by all users. However, there is a class of applications which need a large number of small or medium collections which can be used, managed and scaled separately. This talk will cover our effort in helping a client set up a large scale SolrCloud setup with thousands of collections running on hundreds of nodes. I will describe the bottlenecks that we found in SolrCloud when running a large number of collections. I will also take you through the multiple features and optimisations that we contributed to Apache Solr to reduce or remove the choke points in the system. Finally, I will talk about the benchmarking process and the lessons learned from the exercise.
Familiarity with Solr and SolrCloud is a must. I will explain certain concepts that might not be well known but this is by no means an introductory talk.
I am a committer on Apache Lucene/Solr since 2008 as well as a member of the Lucene/Solr project management committee. I’ve worked at AOL for five years on vertical search, content mangement systems, social/community platforms and anti-spam systems as well as AOL WebMail’s Inbox Search system which uses a highly customized version of Apache Solr to service tens of millions of users and more than a billion index/search operations a day. I currently work at LucidWorks Inc. on Apache Solr and LucidWorks Search mostly on the SolrCloud side of things. I also help organize the Bangalore Apache Solr/Lucene Meetup Group which has 350+ members and holds regular meetings of people interested in Lucene, Solr and search in general.
https://twitter.com/shalinmangar
http://www.meetup.com/Bangalore-Apache-Solr-Lucene-Group/
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