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Big Data Conference
Will be several presentations:
- “IBM Big Data Platform”, Andrew Vyhodtsev, IBM
- “Data Storaging”, Evgeniy Polyakov, Yandex
- “Case: Personalization”, Anton Gorokhov, Pavel Mezentsev, Rambler
- “En . . .deca”, Olga Gorchinskaya
- and round table “real business cases for big data”
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Timing: 11:00am – 7:00pm
Theme: Media & Entertainment
Organised by Rambler
pavel@mezentsev.org
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Level: Not applicable
Format: Conference
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Teleconf “Apache Hadoop: Evolution of Architecture for Exponential Growth” by Konstantin Shvachko WANdisco (Hadoop PMC)
In this lecture, Konstantin will speak about his experience developing Hadoop, showcase challenges that occurred as data grew, and highlight how those challenges were overcome. He will also demonstrat . . .e an architecture solution that allows scaling to thousands of servers from a system of three machines.
Konstantin is Chief Architect for WANdisco (http://www.wandisco.com) and currently a member of the Apache Hadoop PMC. Previously Konstantin was Chief Scientist and founder of AltoStor and developed Hadoop at eBay and Yahoo.
A veteran Hadoop developer, Konstantin is a technical expert specializing in efficient data structures and algorithms for large-scale distributed storage systems. Dozens of publications and presentations to Konstantin’s credit include those in the fields of Big Data Storage, Distributed Computing, Data Structures, Algorithms, Computational Complexity, and Database Theory. Konstantin has a Ph.D. in Computer Science and M.S. in Mathematics from Moscow State University, Russia.
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Timing: 7:30pm – 9:00pm
Theme: Extreme Data
Organised by Rambler
pavel@mezentsev.org
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Level: Intermediate
Format: Presentation
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Teleconf “Impala: A Modern SQL Engine for Hadoop” by Justin Erickson (Cloudera)
The open-source Cloudera Impala project is for the first time making scalable parallel database technology, which is the underpinning of Google’s Dremel as well as that of commercial analytic DBMSs, a . . .vailable to the Hadoop community. With Impala, the Hadoop community now has an open-sourced codebase that allows users to issue low-latency queries to data stored in HDFS and Apache HBase using familiar SQL operators.
This talk will start out with an overview of Impala from the user’s perspective, followed by a presentation of Impala’s architecture and implementation, and will conclude with a comparison of Impala with Apache Hive, commercial MapReduce alternatives, and traditional data warehouse infrastructure.
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Timing: 9:00pm – 10.00pm
Theme: Extreme Data
Organised by Rambler
pavel@mezentsev.org
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Level: Intermediate
Format: Presentation
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