Name: April: Lightning-Fast Cluster Computing with Spark and Shark
Start: 2013-04-16T18:30:00-04:00
End: 2013-04-16T21:30:00-04:00
Location: Bronto Software, Inc.

Speakers: Mayuresh Kunjir (http://www.cs.duke.edu/people/graduate/?csid=0004030) and Harold Lim (http://www.cs.duke.edu/people/graduate/?csid=0002030), Duke University

Spark is an open-source cluster-computing system developed by the AMPLab at the University of California, Berkeley. Spark provides very fast performance and ease of development for a variety of data analytics needs such as machine learning, graph processing, and SQL-like queries. Spark supports distributed in-memory computations that can be up to 100x faster than Hadoop.

Shark is a Hive-compatible data warehousing system built on Spark. Shark supports the HiveQL query language, the Hive Metastore, and all the serialization formats supported by Hive. The use of Spark and a number of built-in optimizations make Shark perform up to 100x faster than Hive.

This talk will discuss the internals of Spark and Shark, the applications that these systems support, and show a demo that includes performance comparisons with Hive.

Jeff Turner

Triangle Hadoop Users Group

Technology

New Technology

Cloud Computing

User Group

Hadoop

Big Data

MapReduce

Data Analytics

Hive

Apache Hbase

HDFS

April: Lightning-Fast Cluster Computing with Spark and Shark

Bronto Software, Inc.

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April: Lightning-Fast Cluster Computing with Spark and Shark

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