Tuesday 6th October, 2015
11:30am to 12:20pm
NoSQL databases have a limited query languages that are not suitable for analytical request. The classical solution provided by most of them is a Hadoop integration. That is not fast. Thus a number of fast distributed, parallel query/computation engines appears recently to fix Hadoop performance problems.
The presentation will show how to solve classical data analytic task by using modern distributed databases and in-memory engines using as example Spark and Cassandra. It will cover following topics:
Apache Spark benefits, architecture and Scala API. (Don't be afraid of Scala, we are here to help you)
Load and store data from Cassandra NoSQL database
Data enrichments and joins
Spark Machine learning and graph algorithms
Target audience: Software engineers and solution architects using or planning to use NoSql products for analytics, particularly Cassandra and Spark.
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